Magnetic Resonance Spectroscopy (MRS)

Number: 0202

Table Of Contents

Policy
Applicable CPT / HCPCS / ICD-10 Codes
Background
References


Policy

Scope of Policy

This Clinical Policy Bulletin addresses magnetic resonance dpectroscopy (MRS).

  1. Medical Necessity

    Aetna considers magnetic resonance spectroscopy (MRS) (also known as NMR spectroscopy) medically necessary for the following indications:

    1. Assessing prognosis in hypoxic ischemic encephalopathy;
    2. Distinguishing low grade from high grade gliomas;
    3. Evaluate a brain lesion of indeterminate nature when the MRS findings will be used to determine whether biopsy/resection can be safely postponed;
    4. Distinguishing recurrent brain tumor from radiation-induced tumor necrosis;
    5. Diagnosis and monitoring of the following metabolic disorders:

      1. Canavan disease;
      2. Creatine deficiency;
      3. Nonketotic hyperglycinemia;
      4. Maple Syrup Urine disease;
    6. Diagnosis of the following disorders:

      1. Metachromatic leukodystrophy (MCL);
      2. Pelizaeus-Merzbacher disease (PMD);
      3. Hypomyelination and Congenital Cataract;
      4. Globoid Cell Leukodystrophy (Krabbe disease);
      5. X-linked adrenoleukodystrophy (X-ALD, CALD);
      6. Mitochondrial disorders (e.g. Leigh’s syndrome, Kearns-Sayre syndrome, MELAS, et al);
      7. Alexander disease (ALX, AXD, demyelinogenic leukodystrophy);
      8. Megalencephalic leukoencephalopathy with subcortical cysts;
      9. Vanishing White Matter disease (Leukoencephalopathy with vanishing white
        matter, CACH syndrome, CACH/VWM).

      Note: MRS is considered medically necessary for disease monitoring of these diagnoses when recent MRI findings are inconclusive and a change in therapy is being considered. 

  2. Experimental and Investigational

    Magnetic resonance spectroscopy (MRS) (also known as NMR spectroscopy) is considered experimental and investigational for all other indications, including the following (not an all-inclusive list) because there is a lack of reliable evidence of its efficacy for these indications in the medical literature:

    1. Breast cancer;
    2. Cerebrovascular diseases/disorders/injuries;
    3. Dementia and movement disorders (e.g., Alzheimer's disease, dementia with Lewy bodies, frontotemporal dementia, Huntington disease, motor neuron disease, normal-pressure hydrocephalus, Parkinson disease/Parkinsonian syndromes, vascular dementia);
    4. Dermatomyositis;
    5. Detection and quantification of hepatic steatosis in living liver donors;
    6. Detection of central nervous system involvement in individuals with rheumatic autoimmune diseases;
    7. Detection of esophageal squamous cell carcinoma;
    8. Diagnosis of mesial temporal sclerosis;
    9. Differentiatiation of primary central nervous system lymphoma (PCNSL) from other focal brain lesions;
    10. Epilepsy (including juvenile myoclonic epilepsy, and temporal lobe epilepsy);
    11. Evaluation of hepatic encephalopathy;
    12. Evaluation of migraine pathophysiology and identification of biomarkers in migraine;
    13. Evaluation of post-traumatic stress disorder;
    14. Head trauma;
    15. Identification of metabolomic profile in individuals with idiopathic intracranial hypertension;
    16. Low back pain;
    17. Lyme neuroborreliosis;
    18. Monitoring hepatocellular carcinoma and liver cirrhosis development;
    19. Mucopolysaccharidosis;
    20. Multiple sclerosis;
    21. Polymyositis;
    22. Prediction of neurodevelopmental impairment in preterm neonates;
    23. Prognosis of consciousness recovery in individuals with vegetative state;
    24. Prostate cancer;
    25. Psychiatric disorders (e.g., attention-deficit/hyperactivity disorder, autism spectrum disorders, bipolar disorder, depression, emotional dysregulation, mood disorders, obsessive-compulsive disorder, psychosis, and schizophrenia);
    26. Radiation encephalopathy;
    27. Sport-related concussion;
    28. Substance use disorders;
    29. Traumatic brain injury.

Table:

CPT Codes / HCPCS Codes / ICD-10 Codes

Code Code Description

CPT codes covered for indications listed in the CPB:

76390 Magnetic resonance spectroscopy

CPT codes not covered for indications listed in the CPB:

0609T Magnetic resonance spectroscopy, determination and localization of discogenic pain (cervical, thoracic, or lumbar); acquisition of single voxel data, per disc, on biomarkers (ie, lactic acid, carbohydrate, alanine, laal, propionic acid, proteoglycan, and collagen) in at least 3 discs
0610T     transmission of biomarker data for software analysis
0611T     postprocessing for algorithmic analysis of biomarker data for determination of relative chemical differences between discs
0612T     interpretation and report

ICD-10 codes covered if selection criteria are met:

C71.0 - C71.9 Malignant neoplasm of brain [not covered for differentiating primary central nervous system lymphoma (PCNSL) from other focal brain lesions]
C78.31 Secondary malignant neoplasm of brain [not covered for differentiating primary central nervous system lymphoma (PCNSL) from other focal brain lesions]
D33.0 - D33.2 Benign neoplasm of brain [not covered for differentiating primary central nervous system lymphoma (PCNSL) from other focal brain lesions]
D43.0 - D43.2 Neoplasm of uncertain behavior of brain [not covered for differentiating primary central nervous system lymphoma (PCNSL) from other focal brain lesions]
D49.6 Neoplasm of unspecified behavior of brain [not covered for differentiating primary central nervous system lymphoma (PCNSL) from other focal brain lesions]
E71.0 Maple Syrup Urine disease
E71.2 Disorder of branched-chain amino-acid metabolism, unspecified [Creatine deficiency]
E71.520 – E71.529 X-linked adrenoleukodystrophy
E72.51 Nonketoic hyperglycinemia
E75.23 Krabbe disease
E75.25 Metachromatic leukodystrophy
E75.29 Other sphingolipidosis [Canavan disease, Pelizaeus-Merzbacher disease, Alexander disease]
E88.40 – E88.49 Mitochondrial metabolism disorders
G31.82 Leigh's disease
G37.9 Demyelinating disease of central nervous system, unspecified
G93.49 Other encephalopathy [Megalencephalic leukoencephalopathy with subcortical cysts]
H49.811 – H49.819 Kearns-Sayre syndrome
P91.60 - P91.63 Hypoxic ischemic encephalopathy
R90.82 White matter disease, unspecified [Vanishing White Matter disease]
T66.xxx+ Radiation sickness, unspecified [necrosis of brain] [not covered for differentiating primary central nervous system lymphoma (PCNSL) from other focal brain lesions]

ICD-10 codes not covered for indications listed in the CPB (not all-inclusive):

A69.20 - A69.29 Lyme disease
C15.3 - C15.9 Malignant neoplasm of esophagus
C22.0 - C22.9 Malignant neoplasm of liver and intrahepatic bile ducts
C50.011 - C50.929 Malignant neoplasm of breast (male and female)
C61 Malignant neoplasm of prostate
C72.9 Malignant neoplasm of central nervous system, unspecified [Primary central nervous system (CNS) lymphoma]
C79.49 Secondary malignant neoplasm of spinal cord
C79.81 Secondary malignant neoplasm of breast
C79.82 Secondary malignant neoplasm of genital organs [prostate]
D05.00 - D05.92 Carcinoma in situ of breast
D07.5 Carcinoma in situ of prostate
D24.1 - D24.9 Benign neoplasm of breast
D29.1 Benign neoplasm of prostate
D40.0 Neoplasm of uncertain behavior of prostate
D43.0 - D43.2, D43.4 Neoplasm of uncertain behavior of brain and spinal cord [covered for distinguishing recurrent brain tumor from radiation necrosis]
D48.60 - D48.62 Neoplasm of uncertain behavior of breast
D49.3 Neoplasm of unspecified behavior of breast
D49.511 - D49.59 Neoplasm of unspecified behavior of other genitourinary organs
E70.0 - E70.9, E71.110 - E71.19, E71.30 - E71.518, E71.53 - E72.50, E72.52 - E75.22, E75.240 - E75.249, E75.26, E75.3 - E88.3, E88.81 - E88.89 Metabolic disorders
F01.50 - F01.C4 Dementia
F02.80 - F02.C4 Dementia in other diseases classified elsewhere with or without behavioral disturbance
F03.90 - F03.C4 Unspecified dementia, with our without behavioral disturbance
F05 Delirium due to known physiological condition
F10.27 Alcohol dependence with alcohol-induced persisting dementia
F10.97 Alcohol use, unspecified with alcohol-induced persisting dementia
F11.10 - F16.99 Substance abuse disorders
F18.17, F18.27, F18.97, F19.17, F19.27, F19.97 Drug induced persisting dementia
F20.81 - F29 Schizophrenia, schizotypal, delusional, and other non-mood psychotic disorders
F30.10 - F39 Mood [affective] disorders
F42.2 - F42.9 Obsessive-compulsive disorder
F43.0 Acute stress reaction
F43.10 - F43.12 Post-traumatic stress disorder (PTSD)
F43.25 Adjustment disorder with mixed disturbance of emotions and conduct
F60.89 Other specific personality disorders
F84.0 Autistic disorder
F84.2 Rett's syndrome
F90.0 - F90.9 Attention deficit hyperactivity disorders
F98.4 Stereotyped movement disorders
G13.2 - G13.8 Systemic atrophy primarily affecting central nervous system in diseases classified elsewhere
G20 - G21.9 Parkinson's disease
G23.0 - G26 Extrapyramidal and movement disorders
G30.0 - G31.1 Alzheimer's disease and other degenerative diseases of nervous system, not elsewhere classified
G31.81, G31.83 - G31.9 Other specified degenerative diseases of nervous system
G35 Multiple sclerosis
G40.001 - G40.919 Epilepsy and recurrent seizures
G43.001 - G43.919 Migraine headache
G45.0 - G45.2
G45.4 - G46.2
Transient cerebral ischemic attacks and related syndromes, and cerebral artery syndrome
G47.61 Periodic limb movement disorder
G47.69 Other sleep related movement disorders
G91.0 - G91.9 Hydrocephalus
G93.2 Benign intracranial hypertension
G93.7 Reye's syndrome
G93.81 Temporal sclerosis
G93.89 - G94 Other and unspecified disorders of the brain
I63.00 - I66.9 Cerebral infarction, occlusion and stenosis of cerebral and precerebral arteries not resulting in cerebral infarction
I67.1 - I67.2
I67.4 - I67.9
I68.0 - I68.8
I69.00 - I69.998
Cerebrovascular diseases and disorders
K70.0 Alcoholic fatty liver
K72.00 - K72.91 Hepatic failure [hepatic encephalopathy]
K74. 0 - K74.69 Fibrosis and cirrhosis of liver
K76.0 Fatty (change of) liver, not elsewhere classified
L40.0 - L40.9 Psoriasis
M05.00 – M06.9 Rheumatoid arthritis
M08.00 - M08.9A Unspecified juvenile rheumatoid arthritis
M32.0 - M32.9 Systemic lupus erythematosus
M33.00 - M33.99 Dermatopolymyositis
M34.0 – M34.9 Systemic sclerosis
M35.00 - M35.09 Sjogren's syndrome
M35.2 Behcet's disease
M54.5 Low back pain
P07.30 - P07.39 Disorders of newborn related to short gestation and low birth weight, not elsewhere classified [Prediction of neurodevelopmental impairment]
R40.3 Persistent vegetative state
S02.0xx+ - S02.92x+ Fracture of skull and facial bones
S06.0x0+ - S06.9x9+ Intracranial injury
S09.8xxA - S09.90xS Specified and unspecified head injury
T86.40 - T86.49 Complications of liver transplant
Z52.6 Liver donor

Background

Magnetic resonance spectroscopy (MRS), also known as nuclear magnetic resonance (NMR) spectroscopy, is a non-invasive analytical technique that has been used to study metabolic changes in brain tumors, strokes, seizure disorders, Alzheimer's disease, depression and other diseases affecting the brain.  It has also been used to study the metabolism of other organs.

Magnetic resonance spectroscopy can be done as part of a routine magnetic resonance imaging (MRI) on commercially available MRI instruments. The probe accessory necessary to perform MRS was granted 510(k) clearance from the Food and Drug Administration (FDA). Magnetic resonance spectroscopy and MRI use different software to acquire and mathematically manipulate the signal. Whereas MRI creates an image, MRS creates a graph or "spectrum" arraying the types and quantity of chemicals in the brain or other organs.

The role of MRS in diagnosis and therapeutic planning has not been established by adequate clinical studies. Specifically, there have been no clinical trials demonstrating improved outcomes in patients evaluated with MRS compared to patients evaluated with conventional imaging modalities.

Guidelines on central nervous system cancers from the National Comprehensive Cancer Network (NCCN, 2016) state that magnetic resonance spectroscopy may be useful in anaplastic gliomas and glioblastoma to differente tumor from radiation necrosis ("pseudoprogression").

Zhang et al (2014) conducted a meta-analysis to evaluate the diagnostic quality of magnetic resonance spectroscopy (MRS) in differentiating glioma recurrence from radiation necrosis. Studies about evaluation of MRS for the differential diagnosis of glioma recurrence from radiation necrosis were systematically searched in PubMed, Embase and Chinese Biomedical databases up to May 4, 2014. The data were extracted to perform heterogeneity test, threshold effect test and to calculate sensitivity (SEN), specificity (SPE) and areas under summary receiver operating characteristic curve (SROC). Eighteen articles comprising a total sample size of 455 patients (447 lesions) with suspected glioma recurrence after radiotherapy, met all inclusion and exclusion criteria, and were included in our meta-analysis. Quantitative synthesis of studies showed that the pooled SEN and SPE for Cho/Cr ratio were 0.83 (95% confidence interval [CI]: 0.77, 0.89) and 0.83 (95% CI: 0.74, 0.90). The area under the curve (AUC) under the SROC was 0.9001. The pooled SEN and SPE for Cho/NAA ratio were 0.88 (95% CI: 0.81, 0.93) and 0.86 (95% CI: 0.76, 0.93). The AUC under the SROC was 0.9185. The authors concluded that this meta-analysis shows that MRS alone has moderate diagnostic performance in differentiating glioma recurrence from radiation necrosis using metabolite ratios like Cho/Cr and Cho/NAA ratio. The authors strongly recommended that MRS should combine other advanced imaging technologies to improve diagnostic accuracy. This authors states that this metaanalysis underlines the importance of implementing multimodal imaging trials and multicentre trials in the future.

Chuang et al (2016) conducted a metaanalysis examining the roles of several metabolites in differentiating recurrent tumor from necrosis in patients with brain tumors using MR perfusion and spectroscopy. Medline, Cochrane, EMBASE, and Google Scholar were searched for studies using perfusion MRI and/or MR spectroscopy published up to March 4, 2015 which differentiated between recurrent tumor vs. necrosis in patients with primary brain tumors or brain metastasis. Only two-armed, prospective or retrospective studies were included. A meta-analysis was performed on the difference in relative cerebral blood volume (rCBV), ratios of choline/creatine (Cho/Cr) and/or choline/N-acetyl aspartate (Cho/NAA) between participants undergoing MRI evaluation. A χ2-based test of homogeneity was performed using Cochran's Q statistic and I2. Of 397 patients in 13 studies who were analyzed, the majority had tumor  recurrence. As there was evidence of heterogeneity among 10 of the studies which used rCBV for evaluation (Q statistic = 31.634, I2 = 97.11%, P < 0.0001) amrandom-effects analysis was applied. The pooled difference in means (2.18, 95% CI: 0.85 to 3.50) indicated that the average rCBV in a contrast-enhancing lesion was significantly higher in tumor recurrence compared with radiation injury (P = 0.001). Based on a fixed-effect model of analysis encompassing the six studies which used Cho/Cr ratios for evaluation (Q statistic = 8.388, I2 = 40.39%, P = 0.137), the pooled difference in means (0.77, 95% CI: 0.57 to 0.98) of the average Cho/Cr ratio was significantly higher in tumor recurrence than in tumor necrosis (P = 0.001). There was significant difference in ratios of Cho to NAA between recurrent tumor and necrosis (1.02, 95% CI: 0.03 to 2.00, P = 0.044). The authors concluded that MRS using Cho/NAA and Cho/Cr ratios and rCBV may increase the accuracy of differentiating necrosis from recurrent tumor in patients with primary brain tumors or metastases.

The consensus in the literature is that further studies are necessary to determine MRS' role in the diagnosing and planning treatment in neurological diseases.

Magnetic resonance spectroscopy (MRS) in the evaluation of brain tumors (either primary tumors or brain metastases) is considered investigational/experimental because there is inadequate evidence in the published peer-reviewed clinical literature regarding its effectiveness.

An assessment of MRS prepared by the Tuft's-New England Medical Center Evidence-Based Practice Center for the Agency for Healthcare Research and Quality (AHRQ) (Jordan et al, 2003) reached the following conclusions: “[h]uman studies conducted on the use of MRS for brain tumors demonstrate that this non-invasive method is technically feasible and suggest potential benefits for some of the proposed indications. However, there is a paucity of high quality direct evidence demonstrating the impact on diagnostic thinking and therapeutic decision-making.  In addition, the techniques of acquiring the MRS spectra and interpreting the results are not well standardized.  In summary, while there are a large number of studies that confirm MRS' technical feasibility, there are very few published studies to evaluate its diagnostic accuracy and whether it can positively affect diagnostic thinking and therapeutic choice. Those studies that do address these areas often have significant design flaws including inadequate sample size, retrospective design and other limitations that could bias the results.”

A structured evidence review of MRS for evaluation of suspected brain tumor conducted by the BlueCross BlueShield Association Technology Evaluation Center (2003) concluded that “[t]he evidence is insufficient to permit conclusions concerning the effect of magnetic resonance spectroscopy on health outcomes.”

The Center for Medicare and Medicaid Services (CMS, 2004) has determined that there is insufficient evidence to deem MRS “reasonable and necessary” for brain tumor diagnosis. Due to “methodological shortcomings” in the 11 studies reviewed on the use of MRS for brain lesion detection and a lack of a controlled comparison of MRS and traditional diagnostic strategies, CMS has announced that it will continue its current national non-coverage determination.

Gluch (2005) stated that ex vivo and in vivo applications of MRS have been developed, which aid in distinguishing malignant from normal tissues. Studies of breast, colon, cervix, esophageal, and prostate cancer reveal both the successes and failings of present technology. The author noted that verification that these non-invasive tests might supplant conventional histology in obtaining spatial diagnostic and chemical prognostic information remains for the time being illusive.

Willmann et al (2006) evaluated the additional pre-operative value of (1)H MRS in identifying the epileptogenic zone (EZ) for epilepsy surgery by performing a meta-analysis. The authors concluded that MRS still remains a research tool with clinical potential. Their findings indicated the connection of ipsilateral MRS abnormality to good outcome. The ability for prediction of post-operative outcome may depend on the assessed population. They noted that prospective studies limited to non-localized ictal scalp electroencephalography or MRI-negative patients are needed for validation of these data. Furthermore, Hollingworth et al (2006) stated that (1)H MRS is a potentially useful adjunct to anatomical MRI in the characterization of brain tumors. These investigators performed an updated systematic review of the evidence. They concluded that the current evidence on the accuracy of (1)H MRS in the characterization of brain tumors is promising. However, additional high-quality studies are needed to convince policy makers.

The clinical evidence is not sufficient to permit conclusions on the health outcome effects of magnetic resonance spectroscopy in the evaluation of prostate cancer. Magnetic resonance spectroscopy (MRS)  provides metabolic information about the prostate gland by assessing the prostatic metabolites choline and citrate. Alterations in levels of these metabolites may provide prognostic information that may be useful for treatment planning.

According to Jung and Westphalen (2012) studies have demonstrated that the addition of proton magnetic resonance spectroscopic imaging (1H-MRSI) to T2-weighted MR imaging improves tumor localization, volume estimation, staging, tissue characterization, and identification of recurrent disease after therapy. A recent multicenter study supported by the American College of Radiology Imaging Network, however, showed that the combination of 1H-MRSI and T2-weighted MR images does not improve tumor detection in patients with low-grade, low-volume disease selected to undergo radical prostatectomy. These results suggest that positive 1H-MRSI findings are more likely to reflect higher tumor grade and/or volume.

NCCN Clinical Practice Guidelines in Oncology for prostate cancer (2011) state: “A negative biopsy following post-radiation biochemical recurrence poses clinical uncertainties. Observation, androgen deprivation therapy (ADT), or enrolling in clinical trials are viable options. Alternatively, the patients may undergo more aggressive workup, such as repeat biopsy, MR spectroscopy, and/or endorectal MRI.”

According to the textbook Wein: Campbell-Walsh Urology (2011), in the initial evaluation of the patient with prostate cancer, tumor-selective imaging tests, such as monoclonal antibody scans, positron emission tomographic scans, magnetic resonance spectroscopy, and lymphotrophic magnetic resonsance imaging (MRI) are not widely used, although they might prove more useful in the future. The use of MRI, alone or in combination with MRS for tumor staging remains controversial. Current research involves the use of magnetic resonance spectroscopy to guide radiation administration by directing higher doses to the metabolically active areas of the tumor. Magnetic resonance spectroscopy–optimized implants are also under study to give higher doses to metabolically active regions of the tumor.

The textbook Abeloff’s Clinical Oncology (2008) states that new imaging technologies, including MRS give great potential for improving the assessment of local and distant prostate cancer extent.

In a retrospective trial, Fradet et al (2010) studied the role that MRI and MRS findings obtained at the time of diagnosis play in the progression of disease in patients whose prostate cancer is being managed with active surveillance and compared the role of these findings with the role of transrectal ultrasonography (US) findings. The final cohort included 114 patients with a median follow-up of 59 months. Two urologists blinded to the clinical outcome in these patients independently reviewed and dichotomized the MRI report and the MRS imaging report as normal or suggestive of malignancy. One urologist performed all US examinations that were then dichotomized similarly. Patients with a lesion that was suggestive of cancer at MRI had a greater risk of the Gleason score being upgraded at subsequent biopsy (hazard ratio, 4.0; 95% confidence interval: 1.1, 14.9) than did patients without such a lesion. Neither MRS imaging nor transrectal US could be used to predict cancer progression.

Westphalen and colleagues (2010), in a retrospective single-institution study, compared resonance (MR) spectroscopic imaging with T2-weighted MR imaging alone in the detection of locally recurrent prostate cancer after definitive external beam radiation therapy. Sixty-four men who underwent endorectal MR imaging, MR spectroscopic imaging, and transrectal ultrasonographically guided biopsy for suspected local recurrence of prostate cancer after definitive external beam radiation therapy were retrospectively identified. Thirty-three patients had also received androgen therapy. Recurrent cancer was determined to be present or absent in the left and right sides of the prostate at T2-weighted MR imaging and MR spectroscopic imaging by a radiologist and a spectroscopist, respectively. Area under the receiver operating characteristic curve (A(Z)) was calculated for T2-weighted MR imaging alone and combined T2-weighted MR imaging and MR spectroscopic imaging by using generalized estimating equations and by using biopsy results as the reference standard. Recurrent prostate cancer was identified at biopsy in 37 (58%) of the 64 men. Recurrence was unilateral in 28 patients and bilateral in nine (total of 46 affected prostate sides). A(Z) analysis revealed that use of combined T2-weighted MR imaging and MR spectroscopic imaging (A(Z) = 0.79), as compared with T2-weighted MR imaging alone (A(Z) = 0.67), significantly improved the detection of local recurrence (P = .001). The addition of MR spectroscopic imaging to T2-weighted MR imaging was found to significantly improve the diagnostic accuracy of endorectal MR imaging in the detection of locally recurrent prostate cancer after definitive external beam radiation therapy.

Zakian and colleagues (2005) evaluated whether hydrogen 1 MR spectroscopic imaging can be used to predict aggressiveness of prostate cancer. A total of 123 patients (median age, 58 years; age range, 40-74 years) who underwent endorectal MRI and MR spectroscopic imaging between January 2000 and December 2002 were included. MR imaging and spectroscopy were performed by using combined pelvic phased-array and endorectal probe. Data from 94 patients were included. Pathologic evaluation was used to identify 239 lesions. Overall sensitivity of MR spectroscopic imaging was 56% for tumor detection, increasing from 44% in lesions with Gleason score of 3 + 3 to 89% in lesions with Gleason score greater than or equal to 4 + 4. There was a trend toward increasing (Cho + Cr)/Cit with increasing Gleason score in lesions identified correctly with MR spectroscopic imaging. Tumor volume assessed with MR spectroscopic imaging increased with increasing Gleason score.

Kline et al (2006) measured citrate in samples from 61 participants, of whom 16 without and 21 with cancer donated semen, and 17 without and 7 with cancer donated expressed prostatic secretions. Mean citrate +/- SE compared to that in controls was 2.7-fold lower in patients with cancer samples in semen (132.2 +/- 30.1 versus 48.0 +/- 7.9 mM, p < 0.05) and expressed prostatic secretions (221.4 +/- 55.4 versus 81.5 +/- 36.0 mM, p < 0.05). ROC curve analysis showed that measurements of citrate in semen performed as well as measurements of citrate in expressed prostatic secretion for detecting prostate cancer (AUC 0.81, 95% CI: 0.60 to 0.92 and AUC 0.73, 95% CI: 0.38 to 0.90, respectively, p > 0.05). ROC curve analysis also showed that the measurement of citrate in either fluid outperformed prostate specific antigen measurement for detecting prostate cancer in these subjects (AUC 0.61, 95% CI: 0.44 to 0.74). The authors concluded that in vitro nuclear MRS measurement of the citrate concentration in semen or expressed prostatic secretions outperforms prostate specific antigen testing for detecting prostate cancer.

Wetter et al (2006) examined fifty patients with biopsy-proven prostate carcinoma. For spectroscopy, a 3D chemical shift imaging (CSI) spin-echo sequence was used. Image interpretation was performed by 2 radiologists. The total number of tumor voxels and tumor voxels per slice were counted to estimate the tumor volume in every patient.  The potential of MR spectroscopy to differentiate between T2 and T3 tumors, based on the estimated tumor volumes, was compared with the staging performance of MRI.  The MR measurement time was 19.01 minutes, and the total procedure time averaged 35 minutes. Seventy-six percent of the spectroscopic examinations were successful. Statistically significant differences in the number of tumor voxels per slice and tumor volumes were found between T2 and T3 tumors. The descriptive parameters of MRI and MR spectroscopy did not differ significantly; sensitivity and specificity were 75% and 87%, respectively, for MRI and 88% and 70%, respectively, for MR spectroscopy. The combination of both methods resulted in only a slight improvement in staging performance and was not statistically significant. The authors concluded that combined MRI and MRS of the prostate has no diagnostic advantage in staging performance over MRI alone.

According to Shah et al (2006), “although MRS has mainly been used in diagnostics and tumor evaluation for brain cancer, it is becoming an increasingly important adjunct to conventional diagnostic and monitoring procedures for cancer of the prostate, colon, breast, cervix, pancreas, and esophagus. The clinical usefulness of MRS has yet to be fully substantiated”.

Rajesh et al (2007) noted that 3D MRS is emerging as a new and sensitive tool in the metabolic evaluation of prostate cancer. Zapotoczna et al (2007) stated that the increasing sensitivity and specificity of MRS to the prostate is causing new interest in its potential role in the definition of target subvolumes at higher risk of failure following radical radiotherapy. Prostate MRS might also play a role as a non-invasive predictive factor for tumor response and treatment outcome. However, guidelnes on the pre-treatment staging of prostate cancer by the American College of Radiology (ACR)'s expert panel on urologic imaging and radiation oncology (Israel et al, 2007) stated that one group of investigators have demonstrated that prostate cancers have a characteristic loss of the citrate peak and gain in the choline/creatine peak on MRS imaging. Moreover, the ratio of choline to citrate is related to the Gleason score, suggesting that MRS imaging may provide information about tumor aggressiveness. Improvements in diagnostic accuracy and staging have been reported.  However, MRS imaging is technically demanding and time consuming.  It has not been proven in multi-institutional trials, although a clinical trial under the auspices of the American College of Radiology Imaging Network (ACRIN) is currently underway.  Thus, MRS imaging can not yet be considered a routine diagnostic tool.

In a meta-analysis of the accuracy of prostate cancer studies which use MRS as a diagnostic tool, Wang et al (2008) concluded that as a new method in the diagnosis of prostate cancer, MRS has a better applied value compared to other common modalities. Ultimately, large scale randomized controlled trial studies are needed to evaluate its clinical value.

The clinical evidence is not sufficient to support the use of magnetic resonance spectroscopy in the evaluation of mucopolysaccharidosis. Vedolin and colleagues (2007) examined the influence of aging on conventional MRI and MRS findings of patients with mucopolysaccharidosis (MPS), and tested the correlation of enzyme levels, urinary glycosaminoglycans (GAG), and neuroimaging findings. A total of 60 patients with MPS types I (n = 8), II (n = 31), IV-A (n = 4), and VI (n = 17) underwent T2, fluid-attenuated inversion recovery (FLAIR), and MRS of the brain. For analysis of MRI variables, the researchers measured the normalized cerebral volume (NCV), normalized cerebrospinal fluid volume (NCSFV), normalized ventricular volume (NVV), and normalized lesion load (NLL) on FLAIR using semi-automated and automated segmentation techniques. For MRS, a point-resolved spectroscopy technique was used. Voxels were positioned at the white and gray matter. Statistical analysis involved Pearson or Spearman tests for correlation between neuroimaging, age, enzyme levels, and urinary GAG.  The median age at onset of the disease was 20 months. Patients with longer disease duration had more NLL in the white matter (r = 0.28, p = 0.03), and this difference was more pronounced in MPS II patients (r = 0.44, p = 0.02). Metabolites ratios in MRS, NCV, NCSFV, and NVV did not correlate with disease duration or age of the patients (p > 0.05). Magnetic resonance imaging and MRS variables in either the white or the gray matter did not correlate with enzymatic activity or GAG levels. Patients with MPS II had a lower mean NCV (p < 0.001). The authors concluded that these findings showed that white matter lesion is more extensive as disease duration increases, especially in mucopolysaccharidosis type II patients. Magnetic resonance imaging and MRS findings did not correlate with either enzymatic or glycosaminoglycan levels.

Boesch et al (2007) evalauted and compared biochemical and volumetric features of the cerebellum in patients with spino-cerebellar ataxia type 2 (SCA2) and patients with the cerebellar variant of multiple system atrophy (MSA-C). Nine genetically assigned SCA2 patients and 6 MSA-C patients who met the clinical criteria of MSA-C underwent a clinical and neuro-radiological work-up with respect to cerebellar features. The MR protocol consisted of a sagittal T1-weighted 3-dimensional fast low-angle shot (3D FLASH) sequence and a transversal T2- and spin-density-weighted turbo spin-echo sequence. The proton magnetic resonance spectroscopic imaging ((1)H-MRSI) protocol consisted of 2 chemical shift imaging (CSI) sequences (echo time (TE) = 20 and 135 msec). Both short- and long-TE MRS images showed significant decreases in values for N-acetylaspartate to creatine (NAA/Cr), and choline to creatine (Cho/Cr) ratios in MSA-C and SCA2 compared to normal controls, though there was no difference between the 2 patient groups.  In contrast, distinct cerebellar lactate (Lac) peaks were detected in 7 SCA2 patients, and small peaks were detected in 2. However, these investigators did not detect any definite Lac peak in MSA-C or control subjects. The authors concluded that MRSI revealed Lac pathology in SCA2 but not in MSA-C. Whether this indicates distinct pathogenetic mechanisms of cerebellar degeneration remains to be established.

Dyke et al (2007) explored (1)H MRSI as a means to assess peri-tumoral tissue response post-resection and Gliadel((R)) implantation in patients with high-grade gliomas. Pilot (1)H MRSI data are presented that demonstrate non-invasive, serial monitoring of metabolic changes at the tumor site following Gliadel implantation. Three patients with newly diagnosed glioblastoma multiforme (GBM) underwent MRI and (1)H MRSI at 3.0 Tesla prior to resection and at 3 to 5 and greater than or equal to 12 weeks post-operatively. Baseline MRS spectra of tumor tissue from all patients were characterized by marked increases of choline (CHO) and lactate (LAC), and a decrease of N-acetylaspartate (NAA), typical of GBM compared with normal contra-lateral brain tissue. Post-operatively, spectra were analyzed from the resection cavity and peri-tumoral regions and compared with normal tissue from the contra-lateral brain at baseline.  In 2 of 3 patients, peri-tumoral NAA/CRE increased and CHO/NAA decreased compared to contra-lateral brain at 3 to 5 weeks compared with baseline following Gliadel therapy and surgery but prior to radiotherapy. This study indicated that (1)H MRSI has the ability to localize regions of heterogeneous response following Gliadel treatment. Although data are limited, these results suggested that metabolic indicators of outcome can be successfully monitored pre- and post-surgical resection and Gliadel implantation with (1)H MRSI. Additional study of patients receiving Gliadel Wafers using (1)H MRSI may serve to aid clinicians in assessing tumor regression and gauging efficacy of this chemotherapy treatment.

De Stefano et al (2007) reviewed current MRS clinical applications in multiple scloersis (MS), and discussed the potential and limitations of the technique, and suggested recommendations for the application of MRS to clinical trials. The authors concluded that despite some important limitations, proton MRS has the potential to be implemented in large, multi-centered clinical trials of MS. The usefulness of MRS-derived outcome measures in MS clinical trial has yet to be proven....Future studies and the few clinical trials that are currently incorporating MRS into their imaging protocols will reveal if MRS has a role in quantifying the impact of therapeutic intervention on tissue damage in MS and will help to determine if MRS can become a standard and accepted part of the assessment of MS treatment in the near future. European Federation of Neurological Societies guidelines on the use of neuroimaging in the management of MS (Filippi et al, 2006) noted that the performance and contribution of diffusion tensor MRI (DT-MRI) and MRS) in multi-center studies still have to be evaluated.

Biomarkers of disc degeneration have been previously described using NMR spectroscopy, but the link between discogenic back pain and biomarkers has not been completely understood. Keshari et al (2008) used quantitative ex vivo proton high resolution magic angle spinning (HR-MAS) NMR spectroscopy to identify biochemical markers associated with discogenic back pain. HR-MAS NMR spectroscopy was performed on snap frozen samples taken from 9 patients who underwent discectomies for painful disc degeneration. The resulting proton NMR spectrums were compared with those from discs harvested from a reference population consisting of 9 scoliosis patients. Spectral analyses demonstrated significantly lower proteoglycan (PG)/collagen (0.31 +/- 0.22 versus 0.77 +/- 0.48) and PG/lactate (0.46 +/- 0.24 versus 2.24 +/- 1.11) ratios, and a higher lactate/collagen (0.77 +/- 0.49 versus 0.40 +/- 0.21) ratio in specimens obtained from discogenic pain patients when compared with scoliosis patients. The authors concluded that these findings suggested that spectroscopic markers of proteoglycan, collagen, and lactate may serve as metabolic markers of discogenic back pain. These results provided a further basis of the potential to develop in vivo MRS for the investigation of discogenic back pain.

Gornet, et al. (2019) sought to refine clinical MRS to optimize performance and then determine whether MRS-derived biomarkers reliably identify painful discs, quantify degeneration severity, and forecast surgical outcomes for chronic low back pain (CLBP) patients. The investigators performed an observational diagnostic development and accuracy study. The investigators MRS scanned 623 discs in 139 patients, with 275 discs also receiving provocative discography (PD). MRS data were used to quantify spectral features related to disc structure (collagen and proteoglycan) and acidity (lactate, alanine, propionate). Ratios of acidity to structure were used to calculate pain potential. MRS-SCOREs were compared to PD and Pfirrmann grade. Clinical utility was judged by evaluating surgical success for 75 of the subjects who underwent lumbar surgery. The investigators reported that 206 discs had both a successful MRS and independent pain diagnosis. When comparing to PD, MRS had a total accuracy of 85%, sensitivity of 82%, and specificity of 88%. These increased to 93%, 91%, and 93% respectively, in non-herniated discs. The MRS structure measures differed significantly between Pfirrmann grades, except grade I versus grade II. When all MRS positive discs were treated, surgical success was 97% versus 57% when the treated level was MRS negative, or 54% when the non-treated adjacent level was MRS positive. The investigators concluded that MRS correlates with PD and may support improved surgical outcomes for CLBP patients. Noninvasive MRS is a potentially valuable approach to clarifying pain mechanisms and designing CLBP therapies that are customized to the patient. Commenting on this study, Benoist (2019) stated: "There is no doubt that if these results are confrmed in future studies, and if this protocol becomes available in clinical practice at a reasonable cost, MRS-derived chemistry will be the first-line noninvasive imaging method."

Guidelines on bone tumors by ACR's expert panel on musculoskeletal imaging (Morrison et al, 2005) noted that MRS has potential to differentiate benign from malignant lesions, however, more research is needed.

In a review on MRS as an imaging tool for cancer, Shah et al (2006) stated that the clinical usefulness of MRS has yet to be fully substantiated. As MRS availability and access increases, appropriate evaluations of its strengths and weaknesses will be made. The authors concluded that research to date and primary observation indicated that MRS is a promising clinical tool for oncologic management of patients.

Magnetic resonance spectroscopy in the evaluation of suspected breast cancer is considered experimental and investigational because there is inadequate evidence in the peer-reviewed clinical literature regarding its effectiveness.

Bartella and Huang (2007) stated that proton (hydrogen 1) [1H]) MRS provides biochemical information about the tissue under investigation. Its diagnostic value in cancer is typically based on the detection of elevated levels of choline compounds, choline being a marker of active tumor. The 2 main potential clinical applications of 1H MRS are:
  1. as an adjunct to breast MRI to improve specificity in differentiating benign from malignant lesions, and
  2. for monitoring or even predicting response to treatment in patients undergoing neoadjuvant chemotherapy. 

Preliminary data are promising, with study results suggesting that 1H MRS may decrease the number of benign biopsies recommended on the basis of MRI findings and may help predict response as early as 24 hours after the first dose of neoadjuvant chemotherapy. Although several limitations currently exist that make the technique premature for clinical use, further evaluation with larger, preferably multi-center trials is certainly warranted.

Tse et al (2007) noted that in vivo proton (1)H-MRS has been demonstrated to be successful in the differentiation of benign and malignant breast lesions in a non-invasive manner by detecting increased levels of composite choline (Cho) compounds. Currently there is molecular evidence of increased Cho metabolism in breast cancer cells. In breast malignancies, (1)H-MRS achieved a high-overall sensitivity (82%). Most test cases were infiltrating duct carcinoma, but infiltrating lobular, medullary, mucinous and adenoid cystic carcinomas were also positive by (1)H-MRS. Large lesional size is a pre-requisite for (1)H-MRS testing, and technical problems account for some of the false negative results. Another potential of (1)H-MRS is to assess patients' response to neoadjuvant chemotherapy. In ductal carcinoma in situ, the results of (1)H-MRS on the limited number of cases were negative. Most of the assessed benign breast lesions including fibroadenoma, fibrocystic changes, cysts and galactoceles, papilloma, tubular adenoma and phyllodes tumors and were mostly negative by (1)H-MRS, with an overall false-positive rate was about 8%. Normal breast tissue was almost always negative by (1)H-MRS, whereas, lactating breast tissue showed positivity with a slightly different spectrum on further analysis. With the clinical use of stronger field MR scanners and better coils, the sensitivity of (1)H-MRS may be further improved. With these improvements, (1)H-MRS may potentially be useful in detection of smaller malignant lesions, characterization of malignant lesions into non-invasive or invasive, and as an invaluable tool in disease progression monitoring.

Kesler et al (2009) stated that males with fragile X syndrome (FRAX) are at risk for significant cognitive and behavioral deficits, particularly those involving executive prefrontal systems. Disruption of the cholinergic system secondary to fragile X mental retardation protein deficiency may contribute to the cognitive-behavioral impairments associated with fragile X. These investigators measured choline in the dorso-lateral prefrontal cortex of 9 males with FRAX and 9 age-matched typically developing controls using (1)H MRS. Right choline/creatine was significantly reduced in the fragile X group compared to controls. In controls, both left and right choline was significantly positively correlated with intelligence and age was significantly negatively correlated with left choline. There were no correlations in the fragile X group. Subjects with FRAX participating in a pilot open-label trial of donepezil demonstrated significantly improved cognitive-behavioral function. The authors concluded that studies utilizing biochemical neuroimaging techniques such as these have the potential to significantly impact the design of treatment strategies for FRAX and other genetic disorders by helping identify neurochemical targets for intervention as well as serving as metrics for treatment efficacy.

Umbehr et al (2009) meta-analyzed the diagnostic accuracy of combined MRI/MRS in prostate cancer and explored risk profiles with highest benefit. The authors searched the MEDLINE and EMBASE databases and the Cochrane Library, and screened reference lists and contacted experts. There were no language restrictions. They identified 31 test-accuracy studies (1,765 patients); 16 studies (17 populations) with a total of 581 patients were suitable for meta-analysis. Nine combined MRI/MRS studies (10 populations) examining men with pathologically confirmed prostate cancer (297 patients; 1,518 specimens) had a pooled sensitivity and specificity on prostate subpart level of 68% (95% confidence interval [CI]: 56 to 78%) and 85% (95% CI: 78 to 90%), respectively. Compared with patients at high-risk for clinically relevant cancer (6 studies), sensitivity was lower in low-risk patients (4 studies) (58% [46 to 69%] versus 74% [58 to 85%]; p > 0.05) but higher for specificity (91% [86 to 94%] versus 78% [70 to 84%]; p < 0.01). Seven studies examining patients with suspected prostate cancer at combined MRI/MRS (284 patients) had an overall pooled sensitivity and specificity on patients level of 82% (59 to 94%) and 88% (80 to 95%). In the low-risk group (5 studies), these values were 75% (39 to 93%) and 91% (77 to 97%), respectively. The authors concluded that a limited number of small studies suggested that MRI combined with MRS could be a rule-in test for low-risk patients. Moreover, they stated that these findings need further confirmation in larger studies and cost-effectiveness needs to be established.

In a prospective, multi-center study, Weinreb et al (2009) determined the incremental benefit of combined endorectal MRI and MRS, as compared with endorectal MRI alone, for sextant localization of peripheral zone (PZ) prostate cancer. A total of 134 patients with biopsy-proved prostate adenocarcinoma and scheduled to undergo radical prostatectomy were recruited at 7 institutions. T1-weighted, T2-weighted, and spectroscopic MR sequences were performed at 1.5 T by using a pelvic phased-array coil in combination with an endorectal coil. Eight readers independently rated the likelihood of the presence of PZ cancer in each sextant by using a 5-point scale -- first on MR images alone and later on combined MR-MRS images. Areas under the receiver operating characteristic curve (AUCs) were calculated with sextant as the unit of analysis. The presence or absence of cancer at centralized histopathologic evaluation of prostate specimens was the reference standard. Reader-specific receiver operating characteristic curves for values obtained with MRI alone and with combined MRI-MRS imaging were developed. The AUCs were estimated by using Mann-Whitney statistics and appropriate 95% CI. Complete data were available for 110 patients (mean age of 58 years; range of 45 to 72 years). Magnetic resonance imaging alone and combined MRI-MRS imaging had similar accuracy in PZ cancer localization (AUC, 0.60 versus 0.58, respectively; p > 0.05). AUCs for individual readers were 0.57 to 0.63 for MRI alone and 0.54 to 0.61 for combined MRI-MRS imaging. The authors concluded that in patients who undergo radical prostatectomy, the accuracy of combined 1.5-T endorectal MRI-MRS imaging for sextant localization of PZ prostate cancer is equal to that of MRI alone.

In a phase I study, Lee et al (2009) examined the use of SR4554, a fluorine-containing 2-nitroimidazole, as a hypoxia marker detectable with 19F MRS. These researchers investigated higher doses of SR4554 and intra-tumoral localization of the 19F MRS signal. Patients who had tumors greater than or equal to 3 cm in diameter and less than or equal to 4 cm deep were included in this study. Measurements were performed using 1H/19F surface coils and localized 19F MRS acquisition. SR4554 was administered at 1,400 mg m(-2), with subsequent increase to 2,600 mg m(-2) using prophylactic metoclopramide. Spectra were obtained immediately post-infusion (MRS no. 1), at 16 hrs (MRS no. 2) and 20 hrs (MRS no. 3), based on the SR4554 half-life of 3.5 hrs determined from a previous study. 19Fluorine retention index (%) was defined as (MRS no. 2/MRS no. 1)*100. A total of 26 patients enrolled at: 1,400 (n = 16), 1,800 (n = 1), 2,200 (n = 1) and 2,600 mg m(-2) (n = 8). SR4554 was well-tolerated and toxicities were all less than or equal to grade 1; mean plasma elimination half-life was 3.7 +/- 0.9 hrs. SR4554 signal was seen on both unlocalized and localized MRS no. 1 in all patients. Localized 19F signals were detected at MRS no. 2 in 5 out of 9 patients and 4 out of 5 patients at MRS no. 3. The mean retention index in tumor was 13.6 (range of 0.6 to 43.7) compared with 4.1 (range of 0.6 to 7.3) for plasma samples taken at the same times (p = 0.001) suggesting (19)F retention in tumor and, therefore, the presence of hypoxia. The authors concluded that they have demonstrated the feasibility of using 19F MRS with SR4554 as a potential method of detecting hypoxia. Certain patients showed evidence of 19F retention in tumor, supporting further development of this technique for detection of tumor hypoxia.

Sturrock et al (2010) evaluated in vivo brain metabolite differences in control subjects, individuals with pre-manifest Huntington disease (pre-HD), and individuals with early HD using ¹H MRS and assessed their relationship with motor performance. A total of 85 subjects (30 controls, 25 pre-HD, and 30 early HD) were recruited as part of the TRACK-HD study; 84 were scanned at 3 T with single-voxel spectroscopy in the left putamen. Disease burden score was greater than 220 among pre-HD individuals. Subjects underwent TRACK-HD motor assessment including Unified Huntington's Disease Rating Scale (UHDRS) motor scoring and a novel quantitative motor battery. Statistical analyses included linear regression and 1-way analysis of variance. Total N-acetylaspartate (tNAA), a neuronal integrity marker, was lower in early HD (about 15%) versus controls (p < 0.001). N-acetylaspartate (NAA), a constituent of tNAA, was lower in pre-HD (about 8%) and early HD (about 17%) versus controls (p < 0.05). The glial cell marker, myo-inositol (mI), was 50% higher in early HD versus pre-HD (p < 0.01). In early HD, mI correlated with UHDRS motor score (R² = 0.23, p < 0.05). Across pre-HD and early HD, tNAA correlated with performance on a tongue pressure task (R² = 0.30, p < 0.0001) and with disease burden score (R² = 0.17, p < 0.005). This study demonstrated lower putaminal tNAA in early HD compared to controls in a cross-section of subjects. A novel biomarker role for mI in early HD was also identified. These findings resolve disagreement in the literature about the role of MRS as an HD biomarker. The authors concluded that putaminal MRS measurements of NAA and mI are promising potential biomarkers of HD onset and progression. Moreover, they stated that the longitudinal assessment of their cohort, and replication of this study in a second large pre-manifest and early HD cohort, ideally in the setting of a therapeutic trial, will be necessary to fully validate these findings.

Beadle and Frenneaux (2010) noted that 31-phosphorous ((31)P) MRS is a technique that allows the non-invasive characterization of the biochemical and metabolic state of the myocardium in vivo. Magnetic resonance spectroscopy is a pure form of molecular imaging using magnetic resonance signals from nuclei with nuclear spin to assess cardiac metabolism without the need for external radioactive tracers. (31)P MRS provides information on the underlying metabolic abnormalities that are fundamental to common conditions including ischemic heart disease, cardiomyopathy, hypertrophy and valvular disease. (31)P MRS could potentially also have a role to play in assessing response to therapy as well as the effectiveness of metabolic modulating agents. However, the use of MRS is currently limited to research due to its poor reproducibility, low spatial and temporal resolution, and long acquisition times. With technical advances in both the spectrometers and post-processing, MRS is likely to play a role in the future of multi-modal non-invasive cardiac assessment.

Horska and Barker (2010) noted that the utility of MRS in diagnosis and evaluation of treatment response to human brain tumors has been widely documented. These researchers discussed the role of MRS in tumor classification, tumors versus non-neoplastic lesions, prediction of survival, treatment planning, monitoring of therapy, and post-therapy evaluation. They concluded that there is a need for standardization and further study in order for MRS to become widely used as a routine clinical tool.

The clinical evidence is not sufficient to permit conclusions on the health outcome effects of magnetic resonance spectroscopy in the evaluation of leukoencephalopathy.  In a 2008 article, Bizzi et al reported that childhood white matter disorders often show similar MR imaging signal-intensity changes, despite different underlying pathophysiologies. The purpose of this study was to determine if proton MR spectroscopic imaging ((1)H-MRSI) may help identify tissue pathophysiology in patients with leukoencephalopathies. Seventy patients (mean age of 6; range, of 0.66 to 17 years) were prospectively examined by (1)H-MRSI; a diagnosis of leukoencephalopathy due to known genetic defects leading to lack of formation, breakdown of myelin, or loss of white matter tissue attenuation (rarefaction) was made in 47 patients. The diagnosis remained undefined (UL) in 23 patients. Patients with definite diagnoses were assigned (on the basis of known pathophysiology) to 3 groups corresponding to hypomyelination, white matter rarefaction, and demyelination. Choline (Cho), creatine (Cr), and N-acetylaspartate (NAA) signals from 6 white matter regions and their intra- and intervoxel (relative to gray matter) ratios were measured. Analysis of variance was performed by diagnosis and by pathophysiology group. Stepwise linear discriminant analysis was performed to construct a model to predict pathophysiology on the basis of (1)H-MRSI, and was applied to the UL group. Analysis of variance by diagnosis showed 3 main metabolic patterns. Analysis of variance by pathophysiology showed significant differences for Cho/NAA (p < 0.001), Cho/Cr (p < 0.004), and NAA/Cr (p < 0.002). Accuracy of the linear discriminant analysis model was 75%, with Cho/Cr and NAA/Cr being the best parameters for classification. On the basis of the linear discriminant analysis model, 61% of the subjects in the UL group were classified as hypomyelinating.

Baltzer and Dietzel (2013) performed a systematic review and meta-analysis to estimate the diagnostic performance of breast proton MRS in differentiating benign from malignant lesions and to identify variables that influence the accuracy of MRS. A comprehensive search of the PubMed database was performed on articles listed until January 6, 2012.  The Medical Subject Headings and text words for the terms "breast," "spectroscopy," and "magnetic resonance" were used. Investigations including more than 10 patients at 1.5 T or 3.0 T applying 1D single-voxel MRS or spatially resolved MRS for differentiation between benign and malignant breast lesions were eligible.  A reference standard had to be established either by means of histopathologic examination or imaging follow-up of 12 or more months.  Statistical analysis included pooling of diagnostic accuracy, control for data inhomogeneity, and identification of publication bias. A total of 19 studies were used for general data pooling.  The studies included a total of 1,183 patients and 1,198 lesions (773 malignant, 452 benign).  Pooled sensitivity and specificity were 73% (556 of 761; 95% CI: 64% to 82%) and 88% (386 of 439; 95% CI: 85% to 91%), respectively.  The pooled diagnostic odds ratio (DOR) was 34.30 (95% CI: 16.71 to 70.43).  For breast cancers versus benign lesions, the area under the symmetric summary receiver operating characteristic curve of MRS was 0.88; and the Q* index was 0.81.  There was evidence of between-studies heterogeneity regarding sensitivity and DOR (p < 0.0001).  No significant influences of higher field strength, post-contrast acquisition, or qualitative versus quantitative MRS measurements were identified. Egger testing confirmed significant publication bias in studies including small numbers of patients (p < 0.0001). The authors concluded that breast MRS showed variable sensitivity and high specificity in the diagnosis of breast lesions, independent from the technical MRS approach.  Moreover, they stated that because of significant publication bias, pooled diagnostic measures might be over-estimated.

Furthermore, an UpToDate review on “MRI of the breast and emerging technologies” (Slanetz, 2013) states that “MR spectroscopy may provide an adjunct to conventional breast MRI, with the potential to increase specificity and avoid benign biopsies in a substantial number of women.  MR spectroscopy is also promising for the evaluation of non-mass like suspicious findings on breast MRI.  However, MR spectroscopy misses some breast cancers, because not all express choline.  In a study of 16 invasive ductal tumors; 88 percent had detectable choline peaks.  MR spectroscopy remains investigational, but it may have a future role in predicting outcome and monitoring response of therapy”.

Mowatt et al (2013) evaluated the diagnostic accuracy of MRS and enhanced MRI techniques [dynamic contrast-enhanced MRI (DCE-MRI), diffusion-weighted MRI (DW-MRI)] and the clinical effectiveness and cost-effectiveness of strategies involving their use in aiding the localization of prostate abnormalities for biopsy in patients with prior negative biopsy who remain clinically suspicious for harboring malignancy. The following databases were searched -- MEDLINE (1946 to March 2012), MEDLINE In-Process & Other Non-Indexed Citations (March 2012), EMBASE (1980 to March 2012), Bioscience Information Service (BIOSIS; 1995 to March 2012), Science Citation Index (SCI; 1995 to March 2012), the Cochrane Library (Issue 3 2012), Database of Abstracts of Reviews of Effects (DARE; March 2012), Medion (March 2012) and Health Technology Assessment database (March 2012). Direct studies/randomized controlled trials reporting diagnostic outcomes.  Index tests included MRS, DCE-MRI and DW-MRI.  Comparators were T2-weighted MRI (T2-MRI), transrectal ultrasound-guided biopsy (TRUS/Bx).  Reference standard was histopathological assessment of biopsied tissue.  A Markov model was developed to assess the cost-effectiveness of alternative MRS/MRI sequences to direct TRUS-guided biopsies compared with systematic extended-cores TRUS-guided biopsies.  A health service provider perspective was adopted and the recommended 3.5% discount rate was applied to costs and outcomes. A total of 51 studies were included.  In pooled estimates, sensitivity [95% CI] was highest for MRS (92%; 95% CI: 86% to 95%). Specificity was highest for TRUS (imaging test) (81%; 95% CI: 77% to 85%).  Life-time costs ranged from £3,895 using systematic TRUS-guided biopsies to £4,056 using findings on T2-MRI or DCE-MRI to direct biopsies (60-year old cohort, cancer prevalence 24%).  The base-case incremental cost-effectiveness ratio for T2-MRI was less than £30,000 per QALY (all cohorts). Probabilistic sensitivity analysis showed high uncertainty surrounding the incremental cost-effectiveness of T2-MRI in moderate prevalence cohorts.  The cost-effectiveness of MRS compared with T2-MRI and TRUS was sensitive to several key parameters. The authors concluded that MRS had higher sensitivity and specificity than T2-MRI.  Relative cost-effectiveness of alternative strategies was sensitive to key parameters/assumptions.  Under certain circumstances T2-MRI may be cost-effective compared with systematic TRUS.  If MRS and DW-MRI can be shown to have high sensitivity for detecting moderate/high-risk cancer, while negating patients with no cancer/low-risk disease to undergo biopsy, their use could represent a cost-effective approach to diagnosis.  However, owing to the relative paucity of reliable data, further studies are required.  In particular, prospective studies are needed in men with suspected PC and elevated PSA levels but previously negative biopsy comparing the utility of the individual and combined components of a multi-parametric magnetic resonance (MR) approach (MRS, DCE-MRI and DW-MRI) with both a MR-guided/-directed biopsy session and an extended 14-core TRUS-guided biopsy scheme against a reference standard of histopathological assessment of biopsied tissue obtained via saturation biopsy, template biopsy or prostatectomy specimens. Non-English-language studies were excluded.  Few studies reported DCE-MRI/DW-MRI.  The modelling was hampered by limited data on the relative diagnostic accuracy of alternative strategies, the natural history of cancer detected at repeat biopsy, and the impact of diagnosis and treatment on disease progression and health-related quality of life.

An UpToDate review on “Diagnosis and differential diagnosis of dermatomyositis and polymyositis in adults” (Miller, 2013) did not mention the use of MRS as a management tool.

Gardner et al (2014) stated that traditional structural neuroimaging techniques are normal in athletes who sustain sport-related concussions and are only considered to be clinically helpful in ruling out a more serious brain injury.  There is a clinical need for more sophisticated, non-invasive imaging techniques capable of detecting changes in neurophysiology after injury.  Concussion is associated with neuro-metabolic changes including neuronal depolarization, release of excitatory neurotransmitters, ionic shifts, changes in glucose metabolism, altered cerebral blood flow, and impaired axonal function.  Proton magnetic resonance spectroscopy ((1)H-MRS, or simply MRS) is capable of measuring brain biochemistry and has the potential to identify and quantify physiologic changes after concussion.  These investigators provided an overview of research findings using MRS in sport-related concussion.  A systematic review of articles published in the English language, up to February 2013, was conducted.  Articles were retrieved via the databases: PsychINFO, Medline, Embase, SportDiscus, Scopus, Web of Science, and Informit using key terms: magnetic resonance spectroscopy, nuclear magnetic resonance spectroscopy, neurospectroscopy, spectroscopy, two-dimensional nuclear magnetic resonance spectroscopy, correlation spectroscopy, J-spectroscopy, exchange spectroscopy, nuclear overhauser effect spectroscopy, NMR, MRS, COSY, EXSY, NOESY, 2D NMR, craniocerebral trauma, mild traumatic brain injury (mTBI), TBI, brain concussion, concussion, brain damage, sport, athletic, and athlete. Observational, cohort, correlational, cross-sectional, and longitudinal studies were all included in the current review.  The review identified 11 publications that met criteria for inclusion, comprised of data on 200 athletes and 116 controls; 9 of 11 studies reported a MRS abnormality consistent with an alteration in neurochemistry.  The authors concluded that these findings support the use of MRS as a research tool for identifying altered neurophysiology and monitoring recovery in adult athletes, even beyond the resolution of post-concussive symptoms and other investigation techniques returning to normative levels.  Moreover, they stated that larger cross-sectional, prospective, and longitudinal studies are needed to understand the sensitivity and prognostic value of MRS within the field of sport-related concussion.

Furthermore, the American Medical Society for Sports Medicine’s position statement on “Concussion in sport” (Harmon et al, 2013) did not mention the use of MRS as a management tool.

Ustymowicz et al (2004) reported results of a MRS study in 12 patients with neuroborreliosis.  These researchers used a PRESS sequence, placing an 8 cm3 voxel in normal-appearing white matter of the frontal lobe.  Peaks indicating N-acetylaspartate (NAA), choline (Cho), creatine (Cr), myo-inositol (mI), lipids (Lip) and lactate (Lac) were identified and ratios of NAA/Cr, Cho/Cr, mI/Cr, Lip/Cr, Lac/Cr calculated.  Significant increases in Cho/Cr and Lip/Cr were noted.  No abnormality was found in mean NAA/Cr and Lac/Cr, but in 4 patients there was a decreased NAA peak; mI/Cr ratio was slightly increased.  The authors concluded that although the spectroscopic profile in patients with neuroborreliosis seems to be non-specific, MRS might be useful for assessing tissue damage of the central nervous system.

Current Lyme disease guidelines have no recommendations for use of magnetic resonance spectroscopy (Wormser, et al., 2007; Mygland, et al., 2010). UpToDate reviews on “Nervous system Lyme disease” (Halperin, 2015) and “Clinical manifestations of Lyme disease in adults” (Hu, 2015) do not mention magnetic resonance spectroscopy as a management tool.

Wang et al (2014) determined the suitability of MRS for screening brain tumors, based on a systematic review and meta-analysis of published data on the diagnostic performance of MRS. The PubMed and PHMC databases were systematically searched for relevant studies up to December 2013. The sensitivities and specificities of MRS in individual studies were calculated and the pooled diagnostic accuracies, with 95% CI, were assessed under a fixed-effects model. A total of 24 studies were included, comprising a total of 1,013 participants. Overall, no heterogeneity of diagnostic effects was observed between studies. The pooled sensitivity and specificity of MRS were 80.05% (95% CI:  75.97% to 83.59%) and 78.46% (95% CI: 73.40% to 82.78%), respectively. The area under the summary receiver operating characteristic curve was 0.78. Stratified meta-analysis showed higher sensitivity and specificity in child than adult; CSI had higher sensitivity and SV had higher specificity. Higher sensitivity and specificity were obtained in short TE value. The authors concluded that although the qualities of the studies included in the meta-analysis were moderate, current evidence suggests that MRS may be a valuable adjunct to MRI for diagnosing brain tumors; but requires selection of suitable technique and TE value.

The American College of Radiology’s Appropriateness Criteria® on “Dementia and movement disorders” (Wippold et al, 2014) stated that “Advanced imaging techniques such as fMRI and MRS hold exciting investigative potential for better understanding of neurodegenerative disorders, but they are not considered routine clinical practice at this time”.

The American College of Radiology’s Appropriateness Criteria® on “Head trauma” (Ryan et al, 2014) stated that “There has been increasing interest in using higher order imaging techniques, such as positron emission tomography (PET), single-photon emission computed tomography (SPECT) perfusion, functional MRI (fMRI), diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (MRS), to assess the functional and microstructural consequences of head trauma …. Advanced imaging techniques may visualize injury occult by standard imaging but remain relatively untested in the pediatric population with few data to support routine clinical use at this time”.

Spencer et al (2014) noted that the major excitatory neurotransmitter in the brain, glutamate plays a critical role in normal brain function; thus, its dysregulation could lead to psychopathology in youth. A growing body of literature has investigated the role of glutamate in the pathophysiology of childhood psychiatric disorders through MRS. These researchers reviewed the existing literature to gauge the specificity of such findings. PubMed was searched for all scientific, peer-reviewed articles published in English that included MRS measurements of glutamatergic metabolites in pediatric psychiatric populations through August 14, 2013. A total of 50 articles were included in this review. These studies included measurements of glutamate or related metabolites with MRS in children with psychiatric disorders. All relevant data (e.g., population; number, sex, and age of subjects; method of comparison; treatment history; MRS Tesla; brain regions of interest; glutamatergic findings; other findings; and co-morbidities) were extracted from the included articles. The direction and significance of glutamate dysregulation and brain region(s) examined were used to compare the studies. Most consistently, increases in glutamatergic metabolites were found in the anterior cingulate cortex (ACC) and other regions in youth with attention-deficit/hyperactivity disorder (ADHD). Limited data suggested increases in glutamatergic metabolites in youth with autism spectrum disorders, emotional dysregulation, and high risk for schizophrenia and decreases in youth with major depression, bipolar disorder, and obsessive-compulsive disorder. There was limited but consistent evidence for normalization of glutamatergic levels with treatment, particularly in bipolar disorder and ADHD. The authors concluded that a relatively small number of studies have examined the role of glutamatergic dysregulation in pediatric psychiatric disorders. Some consistencies can be found, but interpretation of the data is limited by differences in methodology, including age of subjects, severity of current symptoms, treatment, and scanning parameters.

Wang et al (2015) examined the patterns of cerebral metabolite changes in several cerebral regions that are strongly associated with cognitive decline in Alzheimer's disease  patients. Using Hedges' g effect size, a systematic search was performed in PubMed, Cochrane Library, Ovid, Embase, and EBSCO, and 38 studies were integrated into the final meta-analysis. According to the observational studies, N-acetyl aspartate (NAA) in Alzheimer's disease patients was significantly reduced in the posterior cingulate (PC) (effect size (ES) = -0.924, p <  0.005) and bilateral hippocampus (left hippocampus: ES = -1.329, p <  0.005; right hippocampus: ES = -1.287, p <  0.005).  NAA/Cr (creatine) ratio decreased markedly in the PC (ES = -1.052, p <  0.005). Simultaneously, significant elevated myo-inositol (mI)/Cr ratio was found not only in the PC but also in the parietal gray matter.  For lack of sufficient data, these researchers failed to elucidate the effectiveness of pharmacological interventions with the metabolites changes. The authors concluded that available data indicated that NAA, mI, and the NAA/Cr ratio might be potential biomarkers of brain dysfunction in Alzheimer's disease subjects.  Choline (Cho)/Cr and mI/NAA changes might also contribute toward the diagnostic process.  They stated that large, well-designed studies correlated with cerebral metabolism are needed to better estimate the cerebral extent of alterations in brain metabolite levels in Alzheimer's disease patients.

In a longitudinal, multiple time-point study (a subset of the Swedish BioFINDER), Voevodskaya and colleagues (2019) examined the association between longitudinal changes in proton MRS metabolites and amyloid pathology in individuals without dementia, and to explore the relationship between MRS and cognitive decline. These researchers included cognitively healthy subjects, individuals with subjective cognitive decline, and individuals with mild cognitive impairment. MRS was acquired serially in 294 subjects (670 individual spectra) from the posterior cingulate/precuneus. Using mixed-effects models, these investigators evaluated the association between MRS and baseline β-amyloid (Aβ), and between MRS and the longitudinal Mini-Mental State Examination (MMSE), accounting for APOE, age, and sex. While baseline MRS metabolites were similar in Aβ positive (Aβ+) and negative (Aβ-) individuals, in the Aβ+ group, the estimated rate of change was +1.9%/y for myo-inositol (mI)/creatine (Cr) and -2.0%/y for N-acetylaspartate (NAA)/mI. In the Aβ- group, mI/Cr and NAA/mI yearly change was -0.05% and +1.2%; however, this was not significant across time-points. The mild cognitive impairment Aβ+ group showed the steepest MRS changes, with an estimated rate of +2.93%/y (p = 0.07) for mI/Cr and -3.55%/y (p < 0.01) for NAA/mI. Furthermore, in the entire cohort, these researchers found that Aβ+ individuals with low baseline NAA/mI had a significantly higher rate of cognitive decline than Aβ+ individuals with high baseline NAA/mI. The authors concluded that the longitudinal change in mI/Cr and NAA/mI was associated with underlying amyloid pathology. These researchers stated that MRS may be a useful non-invasive marker of Aβ-related processes over time. In addition, they demonstrated that in Aβ+ individuals, baseline NAA/mI may predict the rate of future cognitive decline.

The authors stated that the design of their study was such that a cut-off value has been used to stratify subjects into Aβ− and Aβ+ based on baseline CSF Aβ42 levels. Furthermore, one of their results suggested that there may exist some cut-off value for NAA/mI that was relevant for predicting a worsening of cognitive symptoms. There are certain disadvantages to working with dichotomized biomarkers, such as the possible masking of sub-threshold effects and the assessment of individuals close to the cut-point. Nevertheless, applying a normal/abnormal biomarker classification is an approach that, apart from being practical, is essential for determining eligibility for clinical trials. However, these researchers recognized that a putative cut-off value for NAA/mI, which may have relevance for determining an individual's cognitive decline profile, must be scrutinized by future studies and validated in even larger longitudinal cohorts. The inclusion criteria of the BioFINDER cohort and the final constellation of this study sample may limit the generalizability of the results of this study. The potential sources of selection bias in the recruitment of the subjects to the BioFINDER may stem from the relatively high cognitive scores at entry and the requirement to undergo a lumbar puncture and an MRI. However, although study subjects might be healthier than the general population, it was unclear in which direction this would affect the associations found in this study. These researchers stated that the findings ofthis study showed that the longitudinal changes in mI/Cr and NAA/mI were largely governed by the presence of underlying amyloid pathology, warranting their potential usefulness as non-invasive dynamic disease biomarkers during the pre-dementia stages of AD. Today, amyloid and tau deposition can be imaged using PET, allowing clinicians to evaluate molecular pathology in-vivo. However, the need remains for a more widely available cost-effective technique that can be used for screening dementia and monitoring disease progression and treatment effects in a clinical setting. They stated that large-scale multi-modal studies that include MRS will help further locate spectroscopic changes in the continuum of AD pathophysiologic processes.

In an editorial that accompanied the afore-mentioned study, Kantarci and Jicha (2019) stated that “One limitation of single-voxel 1H MRS is that it is only possible to study a single volume of interest during an acquisition. The authors appropriately chose to study the posterior cingulate gyri bilaterally in a single voxel. Posterior cingulate gyrus is a paralimbic cortical region that connects to the limbic network through the cingulum bundle and also connects the limbic network to other regions of the brain. Because of its functional and structural connections, it is considered the “hub” for the default mode network. The posterior cingulate cortex is vulnerable to both β-amyloid and neurofibrillary tangle tau pathologies early in the AD continuum and has been recommended previously as an optimal region for the conduct of single-voxel 1H MRS studies of AD pathophysiology. While several prior studies have provided evidence that 1H MRS metabolites may provide important information on early β-amyloid and tau pathophysiology within a single acquisition that can be added to a clinical MRI, as a low-cost, non-invasive biomarker of AD, implementation of such strategies remain in their infancy. The findings of the present study by Voevodskaya et al demonstrating a longitudinal increase in mI/Cr ratio associated with β-amyloid pathology, and a longitudinal decline in NAA/mI that tracks with disease progression, highlights the possibility of utilizing 1H MRS metabolites as biological outcome measures of disease progression in clinical trials targeting early predementia AD pathophysiology. Additional studies of 1H MRS from other centers using disparate cohorts, enriched in minority and other underrepresented groups, to explore the generalizability of the present findings, should be a priority for the field. In addition, efforts at standardizing and optimizing 1H MRS methods that will allow for multi-center studies should be a priority for the development of such techniques that will allow future applications in both selecting appropriate trial participants as well as tracking disease progression in early predementia AD clinical trials”.

Monitoring Hepatocellular Carcinoma and Liver Cirrhosis Development

In a randomized trial, Wang and Li (2015) examined the utility of H-MRS to quantify the differences in liver metabolites.  Magnetic resonance spectroscopy was used as a means of predicting the probability of developing hepatocellular carcinoma (HCC) in patients with liver cirrhosis secondary to chronic hepatitis B. This study included 20 healthy volunteers, 20 patients with liver cirrhosis secondary to chronic hepatitis B (cirrhosis group), and 20 patients with small HCC secondary to cirrhosis liver parenchyma (HCC group). All patients underwent routine MRI and H-MRS scanning.  LCModel software was used to quantify Cho (Choline), Lip (lipid), and Cho/Lip in the 3 groups, and a 1-way ANOVA was used to compare the differences in these metabolites between groups. Choline levels were significantly different between the control and HCC group and between the cirrhosis group and the HCC group (all p < 0.001).  There was also a significant difference in Lip levels between the control and cirrhosis group and the control and HCC groups (all p < 0.001).  There were also differences in Cho/Lip between the control and cirrhosis groups, the control and HCC groups, and the cirrhosis and HCC groups (all p < 0.001). The authors concluded that H-MRS followed by the analysis with LCModel can be used to measure changes in hepatic metabolite levels in patients with liver cirrhosis secondary to chronic hepatitis B and HCC. They stated that H-MRS may be helpful in monitoring HCC and liver cirrhosis development. These preliminary findings need to be validated by well-designed studies.

Substance Use Disorders

Hellem et al (2015) presented a systematic review of MRS studies of substance use disorders.  As a non-invasive and non-ionizing imaging technique, MRS is being widely used in substance abuse research to evaluate the effects substances of abuse have on brain chemistry.  Nearly 40 peer-reviewed research articles that focused on the utility of MRS in alcohol, methamphetamine, 3,4-methylenedioxymethamphetamine, cocaine, opiates, opioids, marijuana, and nicotine use disorders were reviewed.  Findings indicated inconsistencies with respect to alterations in brain chemistry within each substance of abuse, and the most consistent finding across substances was decreased N-acetylaspartate and choline levels with chronic alcohol, methamphetamine, and nicotine use.  The authors concluded that variation in the brain regions studied, imaging technique, as well as small sample sizes might explain the discrepancies in findings within each substance.  They stated that future well-designed MRS studies offer promise in examining novel treatment approaches in substance use disorders.

Finnell (2015) provided clinical translation of the afore-mentioned systematic review by Hellem et al (2015).  These investigators provided an overview of the MRS technique and neuro-metabolites that are commonly studied with MRS in the human brain.  The methods and results are presented for the systemic review of MRS studies among adults and focus on alcohol, methamphetamine, MDMA, cocaine, opiates/opioids, marijuana, and nicotine. A total of 36 studies were included in the review of literature.  Substance-specific studies indicated inconsistencies with respect to alterations in brain chemistry.  A consistent finding across substances (alcohol, methamphetamine, and nicotine) was the decrease of 2metabolites (N-acetylaspartate and choline). The authors concluded that MRS offers the possibility of identifying brain biomarkers for disease and evaluating treatment response; studies employing standardized protocols for data acquisition and reporting are needed.

Low Back Pain

Zhao and colleagues (2016)  stated that low back pain (LBP) is a highly prevalent health problem around the world, affecting 50% to 85% of people at some point in life.  These investigators summarized the previous proton MRS studies on brain chemical changes in patients with chronic LBP (CLBP). They identified relevant studies from a literature search of PubMed and Embase from 1980 to March 2016.  Data extraction was performed on the subjects' characteristics, MRS methods, spectral analyses, cerebral metabolites and perceptual measurements. The review identified 9 studies that met the inclusion criteria, comprised of data on 135 CLBP subjects and 137 healthy controls; 7 of these studies reported statistically different neurochemical alterations in patients with CLBP.  The results showed that compared to controls, CLBP patients showed reductions of:
  1. n-acetyl-aspartate (NAA) in the dorsolateral prefrontal cortex (DLPFC), right primary motor cortex, left somatosensory cortex (SSC), left anterior insula and anterior cingulate cortex (ACC),
  2. glutamate in the ACC,
  3. myo-inositol in the ACC and thalamus,
  4. choline in the right SSC, and
  5. glucose in the DLPFC.

The authors concluded that the findings of this review provided evidence for alterations in the biochemical profile of the brain in patients with CLBP, which suggests that biochemical changes may play a significant role in the development and pathophysiology of CLBP and shed light on the development of new treatments for CLBP. They stated that future studies need to emphasize therapeutic response and the relationships between brain metabolites and functions.


This study had several drawbacks:
  1. there are relatively few subjects in each cohort, and confounding factors, such as anxiety and depression, made it difficult to identify specific biochemical markers of CLBP,
  2. in 8 studies, almost 50% of the patients had received prior treatment for CLBP.  Although some of the patients refrained from medications for at least 24 hours before the study, it was unclear if  this eliminated the influence caused by long-term medication use, and
  3. although these MRS studies have detected neurochemical alterations in these brain regions, the underlying causes of these metabolic changes are not fully understood.

Therefore, further investigation is needed to explore the pathophysiological relationship between the neurochemical alterations and CLBP.

Juvenile Myoclonic Epilepsy

Zhang and co-workers (2016) performed a meta-analysis of the MRS findings regarding juvenile myoclonic epilepsy (JME). These investigators searched for studies in the PubMed, Web of Science, and Embase electronic databases; 2 authors collected articles and extracted data independently.  A meta-analysis was performed for diverse metabolites in different brain areas.  The mean difference (MD) and 95% CI were used to compare continuous variables. A decreased NAA/Cr was observed in the motor cortex (MD = 0.14, 95% CI: 0.09 to 0.20), and the NAA was reduced in the thalamus (MD = 0.74, 95% CI: 0.37 to 1.10) and the frontal lobe (MD = 0.87, 95% CI: 0.45 to 1.28); the GLX/Cr was increased in the insula (MD = -0.10, 95% CI: -0.14 to -0.06) and the striatum (MD = -0.11, 95% CI: -0.17 to -0.05). The authors concluded that JME may be a multi-regional, thalamo-frontal network epilepsy rather than an idiopathic generalized epilepsy syndrome. 

Cevik and colleagues (2016) investigated the hypothesis of biochemical changes in frontal cortex and thalamo-cortical pathways in JME and the interaction between the biochemical changes and cortical functions; MRS was applied to 20 JME patients and 20 controls for measuring NAA, N-NAA to creatine ratio (NAA/Cr), glutamine and glutamate (GLX), glutamine-glutamate to Cr (GLX/Cr), choline (Cho) containing compounds and Cho/Cr levels.  Neuropsychological cognitive tests for linguistic and visual attention, linguistic and visual memory, visuospatial and executive functions were applied to all participants; NAA and NAA/Cr concentrations were found lower in bilateral frontal and thalamic regions in JME group as compared with the control group (p < 0.05). There was no difference in frontal and thalamic GLX, GLX/Cr, Cho, Cho/Cr levels in between JME patients and controls (p > 0.05).  Patients with JME were found more unsuccessful than the controls in attention, memory, visuospatial function, verbal fluency, Trail B test and executive functions, Stroop test, clock drawing test and Trail A test (p < 0.05).  Prefrontal NAA/Cr level was positively related to visual attention, memory, Stroop test and thalamic NAA/Cr level was positively related to linguistic memory and Wisconsin card sorting test in JME patients.  The authors concluded that this research highlighted regional brain changes and cognitive decline in JME patients and suggested that MRS may be a sensitive technique for showing subclinical cognitive changes. These preliminary findings need to be validated by well-designed studies.

Radiation Encephalopathy

In a meta-analysis, Chen and associates (2016) noted that articles in English and Chinese were selected from available electronic databases prior to September 2014.  The metabolic concentrations and patterns of NAA, Cho, Cr, NAA/Cr, NAA/Cho, and Cho/Cr ratios in radiotherapy-induced radiation encephalopathy by proton MRS were extracted.  A meta-analysis was performed to quantitatively synthesize findings of these studies.  Weighted mean difference (WMD) and 95% CIs were calculated using random or fixed effective models.  Heterogeneity between studies was assessed using the Cochrane Q test and I (2) statistics.  The results indicated that a total of 4 researches involving 214 patients met inclusion criteria.  Depending on methodologies of selected studies, control groups were referred to as healthy subjects.  The combined analysis revealed that there was no significant difference in value of Cr between radiotherapy group and healthy control group (WMD = -1.483, 95% CI: -67.185 to 64.219, p = 0.965).  However, there were significant difference in values of NAA (WMD = -18.227, 95% CI: -36.317 to -0.137, p = 0.048), Cho (WMD = 38.003, 95% CI: 5.155 to 70.851, p = 0.023), NAA/Cr (WMD = -1.175, 95% CI: -1.563 to -0.787, p = 0.000), NAA/Cho (WMD = -1.108, 95% CI: -2.003 to 0.213, p = 0.015), and Cho/Cr (WMD = -0.773, 95% CI: 0.239 to 1.307, p = 0.005).  The authors concluded that MRS can be regarded as an effective and feasible imaging test for radiotherapy-induced radiation encephalopathy in patients with nasopharyngeal carcinoma. They stated that more future large-scaled studies are needed to confirm these results.

This meta-analysis had several drawbacks:

  1. there was no available detailed individual data and a more precise subgroup analysis should be performed on other variables such as age, sex, and stage of the disease,
  2. the sample sizes of the 4 included studies were rather small and not adequate enough to confirmedly assess the utilities of MRS in the detection of radiation-induced brain injury at an early stage,
  3. these authors included only published studies in this study; the unpublished data or clinical trials have not been included in this analysis,
  4. due to the number limitation of the included studies, there was existence of publication bias in some comparisons, which could potentially influence the results of this meta-analysis, and
  5. there was high heterogeneity in this study.

Detection and Quantification of Hepatic Steatosis in Living Liver Donors

In a meta-analysis, Zheng and colleagues (2017) determined the accuracy of MR imaging for detection and quantification of hepatic steatosis (HS) in living liver donor candidates.  These researchers carried out a systematic search of the literature to find studies on the diagnostic and quantitative accuracy of MR imaging for assessment of HS in liver donors.  The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used, and patient selection, index text, reference standard, and study flow and timing were assessed to evaluate the quality of each included study.  Pooled sensitivity, specificity, positive and negative likelihood ratios, hierarchical summary ROC curves, and the AUC were estimated by using hierarchical summary ROC and bivariate random-effects models.  A total of 8 studies involving 934 subjects were eligible for the meta-analysis.  For detection of HS with MRI and/or MRS in living liver donors, the pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio, respectively, were 0.89 (95% C]: 0.75 to 0.95), 0.84 (95% CI: 0.76 to 0.89), 5.53 (95% CI: 3.71 to 8.25), and 0.14 (95% CI: 0.06 to 0.31).  The AUC was 0.92 (95% CI: 0.89 to 0.94).  For detection of substantial HS (greater than 10% to greater than 30% HS at liver pathologic examination, as defined in each study), these corresponding diagnostic estimates were 0.91 (95% CI: 0.82 to 0.95), 0.89 (95% CI: 0.84 to 0.93), 8.30 (95% CI: 5.47 to 12.59), 0.10 (95% CI: 0.05 to 0.21), and 0.96 (95% CI: 0.93 to  0.97), respectively.  Moderate heterogeneity was detected.  No publication bias was detected (p =0 .12).  The authors concluded that MRI and MRS showed high sensitivity and specificity for detection of HS, especially when HS is substantial, and may be useful for non-invasive evaluation of HS in living liver donors. Moreover, they stated that further high-quality studies are needed to determine whether MRI and/or MRS can obviate the clinical demand for liver biopsy.

This study had several drawbacks:
  1. moderate inter-study heterogeneity, which might be the result of both the diagnostic threshold variability and differences in study methodology, was observed in this meta-analysis.  Prospective studies have lower sensitivity and specificity than do retrospective ones, which indicated that the diagnostic performance of MRI and MRS may have been over-estimated in retrospective studies because of selection and recall biases,
  2. as expected, abdominal radiologists interpreted MRI and MRS with higher sensitivity and specificity.  Other potential sources of heterogeneity included mean age, sex ratio, and sample size.  Unfortunately, these researchers were unable to conduct a meta-regression with these parameters because of limited data, and
  3. for the secondary analysis, these investigators combined different thresholds of substantial HS together because acceptable HS limits ranged from 10% to 30% in most transplantation centers.

Although the authors observed no significant statistical heterogeneity for this, clinical heterogeneity may exist.

Differentiation of Primary Central Nervous System Lymphoma (PCNSL) from Other Focal Brain Lesions

In a systematic review and meta-analysis, Yang and colleagues (2017) examined the roles of SPECT, PET, and MRS in distinguishing primary central nervous system lymphoma (PCNSL) from other focal brain lesions (FBLs) in human immunodeficiency virus (HIV)-infected patients. PubMed, Scopus, and Medline were systematically searched for eligible studies from 1980 to 2016; 2 authors extracted characteristics of patients and their lesions using predefined criteria. A total of 18 studies on SPECT containing 667 patients, 6 studies on PET containing 108 patients, and 3 studies on MRS containing 96 patients were included.  SPECT had a pooled sensitivity of 0.92 (95% CI: 0.85 to 0.96) and specificity of 0.84 (95% CI: 0.74 to 0.90) in differentiating PCNSL from other FBLs.  For the 6 studies that used only pathology and/or serology as the gold standard, the pooled sensitivity was 0.85 (95% CI: 0.72 to 0.97) and the pooled specificity was 0.73 (95% CI: 0.54 to 0.92). In the present study, these investigators included only 3 papers on MRS that contained extractable data, 2 of which reported only modest sensitivity and specificity in differentiating lymphoma from other FBLs in HIV patients. Other advanced MRI techniques, such as apparent diffusion coefficient (ADC) ratios, and regional cerebral blood volume (rCBV) had even less reported evidence. According to the authors’ literature research, only 3 studies on diffusion and 1 study on MR perfusion were published on distinguishing lymphoma from other FBLs in HIV-infected patients; 2 studies on diffusion demonstrated significant overlap in ADC ratios of toxoplasmosis and lymphoma. The only study on MR perfusion reported both sensitivity and specificity of 100% in distinguishing lymphoma from other FBLs in 13 patients. The authors stated that further studies are need to investigate the diagnostic accuracy of these advanced MRI techniques.

Evaluation of Migraine Pathophysiology and Identification of Biomarkers in Migraine

Younis and associates (2017) presented an updated and streamlined overview of the metabolic and biochemical aspect of the migraine pathophysiology based on findings from phosphorous (P) and hydrogen (H) MRS studies. Despite of the variation in the methodology and quality of the MRS migraine studies over time, some results were consistent and reproducible.  P-MRS studies suggested reduced availability of neuronal energy and implied a mitochondrial dysfunction in the migraine brain.  H-MRS studies reported inter-ictal abnormalities in the excitatory and inhibitory neurotransmitters, glutamate and γ-aminobutyric acid (GABA), suggesting persistent altered excitability in migraine patients; n-acetylaspartate levels were decreased in migraine, probably due to a mitochondrial dysfunction and abnormal energy metabolism.  The reported abnormalities may increase the susceptibility of migraine patients to excitatory stimulation, such as migraine attack triggers. The authors concluded that several biochemical aspects of the migraine pathophysiology remain to be elucidated using MRS, such as the migraine attack, correlation to disease severity, and medication efficacy.  Moreover, they stated that to identify a biomarker in migraine, MRS may be a valuable non-invasive technique.

Adrenoleukodystrophy

Vawter-Lee and colleagues (2015) reported a novel presentation of childhood cerebral X-linked adrenoleukodystrophy: status epilepticus followed by abrupt and catastrophic neurologic deterioration. Subject was a 3-year old boy with prior history of autism presented with fever, diarrhea, and status epilepticus requiring a pentobarbital coma.  Admission labs were notable only for a glucose level of 22 mg/dL, which stabilized after correction.  The child never returned to his prior neurologic baseline, with complete loss of gross motor, fine motor, and speech skills.  Serial brain MRI/ MRS was notable for progressive diffuse cortical signal changes with swelling, diffusion restriction, and ultimately laminar necrosis.  At 9 months after presentation, CSF protein and MRS lactate were persistently elevated, concerning for a neurodegenerative disorder.  This led to testing for mitochondrial disease, followed by lysosomal and peroxisomal disorders.  Very long-chain fatty acids were elevated.  Identification of a pathogenic ABCD1 mutation confirmed the diagnosis of X-linked adrenoleukodystrophy. The authors concluded that boys with childhood cerebral X-linked adrenoleukodystrophy typically present with gradual behavioral changes.  Rare reports of boys presenting with transient altered mental status or status epilepticus describe a recovery to their pre-presentation baseline.  To the authors’ knowledge, this was the first X-ALD patient to present with status epilepticus with abrupt and catastrophic loss of neurologic function.  They stated that X-linked adrenoleukodystrophy should be suspected in young boys presenting with seizures, acute decline in neurologic function, with persistently elevated CSF protein and MRS lactate.

An UpToDate review on “Overview of the clinical features and diagnosis of brain tumors in adults” (Wong and Wu, 2018) mentions that MR spectroscopy detects white matter abnormalities that may not be apparent on conventional MR imaging and may predict disease progression.  However, its summary and recommendations does not include a recommendation for MR spectroscopy.

Hypoxic-Ischemic Encephalopathy

An UpToDate review on neonatal encephalopathy (Wu, 2019) stated: "In addition to conventional MRI, magnetic resonance spectroscopy (MRS) can provide useful complimentary information regarding the nature and prognosis of brain injury underlying neonatal encephalopathy. In order to evaluate the presence of hypoxic-ischemic brain injury, it is most useful to obtain spectra from locations that are particularly susceptible to injury. Therefore, two regions of interest are most commonly evaluated: the deep gray nuclei (putamen and/or thalamus) and the posterior white matter. An elevated ratio of lactate to n-acetyl acetate (NAA) in the deep gray nuclei has been shown to be a useful indicator of hypoxic-ischemic injury and a predictor of poor outcome."

Zou and colleagues (2018) noted that hypoxic-ischemic encephalopathy (HIE) is a major contributor to child mortality and morbidity. Reliable prognostication for HIE is of key importance. Proton MRS (1H-MRS) is a quantitative, non-invasive method that has been demonstrated to be a suitable complementary tool for prediction. These investigators examined the prognostic capability of 1H-MRS in the era of therapeutic hypothermia (TH). Databases, namely Medline, Embase, Web of Science, and the Cochrane library (Cochrane Center Register of Controlled Trials), were searched for studies published before July 17, 2017. Study selection and data extraction were performed by 2 independent reviewers. The MD or standardized MD (SMD) and 95% CI were calculated using random-effects models. Subgroup analyses were conducted based on the use of TH. Among the 1,150 relevant studies, 7 were included for meta-analysis, but only 2 small studies were conducted under TH. For 1H-MRS measurement, 3 peak area ratios revealed predictive values for adverse outcomes in TH subgroup and the combined results (with and without TH): N-acetylaspartate (NAA)/creatine in basal ganglia/thalamus (BG/T) in TH (MD -0.31, 95% CI: -0.55 to -0.07) and combined results (MD -0.37, 95% CI: -0.49 to -0.25); NAA/choline in BG/T in TH (MD -0.89, 95% CI: -1.43 to -0.35) and combined results (MD -0.25, 95% CI: -0.42 to -0.07); and myo-inositol/choline in cerebral cortex in TH (MD -1.94, 95% CI: -3.69 to -0.19) and combined results (MD -1.64, 95% CI: -2.64 to -0.64). Moreover, NAA relative concentration was associated with adverse outcomes: in TH (MD -0.04, 95% CI: -0.06 to -0.02) and combined results (MD -0.06, 95% CI: -0.11 to -0.01) in white matter; in TH (MD -0.04, 95% CI: -0.07 to -0.01) and combined results (MD -0.05, 95% CI: -0.07 to -0.02) in gray matter. The authors concluded that NAA may be a potential marker in outcome prediction for all HIE subjects. It appeared that MDs for the ratios including NAA were larger than for its relative concentration, and therefore were more likely to be measurable in a clinical context. These researchers stated that larger prospective multi-center studies with a standardized protocol for both measurement protocols and analysis methods are needed in future studies.

Traumatic Brain Injury

Veeramuthu and associates (2018) evaluated the acute alteration of neuro-metabolites in complicated and uncomplicated mTBI patients in comparison to control subjects using proton 1H-MRS. A total of 48 subjects (23 complicated mTBI [cmTBI] patients, 12 uncomplicated mTBI [umTBI] patients, and 13 controls) underwent MRI scan with additional single voxel spectroscopy sequence. Magnetic resonance imaging scans for patients were done at an average of 10 hours (SD =  4.26) post-injury. The single voxel spectroscopy adjacent to side of injury and non-injury regions were analyzed to obtain absolute concentrations and ratio relative to creatine of the neuro-metabolites. One-way analysis of variance was performed to compare neuro-metabolite concentrations of the 3 groups, and a correlation study was done between the neuro-metabolite concentration and Glasgow Coma Scale. Significant difference was found in ratio of NAA to creatine (NAA/Cr + PCr) (χ2(2) = 0.22, p < 0.05) between the groups. The sum of NAA and N-acetylaspartylglutamate (NAAG) also showed significant differences in both the absolute concentration (NAA + NAAG) and ratio to creatine (NAA + NAAG/Cr + PCr) between groups (χ2(2) = 4.03, p < 0.05and (χ2(2) = 0.79, p < 0.05)). NAA values were lower in cmTBI and umTBI compared to control group. A moderate weak positive correlation were found between Glasgow Coma Scale with NAA/Cr + PCr (ρ = 0.36, p < 0.05 and NAA + NAAG/Cr + PCr (ρ = 0.45, p < 0.05)), whereas a moderate correlation was seen with NAA + NAAG (ρ = 0.38, p < 0.05). The authors concluded that neuro-metabolite alterations were already apparent at onset of both complicated and uncomplicated TBI. They stated that the ratio of NAA and NAAG has potential to serve as a biomarker reflecting injury severity in a quantifiable manner as it discriminates between the complicated and uncomplicated cases of mTBI.

Furthermore, UpToDate reviews on “Acute mild traumatic brain injury (concussion) in adults” (Evans RW, Whitlow, 2018), “Severe traumatic brain injury in children: Initial evaluation and management” (Vavilala and Tasker, 2018), and “Management of acute severe traumatic brain injury” (Rajajee, 2018)  do not mention magnetic resonance spectroscopy as a management tool.

Eisele and colleagues (2020) noted that TBI is the most relevant external risk factor for dementia and a major global health burden; and mTBI contributes to up to 90% of all TBIs, and the classification "mild" often misrepresents the patient's burden who suffer from neuropsychiatric long-term sequelae.  Magnetic resonance spectroscopy (MRS) allows in-vivo detection of compromised brain metabolism although it is not routinely used after TBI.  These investigators carried out a systematic review and meta-analysis to examine if MRS has the potential to identify changes in brain metabolism in adult patients after a single mTBI with a negative routine brain scan (CCT and/or MRI scan) compared to aged- and sex-matched healthy controls (HC) during the acute or subacute post-injury phase (less than or equal to 90 days after mTBI).  They performed a comprehensive literature search from the 1st edition of electronic databases until January 31, 2020.  Group analyses were carried out per metabolite using a random-effects model.  Four and 2 out of 5,417 articles met the inclusion criteria for the meta-analysis and systematic review, respectively.  For the meta-analysis, 50 mTBI patients and 51 HC with a mean age of 31 and 30 years, respectively, were scanned using NAA.  Glutamate (Glu), a marker for disturbed brain metabolism, Cho, a marker for increased cell membrane turn-over, and Cr were used in 2 out of the 4 included articles.  Regions of interests were the frontal lobe, the white matter around 1 cm above the lateral ventricles, or the whole brain.  NAA was decreased in patients compared to HC with an effect size (ES) of -0.49 (95% CI: -1.08 to 0.09), primarily measured in the frontal lobe. Glu was increased in the white matter in 22 mTBI patients compared to 22 HC (ES 0.79; 95% CI: 0.17 to 1.41).  Cho was decreased in 31 mTBI patients compared to 31 HC (ES -0.31; 95% CI: -0.81 to 0.19).  Cr was contradictory; thus, potentially not suitable as a reference marker after mTBI.  The authors concluded that MRS pinpointed changes in post-traumatic brain metabolism that correlated with cognitive dysfunction and, therefore, might possibly help to detect mTBI patients at risk for unfavorable outcome or post-traumatic neurodegeneration early. Moreover, these researchers stated that if these metabolites have the capacity to recognize patients with negative routine brain scans that are at risk for post-traumatic long-term sequelae is still not yet clear. Follow-up studies correlating MRS with cognitive outcome are needed to ascertain the potential of these metabolites as biomarkers to predict and detect post-traumatic neurodegeneration at an early stage.

The authors stated that this study had several drawbacks. First, only a limited number of articles with small sample sizes were eligible for inclusion.  Second, MRI sequences, field strength, voxel placements, and sizes were incongruent between studies. Third, Cramer Rao Lower bounds cut-offs were only given in study 3.

Detection of Esophageal Squamous Cell Carcinoma

Liu and colleagues (2019) stated that esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastro-intestinal (GI) malignancies. These researchers used 1H nuclear magnetic resonance spectroscopy (1H-NMR) to identify potential serum biomarkers in patients with early stage ESCC. A total of 65 serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analyzed using 1H-NMR spectroscopy. These researchers distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers. Using OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, 6 serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence. The authors concluded that 1H-NMR spectroscopy may be a useful tumor detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC. Furthermore, these researchers stated that NMR still has a relatively low sensitivity and a narrow dynamic range compared to other platforms (such as mass spectrometry).  They did not achieve absolute quantification of metabolites in their experiment as the lipids and protein were not removed. In the future, using a combination of multiple metabolomic analysis platforms could render a detailed picture of metabolic changes in ESCC patients compared with healthy controls.

Prognosis of Consciousness Recovery in Individuals With Vegetative State

Kondratyeva and colleagues (2019) examined the prognostic value of MRS in patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS). A total of 34 patients with VS/UWS underwent multi-voxel MRS (thalamus, globus pallidus, putamen, internal capsules, fornix, brainstem, temporal and frontal cortex). Subjects were grouped according to etiology: 22 patients with TBI (group 1) and 12 patients with a hypoxia (group 2). The groups were matched by age and duration of UWS (mean of 2, 3 months). The CRS-R was used to identify the 1st signs of consciousness during hospitalization and 6 to 12 months later. Outcomes of the patients with TBI were as follows: chronic VS/UWS (n = 6), minimally conscious state (MCS) plus (n = 9), emergence from MCS (EMCS) (n = 7). Outcomes of the patients with hypoxia were: chronic vegetative state (n = 10), minimally conscious state (MCS) (n = 2). The decrease in the NAA/Cr ratio in thalamus, capsula interna, temporal cortex were correlated with poor outcome in both groups. Higher rates of NAA/Cr in these structures were correlated with further recovery of consciousness. The decrease in the ratio of NAA Cr and NAA/NAA+Cho+Cr in the mid-brain was correlated with poor outcome only in UWS with hypoxia. The authors concluded that the findings of this study suggested that the MRS allowed to more accurately predicting the outcome in VS/UWS patients with hypoxic brain damage, as well as in UWS patients with TBI, who have recovered consciousness to the level of EMCS. These findings need to be validated by well-designed studies.

Detection of Central Nervous System Involvement in Individuals with Rheumatic Autoimmune Diseases

Frittoli and colleagues (2020) stated that proton MRS (1H-MRS) has been shown to be an important non-invasive tool to quantify neuronal loss or damage in the evaluation of CNS disorders.  In a systematic review, these investigators examined the clinical utility of 1H-MRS in determining CNS involvement in individuals with rheumatic autoimmune diseases.  This review of the literature was carried out during the November and December of 2019 of articles published in the last 16 years (2003 to 2019).  The search for relevant references was performed via the exploration of electronic databases (PubMed/Medline and Embase).  These investigators searched for studies including systemic lupus erythematosus (SLE), systemic sclerosis (SSc), juvenile idiopathic arthritis, rheumatoid arthritis (RA), psoriasis, Sjogren's syndrome (pSS), vasculitis and Behcet; only studies published after 2003 and with more than 20 patients were included.  This review included 26 articles; NAA/Cr ratios were significantly lower and Cho/Cr ratios increased in several brain regions in SLE, SS, RA, SSc.  Associations with disease activity, inflammatory markers, CNS manifestations and co-morbidities varied across studies and diseases.  The authors concluded that the presence of neuro-metabolite abnormalities in patients without overt CNS manifestations, suggested that systemic inflammation, atherosclerosis or abnormal vascular reactivity may be associated with subclinical CNS manifestations.  These researchers stated that MRS may be a useful non-invasive method for screening rheumatic autoimmune diseases patients with risk for CNS manifestations.

Evaluation of Hepatic Encephalopathy

Zeng and colleagues (2020) noted that various imaging modalities have been used to examine pathogenic mechanisms and stratify the severity of hepatic encephalopathy (HE).  In a meta-analysis, these investigators hypothesized that there is a progressive identifiable derangement of imaging measures using MRS related to the severity of the HE.  Studies with more than 10 cases and HE diagnosis were identified from the electronic data-bases PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Literatura Latino Americana em Ciências da Saúde (LILACS), and Cochrane Central Register of Controlled Trials (CENTRAL) through July 25, 2018.  Subjects were stratified into healthy controls and patients with non-HE (NHE) (cirrhosis without HE), minimal HE (MHE), and overt HE (OHE).  Analyses were organized by metabolite studied and brain region examined.  Statistical meta-analysis was carried out using the metafor package in R (v3.4.1).  Pooled SMDs between patient groups were calculated using a random effects model.  These researchers identified 31 studies (1,481 patients) that included data on cirrhosis-related HE.  They found the parietal region to be the most reliable in differentiating between patients with and without MHE, with SMDs of +0.82 (95% CI: +0.49 to +1.15, p < 0.0001, I2 = 37.45%) for glutamine/glutamate, -0.36 (95% CI: -0.61 to -0.10, p = 0.007, I2 = 20.00%) for choline, and-0.77 (95% CI: -1.19 to -0.34, p = 0.0004, I2 = 67.48%) for myo-inositol.  These investigators also found that glutamine/glutamate was the metabolite that reliably correlated with HE grade in all brain regions.  The authors concluded that the findings of this meta-analysis showed that MRS changes in glutamine/glutamate, choline, and myo-inositol, especially in the parietal lobe, correlated with the severity of HE; they stated that MRS may be of value in the evaluation of HE. Moreover, these researchers stated that to better facilitate direct comparison between imaging modalities in the future, researchers should design more multi-modal studies that take advantage of contemporary and evolving imaging techniques.

The authors stated that a major drawback of this study was the observed high levels of heterogeneity in some of the analyzed outcomes.  This was the result of methodologic differences between studies, including sample size, geographic location, MRI technology, treatment of HE, and the varied assessment of HE.  The studies utilized different neuro-psychometric test cut-offs for definition of MHE, and not all studies reported their method of MHE definition.  One study defined MHE as the presence of prior HE in patients. Given the complexity of categorization between NHE and MHE, there should be a push for standardization of MHE diagnosis for study comparison.  It is generally preferable to analyze neuro-psychometric result as a continuous variable; however, this meta-analysis necessitated categorization of patients into discrete groups.  Finally, as this meta-analysis included many studies that were heterogenous in their patient classification, these researchers decided to group and analyze MHE and CHE together due to their considerable overlap in definition.  In parallel, OHE classification in each study could refer to patients of any West Haven grade, and the severity of OHE between studies also varied considerably.

Furthermore, an UpToDate review on “Hepatic encephalopathy in adults: Clinical manifestations and diagnosis” (Ferenci, 2020) states that “In vivo magnetic resonance spectroscopy (MRS) is a noninvasive method that is being studied but is not yet in routine clinical use.  It permits serial measurement of various neurometabolites in the brain using a variety of isotopes, such as (1)H, (32)P, and (12)C.  Proton (1H) MRS assesses regional brain concentrations of choline, creatine (Cr), glutamine/glutamate (Glx), myoinositol, and N-acetyl aspartate, depending on the spectral sequence used.  (1H) MRS has tremendous potential for the future, particularly for documenting treatment effects”.

Diagnosis of MELAS (Mitochondrial Encephalomyopathy with Lactic Acidosis and Stroke-Like Episodes)

Hovsepian et al (2019) examined the use of MRS as a biomarker of response to L-arginine in mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS).  These researchers described a case of MELAS treated with L-arginine that showed improvement clinically and on serial MRS.  MRS was performed on a 1.5-Tesla scanner to evaluate a MELAS patient before, during, and after intravenous (IV) L-arginine therapy for the treatment of stroke-like episodes.  L-arginine was infused at a dose of 500 mg/kg daily for 7 days followed by oral arginine therapy.  The patient had clinical improvement following treatment with IV L-arginine.  MRS performed before, during, and after treatment with IV L-arginine showed significant improvement in brain lactate and increase in the N-acetylaspartate/Choline (NAA/Cho) ratio compared to pre-treatment baseline.  The authors concluded that serial MRS imaging showed significant improvement in lactate peaks and NAA/Cho ratios that corresponded with clinical improvement after L-arginine therapy.  Given this correlation between radiologic and clinical improvement, MRS may be a useful biomarker assessing response to treatment in MELAS.

Consensus-based statements on “Management of mitochondrial stroke-like episodes” (Ng et al, 2019) did not mention MRS as a management option.

An UpToDate review on “Mitochondrial myopathies: Clinical features and diagnosis” (O’Ferrall, 2021) states that “New magnetic resonance techniques, including magnetic resonance spectroscopy (MRS) of the brain to look for elevated lactate, may also be useful where this method is available.  MRS of muscle or even cardiac tissue may be useful in the future but requires further research”.

Diagnosis of Mesial Temporal Sclerosis

Fernandez-Vega and colleagues (2021) stated that MRS provides non-invasive information regarding metabolic features in different regions of the brain affected by mesial temporal sclerosis (MTS).  These investigators reviewed articles analyzing the most common alterations in biochemical parameters in MTS and the applications of MRS in pre-surgical assessment.  They carried out a systematic search for MRS in MTS in PubMed, SCOPUS, and Cochrane based on the MESH terms "magnetic resonance spectroscopy", "proton magnetic resonance spectroscopy", "carbon-13 magnetic resonance spectroscopy", "1H-MRS", "31P-MRS", "mesial temporal sclerosis", "hippocampal sclerosis", "mesial temporal seizure", and "mesial temporal epilepsy".  Of the initial 134 articles found, 30 were selected after the exclusion process.  Of these, 13 detected a decrease in N-acetylaspartate (NAA), 9 showed a decreased in the ratio NAA/Cho+Cr, and 8 demonstrated a decreased in the ratio NAA/Cr, all of them in the ipsilateral hippocampus; 9 studies also found reduced NAA levels in extra-hippocampal regions.  The authors concluded that the main findings were a decrease in NAA in the ipsilateral hippocampus.  Furthermore, NAA levels were low outside the hippocampus so MTS could be a more extensive disease.  Patients without MTS also presented a decrease in NAA in the ipsilateral hippocampus although NAA was even lower in the MTS patients; therefore, MRS could be useful in the pre-surgical evaluation to locate the epileptogenic focus, but not specific for the diagnosis of MTS.

Evaluation of Neurometabolic Alterations in Motor Neuron Disease

Chritidi et al (2022) stated that MRS has contributed important academic insights in motor neuron diseases (MNDs), especially in amyotrophic lateral sclerosis (ALS).  Over the last 30 years, momentous methodological advances took place, including the emergence of high-field MRI platforms, multi-voxel techniques, whole-brain protocols, novel head-coil designs, and a multitude of open-source imaging suites.  Technological advances in MRS are complemented by important conceptual developments in MND, such as the recognition of the importance of extra-motor brain regions, multi-timepoint longitudinal study designs, assessment of asymptomatic mutation carriers, description of genotype-associated signatures, and the gradual characterization of non-ALS MND phenotypes.  In a systematic review, these investigators examined published MRS studies in MND to identify important emerging research trends, key lessons from pioneering studies, and stereotyped shortcomings.  They also sought to highlight notable gaps in the current literature so that research priorities for future studies could be outlined.  The authors concluded that MRS remains one of the most promising MR-based imaging modalities in MND, which offers invaluable metabolic data non-invasively.  Existing studies have already cemented the academic role of MRS by characterizing neurodegenerative processes in MND.  An urgent priority of future investigation is to define, gauge, and establish the clinical role MRS in expediting the diagnosis, monitoring disease progression and assessing response to therapy.

The authors stated that a potential limitation of this study was that search and data extraction was conducted on a single database.  Furthermore, the review of published MRS studies revealed common study limitations.  Most of the published MRS studies centered on ALS, especially earlier studies in the field, only reported MRS alterations and corresponding structural, diffusivity and functional changes were not evaluated.  Another limitation was the lack of MRS studies in GGGGCC hexanucleotide repeat carriers in C9orf72.  While the structural correlates of C9orf72 have been extensively investigated, the metabolic correlates of this genotype remain to be characterized.

Evaluation of Post-Traumatic Stress Disorder

Swanberg et al (2022) noted that post-traumatic stress disorder (PTSD) is associated with wide-ranging abnormalities across the body.  While various methods have examined these deviations, only proton MRS (1H-MRS) enables non-invasive measurement of small-molecule metabolites in the living human.  1H-MRS has correspondingly been used to test hypotheses regarding the composition and function of multiple brain regions putatively involved in PTSD.  In a systematic review, these investigators examined methodological considerations and reported findings, both positive and negative, of the current 1H-MRS literature in PTSD (n = 32 studies) to communicate the brain regional metabolite alterations heretofore observed, providing random-effects model meta-analyses for those most extensively studied.  The findings of this review suggested significant PTSD-associated decreases in N-acetyl aspartate in bilateral hippocampus and anterior cingulate cortex with less evident effect in other metabolites and regions.  Model heterogeneities diverged widely by analysis (I2 of less than 0.01 % to 90.1 %) and suggested regional dependence on quantification reference (creatine or otherwise).  The authors concluded that while observed variabilities in methods and reported findings suggested that 1H-MRS examinations of PTSD could benefit from methodological standardization, informing this standardization by quantitative assessment of the existing literature is currently hampered by its small size and limited scope.  These researchers stated that the potential for 1H-MRS to forge new ground in the understanding of PTSD, as well as play a role in the development of biomarkers for risk, diagnosis, and/or treatment monitoring, is not only as-yet largely untried; but has also yielded meaningfully interpretable information where it has been, therefore remaining a useful piece of the puzzle behind the pathogenesis and evolution of this life-changing condition.

Identification of Metabolomic profile in Individuals with Idiopathic Intracranial Hypertension

In a case-control study, Grech et al (2022) examined the metabolomic profile in the CSF, serum, and urine of patients with idiopathic intracranial hypertension (IIH) compared with that in controls and measured changes in metabolism associated with clinical markers of disease activity and treatment.  This trial compared women aged 18 to 55 years with active IIH (Friedman diagnostic criteria) with a sex-matched, age-matched, and body mass index (BMI)-matched control group.  IIH patients were identified from neurology and ophthalmology clinics from National Health Service (NHS) hospitals and underwent a prospective intervention to induce disease remission via weight loss with re-evaluation at 12 months.  Clinical assessments included lumbar puncture, headache, papilledema, and visual measurements.  Spectra of the CSF, serum, and urine metabolites were acquired using proton nuclear MRS.  Urea was lower in IIH participants (CSF, controls median ± inter-quartile range [IQR] 0.196 ± 0.008, IIH 0.058 ± 0.059, p < 0.001; urine, controls 5,971.370 ± 3,021.831, IIH 4,691.363 ± 1,955.774, p = 0.009), correlated with intra-cranial pressure (ICP) (urine p = 0.019) and headache severity (CSF p = 0.031), and increased by 12 months (CSF 12 months; 0.175 ± 0.043, p = 0.004, urine; 5,210.874 ± 1,825.302, p = 0.043).  The lactate:pyruvate ratio was increased in IIH patients compared with that in controls (CSF, controls 49.739 ± 19.523, IIH 113.114 ± 117.298, p = 0.023; serum, controls 38.187 ± 13.392, IIH 54.547 ± 18.471, p = 0.004) and decreased at 12 months (CSF, 113.114 ± 117.298, p < 0.001).  Baseline acetate was higher in IIH patients (CSF, controls 0.128 ± 0.041, IIH 0.192 ± 0.151, p = 0.008), correlated with headache severity (p = 0.030) and headache disability (p = 0.003), and was reduced at 12 months (0.160 ± 0.060, p = 0.007).  Ketones, 3-hydroxybutyrate and acetoacetate, were altered in the CSF at baseline in IIH patients (3-hydroxybutyrate, controls 0.074 ± 0.063, IIH 0.049 ± 0.055, p = 0.019; acetoacetate, controls 0.013 ± 0.007, IIH 0.017 ± 0.010, p = 0.013) and normalized at 12 months (0.112 ± 0.114, p = 0.019, 0.029 ± 0.017, p = 0.015, respectively).  The authors observed metabolic disturbances that were evident in the CSF, serum, and urine of IIH patients, suggesting global metabolic dysregulation.  Altered ketone body metabolites normalized after therapeutic weight loss.  CSF:serum urea ratio was altered, which may influence ICP dynamics and headache.  Elevated CSF acetate, known to stimulate trigeminal sensitization, was associated with headache morbidity.  These researchers stated that these findings extended their knowledge of IIH etiology and provided a roadmap for future mechanistic studies.  They stated that further investigation is needed to validate their findings and to establish which metabolites may be the most clinically useful as biomarkers of disease diagnosis, progression, and outcome.  This may include instigation of the role of these key metabolites in IIH pathogenesis in animal and cell models.

The authors stated that this study had several drawbacks, one of which was the smaller number of control participants in comparison with IIH participants.  Participants were matched by age, sex, and BMI, which limited the number of controls eligible for inclusion.  However, obtaining detailed phenotyping and CSF collections from healthy BMI-matched controls is challenging due to ethical considerations and participant acceptability.  Despite this, these investigators presented the largest group of controls matched for age, sex, and BMI of any IIH studies.  Because this study was limited to including women only, the results may not be generalizable to children and men with IIH.  These researchers found that not all clinical markers (including papilledema) were correlated with metabolites.  This may be related to the severity of disease in participants; thus, performing this analysis in a more severe disease cohort would be of future interest.  These investigators acknowledged that a small number of patients were on medications and could not exclude that this may have affected the metabolite profile; however, there were no significant changes noted to result from medications (e.g., acetazolamide).  Thus, it was unlikely that the medications meaningfully change the inference of these findings.

Prediction of Neurodevelopmental Impairment in Preterm Neonates

In a systematic review, Laccetta et al (2022) examined the diagnostic utility of 1H-MRS in early diagnosis of neurodevelopmental impairment in preterm newborns.   The systematic review was carried out in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements.  Eligible articles were searched in Medline, Scopus, and ISI Web of Science databases using the following medical subject headings and terms: "magnetic resonance spectroscopy", "infant" and "newborn".  Studies of any design published until December 20, 2021 and meeting the following criteria were selected: First, studies including newborns with gestational age at birth 37 weeks or less which underwent at least 1 1H-MRS scan within 52 weeks' post-menstrual age and neurodevelopmental assessment within 4 years of age.  Second, studies in which preterm newborns with congenital infections, genetic disorders, and brain congenital anomalies were clearly excluded.  Data regarding the relationship between metabolite ratios in basal ganglia, thalamus, and white matter, and neurodevelopment were analyzed.  The quality assessment of included studies was carried out according to the criteria from the QUADAS-2.  N-acetylaspartate (NAA)/choline (Cho) was the most studied metabolite ratio.  Lower NAA/Cho ratio in basal ganglia and thalamus was associated with adverse motor, cognitive, and language outcomes, and worse global neurodevelopment.  Lower NAA/Cho ratio in white matter was associated with cognitive impairment.  However, some associations came from single studies or were discordant among studies.  The quality of included studies was low.  The authors concluded that 1H-MRS could be a promising tool for early diagnosis of neurodevelopmental impairment.  Moreover, these researchers stated that further studies of good quality are needed to define the relationship between metabolite ratios and neurodevelopment.

In a cohort study, Gire et al (2022) identified in the preterm EPIRMEX cohort any correlations between 1H-MRS metabolites ratio at term equivalent age (TEA) and neurodevelopmental outcomes at 2 years.  This trial included EPIRMEX eligible patients who were very preterm infants (gestational age at birth 32 or less weeks) and who underwent a brain MRI at TEA and 1H-MRS using a mono-voxel technique.  The volumes of interest (VOI) were periventricular white matter posterior area and basal ganglia.  The ratio of NAA to Cho, NAA to Cr (creatine), Cho to Cr, and Lac (Lactate) to Cr were measured.  Neurodevelopment was evaluated at 24 months TEA with ASQ (Ages and Stages Questionnaire).  A total of 69 very preterm infants had a 1H-MRS at TEA.  In white matter there was a significant correlation between a reduction in the NAA/Cho ratio and a total ASQ and/or abnormal communication score, and an increase in the Lac/Cr ratio and an abnormality of fine motor skills.  In the gray nuclei there was a trend correlation between the reduction in the NAA/Cho ratio and sociability disorders; and the increase in the Lac/Cr ratio and an anomaly in problem-solving.  The authors concluded that using NAA as a biomarker, the vulnerability of immature oligodendrocytes in preterm children at TEA was correlated to neurodevelopment at 2 years.  Similarly, the presence of lactate at TEA was associated with abnormal neurodevelopment at 2 years in the preterm brain.  Moreover, these researchers stated that population-based, multi-center studies in preterm infants are needed to confirm the results with mono-voxel metabolic profiles to obtain detailed information on metabolites in the posterior periventricular zone, the deep gray matter, and the cerebellum, known to be areas at risk in preterm newborns at TEA. 

The authors stated that this study had several drawbacks.  First, the sample size was relatively small and nested in a population-based study.  Given the exploratory nature of the study, a prospective study with a larger sample size is needed to validate the findings of this study.  Second, the MRI was carried out at different periods (37 to 42 weeks).  There was no comparison group with term infants.  Third, normal development at 24 months of corrected age may not reflect normal motor, cognitive, and language functions at older ages.  Generally, higher-order or more subtle brain dysfunction will not be evident until later on in childhood.

Mood Disorders / Psychosis

Reddy-Thootkur et al (2022) noted that epidemiologic, genetic, and neurobiological studies suggested considerable overlap between schizophrenia and mood disorders.  More importantly, both disorders are associated with a broad range of cognitive deficits as well as altered glutamatergic and GABAergic neuro-metabolism.  In a systematic review, these investigators reviewed MRS studies examining the relationship between glutamatergic and GABAergic neuro-metabolites and cognition in schizophrenia spectrum disorders and mood disorders.  They carried out a literature search in PubMed of studies published before April 15, 2019 and 37 studies were deemed eligible for systematic review.  These investigators found that alterations in glutamatergic and GABAergic neurotransmission have been identified relatively consistently in both schizophrenia and mood disorders.  However, because of the vast heterogeneity of published studies in terms of illness stage, medication exposure, MRS acquisition parameters and data post-processing strategies, these researchers still do not understand the relationship between those neurotransmitters and cognitive dysfunction in mental illness, which is a critical initial step for rational drug development.  The authors concluded that these findings emphasized the need for coordinated multi-center studies that characterize cognitive function and its biological substrates in large and well-defined clinical populations, using harmonized imaging sequences and analytical methods with the objective to elucidate the underlying pathophysiological mechanisms and to inform future clinical trials.

The authors stated that this study had several drawbacks.  First, these researchers did not carry out analyses examining possible confounds of anti-psychotic medication exposure or illness chronicity on the relationships between cognition and neuro-metabolite levels, because only a limited number of studies were carried out in drug-naive patients experiencing their 1st episode of psychosis or a mood disorder.  Second, in those with a more chronic illness, medication exposure was, perhaps not surprisingly, heterogeneous ranging from anti-depressants to mood stabilizers to anti-psychotic drugs or combinations thereof.  These investigators also chose not to conduct meta-analyses to quantify findings as distinct brain regions have differing relevance for diverse cognitive domains and metabolite alterations were not uniform across brain regions.  Third, with the number of studies published in individual cognitive domains in different brain regions , these researchers did not have the statistical power accurately capture this diversity.  Fourth, it was not possible to equate the glutamate, glutamine and GABA metabolite peaks captured with MRS to neurotransmission.

Bissonnette et al (2022) stated that glutamate and NAA have been examined in the neuropathology of chronic schizophrenia, with fewer studies focusing on early phase psychosis.  Furthermore, there has been little review and synthesis of the literature focused on multiple brain regions.  In a systematic review, these investigators discussed the current state of research on glutamate and NAA concentrations in early phase psychosis (EPP; defined as the first 5 years following psychosis onset) in multiple brain regions.  Existing literature was searched systematically to compile reports of glutamate/glutamate+glutamine (Glx) and NAA absolute levels and ratios in both male and female patients with early phase psychosis.  Reports on glutamate/Glx concentrations in the medial prefrontal region and thalamus were varied, but the majority of reports suggested no alterations in EPP.  No studies reported glutamate alterations in the hippocampus or cerebellum.  There was no evidence for NAA alterations in the caudate, basal ganglia, and medial prefrontal cortex, and minimal evidence for NAA reductions in the thalamus, anterior cingulate cortex, and hippocampus.  The authors concluded that future research should focus on the regions that are less commonly reported, and should aim to examine possible confounds, such as medication status and substance use.


References

The above policy is based on the following references:

  1. Baltzer PA, Dietzel M. Breast lesions: Diagnosis by using proton MR spectroscopy at 1.5 and 3.0 T -- systematic review and meta-analysis. Radiology. 2013;267(3):735-746.
  2. Bartella L, Huang W. Proton (1H) MR spectroscopy of the breast. Radiographics. 2007;27 Suppl 1:S241-S252.
  3. Beadle R, Frenneaux M. Magnetic resonance spectroscopy in myocardial disease. Expert Rev Cardiovasc Ther. 2010;8(2):269-277.
  4. Benoist M. The Michel Benoist and Robert Mulholland Yearly European Spine Journal Review: A survey of the "medical" articles in the European Spine Journal, 2018. Eur Spine J. 2019;28(1):10-20.
  5. Bissonnette JN, Francis AM, MacNeil S, et al. Glutamate and N-acetylaspartate alterations observed in early phase psychosis: A systematic review of proton magnetic resonance spectroscopy studies. Psychiatry Res Neuroimaging. 2022;321:111459.
  6. Bitencourt AGV, Goldberg J, Pinker K, Thakur SB. Clinical applications of breast cancer metabolomics using high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS): Systematic scoping review. Metabolomics. 2019;15(11):148.
  7. Bizzi A, et al. Classification of childhood white matter disorders using proton MR spectroscopic imaging. AJNR Am J Neuroradiol. 2008;29(7):1270-1275.
  8. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Magnetic resonance spectroscopy for evaluation of suspected brain tumor. TEC Assessment Program. Chicago, IL: BCBSA; June 2003;18(1). 
  9. Boesch SM, Wolf C, Seppi K, et al. Differentiation of SCA2 from MSA-C using proton magnetic resonance spectroscopic imaging. J Magn Reson Imaging. 2007;25(3):564-569.
  10. Brugger S, Davis JM, Leucht S, Stone JM. Proton magnetic resonance spectroscopy and illness stage in schizophrenia -- a systematic review and meta-analysis. Biol Psychiatry. 2011;69(5):495-503.
  11. Canadian Coordinating Office for Health Technology Assessment (CCOHTA). Magnetic resonance spectroscopy (MRS) in the management of localized prostate cancer. Emerging Technology List. No. 17. Ottawa, ON: CCOHTA; September 2003.
  12. Centers for Medicare & Medicaid Services (CMS). Decision memo for magnetic resonance spectroscopy for brain tumors (CAG-00141N). Baltimore, MD: CMS; January 29, 2004. 
  13. Cevik N, Koksal A, Dogan VB, et al. Evaluation of cognitive functions of juvenile myoclonic epileptic patients by magnetic resonance spectroscopy and neuropsychiatric cognitive tests concurrently. Neurol Sci. 2016;37(4):623-627.
  14. Chen T, Tan H, Lei H, et al. Nature of glutamate alterations in substance dependence: A systematic review and meta-analysis of proton magnetic resonance spectroscopy studies. Psychiatry Res Neuroimaging. 2021;315:111329.
  15. Chen WS, Li JJ, Hong L, et al. Diagnostic value of magnetic resonance spectroscopy in radiation encephalopathy induced by radiotherapy for patients with nasopharyngeal carcinoma: A meta-analysis. Biomed Res Int. 2016;2016:5126074.
  16. Christidi F, Karavasilis E, Argyropoulos GD, et al. Neurometabolic alterations in motor neuron disease: Insights from magnetic resonance spectroscopy. J Integr Neurosci. 2022;21(3):87.
  17. Clarke CE, Lowry M. Systematic review of proton magnetic resonance spectroscopy of the striatum in Parkinsonian syndromes. Eur J Neurol. 2001;8(6):573-577.
  18. Conseil d'Evaluation des Technologies de la Sante du Quebec (CETS). In vivo magnetic resonance spectroscopy -- nonsystematic review. Pub. No. CETS 98-6 NE. Montreal, QC: CETS; 1999.
  19. Corabian P, Hailey D. Functional diagnostic imaging in epilepsy. Technology Assessment Report. Pub. No. HTA10. Edmonton, AB: Alberta Heritage Foundation for Medical Research (AHFMR); August 1998. 
  20. Cox IJ. Development and applications of in vivo clinical magnetic resonance spectroscopy. Prog in Biophys Mol Biol. 1996;65(1-2):45-81.
  21. De Stefano N, Filippi M, Miller D, et al. Guidelines for using proton MR spectroscopy in multicenter clinical MS studies. Neurology. 2007;69(20):1942-1952.
  22. Dowling C, Bowlen AW, Noworolski SM, et al. Preoperative proton MR spectroscopic imaging of brain tumors: Correlation with histopathologic analysis of resection specimens. AJNR Am J Neuroradiol. 2001;22(4):604-612.
  23. Duncan JS. Imaging and epilepsy. Brain. 1997;120(Pt 2):339-377.
  24. Dyke JP, Sanelli PC, Voss HU, et al. Monitoring the effects of BCNU chemotherapy Wafers (Gliadel) in glioblastoma multiforme with proton magnetic resonance spectroscopic imaging at 3.0 Tesla. J Neurooncol. 2007;82(1):103-110. 
  25. Eisele A, Hill-Strathy M, Michels L, Rauen K.  Magnetic resonance spectroscopy following mild traumatic brain injury: A systematic review and meta-analysis on the potential to detect posttraumatic neurodegeneration. Neurodegener Dis. 2020;20(1):2-11.
  26. Evans RW, Whitlow CT. Acute mild traumatic brain injury (concussion) in adults. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed November 2018.
  27. Falini A, Calabrese G, Origgi D, et al. Proton magnetic resonance spectroscopy and intracranial tumours: Clinical perspectives. J Neurol. 1996;243(10):706-714.
  28. Federico F, Simone IL, Lucivero V, et al. Proton magnetic resonance spectroscopy in Parkinson's disease and progressive supranuclear palsy. J Neurol Neurosur Psychiatry. 1997;62(3):239-242.
  29. Fenton BW, Lin CL, Macedonia C. Instruments and methods. Magnetic resonance spectroscopy to detect lecithin in amniotic fluid and fetal lung. Obstet Gynecol. 2000;95(3):457-460.
  30. Ferenci P. Hepatic encephalopathy in adults: Clinical manifestations and diagnosis. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed December 2020.
  31. Fernandez-Vega N, Ramos-Rodriguez JR, Alfaro F, et al. Usefulness of magnetic resonance spectroscopy in mesial temporal sclerosis: A systematic review. Neuroradiology. 2021;63(9):1395-1405.
  32. Filippi M, Rocca MA, Arnold DL, et al. EFNS guidelines on the use of neuroimaging in the management of multiple sclerosis. Eur J Neurol. 2006;13(4):313-325.
  33. Finnell DS. A clinical translation of the article titled, "The utility of magnetic resonance spectroscopy for understanding substance use disorders: A systematic review of the literature". J Am Psychiatr Nurses Assoc. 2015;21(4):276-278.
  34. Firbank MJ, Harrison RM, O'Brien JT. A comprehensive review of proton magnetic resonance spectroscopy studies in dementia and Parkinson's disease. Dement Geriatr Cogn Disord. 2002;14(2):64-76.
  35. Fisher M, Prichard JW, Warach S. New magnetic resonance techniques for acute ischemic stroke. JAMA. 1995;274(11):908-911.
  36. Fradet V et al. Prostate cancer managed with active surveillance: Role of anatomic MR imaging and MR spectroscopic imaging. Radiology. 2010;256(1):176-183.
  37. Frittoli RB, Pereira DR, Rittner L, Appenzeller S. Proton magnetic resonance spectroscopy ( 1 H-MRS) in rheumatic autoimmune diseases: A systematic review. Lupus. 2020;29(14):1873-1884.
  38. Garcia PA, Laxer KD, Magnetic resonance spectroscopy. Neuroimaging Clin N Am. 1995;5(4):675-682.
  39. Gardner A, Iverson GL, Stanwell P. A systematic review of proton magnetic resonance spectroscopy findings in sport-related concussion. J Neurotrauma. 2014;31(1):1-18.
  40. Gire C, Berbis J, Dequin M, et al. A correlation between magnetic resonance spectroscopy (1-H MRS) and the neurodevelopment of two-year-olds born preterm in an EPIRMEX cohort study. Front Pediatr. 2022;10:936130.
  41. Gluch L. Magnetic resonance in surgical oncology: II - literature review. ANZ J Surg. 2005;75(6):464-470.
  42. Gornet MG, Peacock J, Claude J, et al. Magnetic resonance spectroscopy (MRS) can identify painful lumbar discs and may facilitate improved clinical outcomes of lumbar surgeries for discogenic pain. Eur Spine J. 2019;28(4):674-687.
  43. Grech O, Seneviratne SY, Alimajstorovic Z, et al. Nuclear magnetic resonance spectroscopy metabolomics in idiopathic intracranial hypertension to identify markers of disease and headache. Neurology. 2022;99(16): e1702-e1714.
  44. Halperin JJ. Nervous system Lyme disease. UpToDate [online serial], Waltham, MA: UpToDate; reviewed January 2015.
  45. Harmon KG, Drezner JA, Gammons M, et al. American Medical Society for Sports Medicine position statement: Concussion in sport. Br J Sports Med. 2013;47(1):15-26.
  46. Hellem T, Shi X, Latendresse G, Renshaw PF. The utility of magnetic resonance spectroscopy for understanding substance use disorders: A systematic review of the literature. J Am Psychiatr Nurses Assoc. 2015;21(4):244-275.
  47. Heun R, Schlegel S, Graf-Morgenstern M, et al. Proton magnetic resonance spectroscopy in dementia of Alzheimer type. Int J Geriatr Psychiatry. 1997;12(3);349-358.
  48. Hollingworth W, Medina LS, Lenkinski RE, et al. A systematic literature review of magnetic resonance spectroscopy for the characterization of brain tumors. AJNR Am J Neuroradiol. 2006;27(7):1404-1411.
  49. Horská A, Barker C. Imaging of brain tumors: MR spectroscopy and metabolic imaging. Neuroimaging Clin N Am. 2010;20(3):293-310.
  50. Hovsepian DA, Galati A, Chong RA, et al. MELAS: Monitoring treatment with magnetic resonance spectroscopy. Acta Neurol Scand. 2019;139(1):82-85.
  51. Hu L. Clinical manifestations of Lyme disease in adults. UpToDate [online serial], Waltham, MA: UpToDate; reviewed January 2015.
  52. Israel GM, Francis IR, Roach M III, et al, Expert Panel on Urologic Imaging and Radiation Oncology-Prostate. Pretreatment staging prostate cancer [online publication]. Reston, VA: American College of Radiology (ACR); 2007.
  53. Jambor I, Borra R, Kemppainen J, et al. Functional imaging of localized prostate cancer aggressiveness using 11C-acetate PET/CT and 1H-MR spectroscopy. J Nucl Med. 2010;51(11):1676-1683.
  54. Jenkins BG, Kraft E. Magnetic resonance spectroscopy in toxic encephalopathy and neurodegeneration. Curr Opin Neurol. 1999;12(6):753-760.
  55. Jessen F, Gür O, Block W, et al. A multicenter (1)H-MRS study of the medial temporal lobe in AD and MCI. Neurology. 2009;72(20):1735-1740.
  56. Jordan HS, Bert R, Chew P, et al., and the Tufts-New England Medical Center Evidence-Based Practice Center. Magnetic resonance spectroscopy for brain tumors. EPC Technical Support of the CPTA Technology Assessment Program. Prepared for the Agency for Healthcare Research and Quality (AHRQ). Contract No. 290-02-0022, Task Order # 1. Rockville, MD: AHRQ; revised June 13, 2003. 
  57. Jung AJ, Westphalen AC. Imaging prostate cancer. Radiol Clin North Am. 2012; 50(6).
  58. Kantarci K, Jicha GA. Development of 1H MRS biomarkers for tracking early predementia Alzheimer disease. Neurology. 2019;92(5):209-210.
  59. Karl A, Werner A. The use of proton magnetic resonance spectroscopy in PTSD research -- meta-analyses of findings and methodological review. Neurosci Biobehav Rev. 2010;34(1):7-22.
  60. Keshari KR, Lotz JC,  Link TM, et al. Lactic acid and proteoglycans as metabolic markers for discogenic back pain. Spine. 2008;33(3):312-317.
  61. Kesler SR, Lightbody AA, Reiss AL. Cholinergic dysfunction in fragile X syndrome and potential intervention: A preliminary 1H MRS study. Am J Med Genet A. 2009;149A(3):403-407.
  62. Kondratyeva EA, Diment SV, Kondratyev SA, et al. Magnetic resonance spectroscopy data in the prognosis of consciousness recovery in patients with vegetative state. Zh Nevrol Psikhiatr Im S S Korsakova. 2019;119(10):7-14.
  63. Kubota M, Moriguchi S, Takahata K, et al. Treatment effects on neurometabolite levels in schizophrenia: A systematic review and meta-analysis of proton magnetic resonance spectroscopy studies. Schizophr Res. 2020;222:122-132.
  64. Kuzniecky R. Magnetic resonance and functional magnetic resonance imaging: Tools for the study of human epilepsy. Curr Opin Neurol. 1997;10(2):88-91.
  65. Kuzniecky RI, Knowlton RC. Neuroimaging of epilepsy. Semin Neurol. 2002;22(3):279-288.
  66. Kwek JW, Thng CH. MR imaging and MR spectroscopy of adenocarcinoma of the prostate. Ann Acad Med Singapore. 2003;32(4):500-506.
  67. Laccetta G, De Nardo MC, Cellitti R, et al. 1H-magnetic resonance spectroscopy and its role in predicting neurodevelopmental impairment in preterm neonates: A systematic review. Neuroradiol J. 2022;35(6):667-677.
  68. Laxer KD. Clinical applications of magnetic resonance spectroscopy. Epilepsia. 1997;38(Suppl 4):S13-S17.
  69. Leclerc X, Huisman TA, Sorensen AG. The potential of proton magnetic resonance spectroscopy ((1)H-MRS) in the diagnosis and management of patients with brain tumors. Curr Opin Oncol. 2002;14(3):292-298.
  70. Lee CP, Payne GS, Oregioni A, et al. A phase I study of the nitroimidazole hypoxia marker SR4554 using 19F magnetic resonance spectroscopy. Br J Cancer. 2009;101(11):1860-1868.
  71. Lee JW, Sreepada LP, Bevers MB, et al. Magnetic resonance spectroscopy of hypoxic-ischemic encephalopathy after cardiac arrest. Neurology. 2022;98(12):e1226-e1237.
  72. Liu H, Zhang D, Lin H, et al. Meta-analysis of neurochemical changes estimated via magnetic resonance spectroscopy in mild cognitive impairment and Alzheimer's disease. Front Aging Neurosci. 2021;13:738971.
  73. Liu YY, Yang ZX, Ma LM, et al. 1H-NMR spectroscopy identifies potential biomarkers in serum metabolomic signatures for early stage esophageal squamous cell carcinoma. PeerJ. 2019;7:e8151.
  74. Malhi GS, Valenzuela M, Wen W, et al. Magnetic resonance spectroscopy and its applications in psychiatry. Aust N Z J Psychiatry. 2002;36(1):31-43.
  75. Matchar DB, Kulasingam SL, Huntington A, et al. Positron emission tomography, single photon emission computed tomography, computed tomography, functional magnetic resonance imaging, and magnetic resonance spectroscopy and for the diagnosis and management of Alzheimer's dementia. Prepared by the Duke Center for Clinical Health Policy Research and Evidence Practice Center for the Agency for Healthcare Research and Quality (Contract No. 290-02-0025, Task Order No. 1). Rockville, MD: Agency for Healthcare Research and Quality (AHRQ); 2004.
  76. McCully K, Mancini D, Levine S. Nuclear magnetic resonance spectroscopy: Its role in providing valuable insight into diverse clinical problems. Chest. 1999;116(5):1434-1441.
  77. Merritt K, Egerton A, Kempton MJ, et al. Nature of glutamate alterations in schizophrenia: A meta-analysis of proton magnetic resonance spectroscopy studies. JAMA Psychiatry. 2016;73(7):665-674.
  78. Miller ML. Diagnosis and differential diagnosis of dermatomyositis and polymyositis in adults. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed December 2013.
  79. Moriguchi S, Takamiya A, Noda Y, et al. Glutamatergic neurometabolite levels in major depressive disorder: A systematic review and meta-analysis of proton magnetic resonance spectroscopy studies. Mol Psychiatry. 2019;24(7):952-964.
  80. Morrison WB, Dalinka MK, Daffner RH, et al, Expert Panel on Musculoskeletal Imaging. Bone tumors [online publication]. Reston, VA: American College of Radiology (ACR); 2005.
  81. Moser HW, Barker PB. Magnetic resonance spectroscopy: A new guide for the therapy of adrenoleukodystrophy. Neurology. 2005;64(3):406-407.
  82. Mowatt G, Scotland G, Boachie C, et al. The diagnostic accuracy and cost-effectiveness of magnetic resonance spectroscopy and enhanced magnetic resonance imaging techniques in aiding the localisation of prostate abnormalities for biopsy: A systematic review and economic evaluation. Health Technol Assess. 2013;17(20):vii-xix, 1-281.
  83. Mygland A, Ljostad U, Fingerle V, et al.; European Federation of Neurological Societies. EFNS guidelines on the diagnosis and management of European Lyme neuroborreliosis. Eur J Neurol. 2010;17(1):8-16, e1-e4.
  84. National Comprehensive Cancer Network (NCCN). Central nervous system cancers. NCCN Clinical Practice Guidelines in Oncology, version 1.2016. Fort Washington, PA: NCCN; 2016. 
  85. National Horizon Scanning Centre (NHSC). Magnetic resonance spectroscopy for prostate cancer: Horizon scanning technology briefing. Birmingham, UK: NHSC; 2006.
  86. Ng YS, Bindoff LA, Gorman GS, et al. Consensus-based statements for the management of mitochondrial stroke-like episodes. Wellcome Open Res. 2019;4:201.
  87. Nocimed, LLC. NOCISCAN-Lumbar Spine (LS) Clinical Evaluation Study. ClinicalTrials.gov Identifier: NCT04015791. Bethesda, MD: National Library of Medicine; last update August 6, 2019. 
  88. Nurenberg P, Sartoni-D'Ambrosia G, Szczepaniak LS. Magnetic resonance spectroscopy of renal and other retroperitoneal tumors. Curr Opin Urol. 2002;12(5):375-380.
  89. O’Ferrall E. Mitochondrial myopathies: Clinical features and diagnosis. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed December 2021.
  90. Panebianco V, Sciarra A, Marcantonio A, et al. Conventional imaging and multiparametric magnetic resonance (MRI, MRS, DWI, MRP) in the diagnosis of prostate cancer. Q J Nucl Med Mol Imaging. 2012;56(4):331-342.
  91. Rajajee V. Management of acute severe traumatic brain injury. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed November 2018.
  92. Rajesh A, Coakley FV, Kurhanewicz J. 3D MR spectroscopic imaging in the evaluation of prostate cancer. Clin Radiol. 2007;62(10):921-929.
  93. Reddy-Thootkur M, Kraguljac NV, Lahti AC. The role of glutamate and GABA in cognitive dysfunction in schizophrenia and mood disorders -- A systematic review of magnetic resonance spectroscopy studies. Schizophr Res. 2022;249:74-84.
  94. Reyngoudt H, Achten E, Paemeleire K. Magnetic resonance spectroscopy in migraine: What have we learned so far? Cephalalgia. 2012;32(11):845-859.
  95. Ross AJ, Sachdev PS. Magnetic resonance spectroscopy in cognitive research. Brain Res Brain Res Rev. 2004;44(2-3):83-102.
  96. Ryan ME, Palasis S, Saigal G, et al; Expert Panel on Pediatric Imaging. ACR Appropriateness Criteria® head trauma -- child [online publication]. Reston, VA: American College of Radiology (ACR); 2014.
  97. Schmidt M, Crnac J, Dederichs B, et al. Magnetic resonance imaging in valvular heart disease. Int J Card Imaging. 1997;13(3):219-231.
  98. Sciarra A, Panebianco V, Ciccariello M, et al. Value of magnetic resonance spectroscopy imaging and dynamic contrast-enhanced imaging for detecting prostate cancer foci in men with prior negative biopsy. Clin Cancer Res. 2010;16(6):1875-1883.
  99. Scott DL, Kingsley GH. Use of imaging to assess patients with muscle disease. Curr Opin Rheumatol. 2004;16(6):678-683.
  100. Shah N, Sattar A, Benanti M, Hollander S, Cheuck L. Magnetic resonance spectroscopy as an imaging tool for cancer: A review of the literature. J Am Osteopath Assoc. 2006;106(1):23-27
  101. Slanetz PJ. MRI of the breast and emerging technologies. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed December 2013.
  102. Slosman DO, Lazeyras F. Metabolic imaging in the diagnosis of brain tumors. Curr Opin Neurol. 1996;9(6):429-435.
  103. Smartt P. Magnetic resonance spectroscopy for the initial diagnosis and staging of prostate, brain, breast and other cancers: Horizon scanning report. HSAC Report. Christchurch, New Zealand: Health Services Assessment Collaboration (HSAC); 2009;2(8).
  104. Spencer AE, Uchida M, Kenworthy T, et al. Glutamatergic dysregulation in pediatric psychiatric disorders: A systematic review of the magnetic resonance spectroscopy literature. J Clin Psychiatry. 2014;75(11):1226-1241.
  105. Stærmose TG, Knudsen MK, Kasch H, Blicher JU. Cortical GABA in migraine with aura -an ultrashort echo magnetic resonance spectroscopy study. J Headache Pain. 2019;20(1):110.
  106. Steen RG, Hamer RM, Lieberman JA. Et al. Measurement of brain metabolites by 1H magnetic resonance spectroscopy in patients with schizophrenia: A systematic review and meta-analysis. Neuropsychopharmacology. 2005;30(11):1949-1962.
  107. Sturrock A, Laule C, Decolongon J, et al. Magnetic resonance spectroscopy biomarkers in premanifest and early Huntington disease. Neurology. 2010;75(19):1702-1710.
  108. Sullivan T, Merlin T. Magnetic resonance spectroscopy for the diagnosis of suspected breast cancer malignancies. Horizon Scanning Prioritising Summary. Adelaide, SA: Adelaide Health Technology Assessment (AHTA) on behalf of National Horizon Scanning Unit (HealthPACT and MSAC); September 2006;14(3).
  109. Swanberg KM, Campos L, Abdallah CG, Juchem C. Proton magnetic resonance spectroscopy in post-traumatic stress disorder -- Updated systematic review and meta-analysis. Chronic Stress (Thousand Oaks). 2022;6:24705470221128004.
  110. Taylor-Robinson SD. Applications of magnetic resonance spectroscopy to chronic liver disease. Clin Med. 2001;1(1):54-60.
  111. Tse GM, Yeung DK, King AD, et al. In vivo proton magnetic resonance spectroscopy of breast lesions: An update. Breast Cancer Res Treat. 2007;104(3):249-255.
  112. Umbehr M, Bachmann LM, Held U, et al. Combined magnetic resonance imaging and magnetic resonance spectroscopy imaging in the diagnosis of prostate cancer: A systematic review and meta-analysis. Eur Urol. 2009;55(3):575-590.
  113. Ustymowicz A, Tarasow E, Zajkowska J, et al. Proton MR spectroscopy in neuroborreliosis: A preliminary study. Neuroradiology. 2004;46(1):26-30.
  114. Vavilala MS, Tasker RC. Severe traumatic brain injury in children: Initial evaluation and management. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed November 2018.
  115. Vawter-Lee MM, Hallinan BE, Burrow TA, et al. A novel catastrophic presentation of X-linked adrenoleukodystrophy. JIMD Rep. 2015;24:97-102.
  116. Vedolin L, Schwartz IV, Komlos M, et al. Brain MRI in mucopolysaccharidosis: Effect of aging and correlation with biochemical findings. Neurology. 2007;69(9):917-924.
  117. Veeramuthu V, Seow P, Narayanan V, et al. Neurometabolites alteration in the acute phase of mild traumatic brain injury (mTBI): An in vivo proton magnetic resonance spectroscopy (1H-MRS) study. Acad Radiol. 2018;25(9):1167-1177.
  118. Voevodskaya O, Poulakis K, Sundgren P, et al; Swedish BioFINDER Study Group. Brain myoinositol as a potential marker of amyloid-related pathology: A longitudinal study. Neurology. 2019;92(5):e395-e405.
  119. Wang D, Li Y. 1H magnetic resonance spectroscopy predicts hepatocellular carcinoma in a subset of patients with liver cirrhosis: A randomized trial. Medicine (Baltimore). 2015;94(27):e1066.
  120. Wang H, Tan L, Wang HF, et al. Magnetic resonance spectroscopy in Alzheimer's disease: Systematic review and meta-analysis. J Alzheimers Dis. 2015;46(4):1049-1070.
  121. Wang P, Guo YM, Liu M, et al. A meta-analysis of the accuracy of prostate cancer studies which use magnetic resonance spectroscopy as a diagnostic tool. Korean J Radiol. 2008;9(5):432-438.
  122. Wang Q, Zhang H, Zhang J, et al. The diagnostic performance of magnetic resonance spectroscopy in differentiating high-from low-grade gliomas: A systematic review and meta-analysis. Eur Radiol. 2016;26(8):2670-2684.
  123. Wang W, Hu Y, Lu P, et al. Evaluation of the diagnostic performance of magnetic resonance spectroscopy in brain tumors: A systematic review and meta-analysis. PLoS One. 2014;9(11):e112577.
  124. Wein. Campbell-Walsh Urology. Tenth Edition. 2011.
  125. Weinreb JC, Blume JD, Coakley FV, et al. Prostate cancer: Sextant localization at MR imaging and MR spectroscopic imaging before prostatectomy -- results of ACRIN prospective multi-institutional clinicopathologic study. Radiology. 2009;251(1):122-133.
  126. Westphalen AC, et al. Locally recurrent prostate cancer after external beam radiation therapy: Diagnostic performance of 1.5-T endorectal MR imaging and MR spectroscopic imaging for detection. Radiology. 2010;256(2):485-492.
  127. Wetter A, Engl TA, Nadjmabadi D, et al. Combined MRI and MR spectroscopy of the prostate before radical prostatectomy. AJR Am J Roentgenol. 2006;187(3):724-730.
  128. Willmann O, Wennberg R, May T, et al. The role of 1H magnetic resonance spectroscopy in pre-operative evaluation for epilepsy surgery. A meta-analysis. Epilepsy Res. 2006;71(2-3):149-158.
  129. Wippold FJ II, Brown DC, Broderick DF, et al; Expert Panel on Neurologic Imaging. ACR Appropriateness Criteria® dementia and movement disorders [online publication]. Reston, VA: American College of Radiology (ACR); 2014. 
  130. Wong ET, Wu JK. Overview of the clinical features and diagnosis of brain tumors in adults. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed November 2018.
  131. Wormser GP, Dattwyler RJ, Shapiro ED, et al. The clinical assessment, treatment, and prevention of Lyme disease, human granulocytic anaplasmosis, and babesiosis: Clinical practice guidelines by the Infectious Diseases Society of America. Clin Infect Dis. 2006;43(9):1089-1134.
  132. Wu Y. Clinical features, diagnosis, and treatment of neonatal encephalopathy. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed May 2020.
  133. Yang M, Sun J, Bai HX, et al. Diagnostic accuracy of SPECT, PET, and MRS for primary central nervous system lymphoma in HIV patients: A systematic review and meta-analysis. Medicine (Baltimore). 2017;96(19):e6676.
  134. Younis S, Hougaard A, Vestergaard MB, et al. Migraine and magnetic resonance spectroscopy: A systematic review. Curr Opin Neurol. 2017;30(3):246-262.
  135. Yuksel C, Tegin C, O'Connor L, et al. Phosphorus magnetic resonance spectroscopy studies in schizophrenia. J Psychiatr Res. 2015;68:157-166.
  136. Zakian K, et al. Correlation of proton MR spectroscopic imaging with Gleason score based on step-section pathologic analysis after radical prostatectomy. Radiology. 2005;234(3):804-814.
  137. Zapotoczna A, Sasso G, Simpson J, Roach M 3rd. Current role and future perspectives of magnetic resonance spectroscopy in radiation oncology for prostate cancer. Neoplasia. 2007;9(6):455-463.
  138. Zeng G, Penninkilampi R, Chaganti J, et al. Meta-analysis of magnetic resonance spectroscopy in the diagnosis of hepatic encephalopathy.
  139. Zhang H, Ma L, Wang Q, et al. Role of magnetic resonance spectroscopy for the differentiation of recurrent glioma from radiation necrosis: A systematic review and meta-analysis. Eur J Radiol. 2014;83(12):2181-2189.
  140. Zhang L, Li H, Hong P, Zou X. Proton magnetic resonance spectroscopy in juvenile myoclonic epilepsy: A systematic review and meta-analysis. Epilepsy Res. 2016;121:33-38.
  141. Zhao X, Xu M, Jorgenson K, Kong J. Neurochemical changes in patients with chronic low back pain detected by proton magnetic resonance spectroscopy: A systematic review. Neuroimage Clin. 2016;13:33-38.
  142. Zheng D, Guo Z, Schroder PM, et al. Accuracy of MR imaging and MR spectroscopy for detection and quantification of hepatic steatosis in living liver donors: A meta-analysis. Radiology. 2017;282(1):92-102.
  143. Zou R, Xiong T, Zhang L, et al. Proton magnetic resonance spectroscopy biomarkers in neonates with hypoxic-ischemic encephalopathy: A systematic review and meta-analysis. Front Neurol. 2018;9:732.