Bone Mass Measurements

Number: 0134

Table Of Contents

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

Policy

Scope of Policy

This Clinical Policy Bulletin addresses bone mass measurements.

  1. Medical Necessity

    Aetna considers the following interventions medically necessary: 

    1. Bone mass measurement using the established techniques listed below for members who meet any of the following criteria:

      1. Individuals being monitored to assess the response to or efficacy of osteoporosis drug therapy (only dual-energy x-ray absorptiometry for this indication); or
      2. Individuals receiving (or expected to receive) glucocorticoid (steroid) therapy equivalent to 5 mg of prednisone or greater, per day, for more than 3 months; or
      3. Individuals on long-term anticonvulsant therapy (e.g., phenytoin, phenobarbital); or
      4. Individuals on long-term aromatase inhibitor therapy; or
      5. Individuals with celiac sprue; or
      6. Individuals with primary hyperparathyroidism; or
      7. Individuals with vertebral abnormalities as demonstrated by an x-ray to be indicative of osteoporosis, osteopenia, or vertebral fracture; or
      8. Men greater than 50 years of age with specific risk factors for osteoporosis (i.e., low body weight, weight loss, or physical inactivity) (Note: covered for members with preventive services benefits only); or
      9. Men with hypogonadism or receiving androgen deprivation treatment (e.g., leuprolide, histrelin, goserelin); or
      10. Non-traumatic (fragility) fractures; or
      11. Screening of men greater than 70 years of age (Note: covered for members with preventive services benefits only); or
      12. Screening of women who have been determined to be estrogen-deficient (peri- or post-menopausal) (Note: covered for members with preventive services benefits only); or
      13. Women on long-term (i.e., longer than 2 years) Depo-Provera Contraceptive Injection (CI) therapy; or
      14. Women with hyperthyroidism; or
      15. Women with Turner syndrome;

      Repeat bone mass measurements are usually not indicated more frequently than once every 2 years. 

    2. More frequent bone mass measurements in any of the following circumstances:

      1. For a confirmatory baseline bone mass measurement to permit monitoring of individuals in the future if the initial bone mass test was performed with a technique that is different from the proposed testing method; or
      2. Monitoring of individuals on long-term glucocorticoid (steroid) therapy or anticonvulsant therapy of more than 3 months duration; or
      3. Monitoring of individuals with uncorrected primary hyperparathyroidism;

      Repeat bone mass measurement has no proven value for other indications.

    3. Simultaneous axial (central) and appendicular (peripheral) bone mass measurements only in the following limited circumstances:

      1. An axial scan to get a baseline measurement for monitoring if osteoporosis is identified with an appendicular scan; or
      2. Appendicular measurements, when artifacts obscure measurement at the axial skeleton; or 
      3. Member is diagnosed with uncorrected primary hyperparathyroidism;

      Simultaneous axial and appendicular bone mass measurements have no proven value for other indications.

    4. The following methods are established procedures of bone mass measurements of the axial or appendicular (peripheral) skeleton:

      1. Dual energy X-ray absorptiometry (DEXA or DXA);
      2. Quantitative computed tomography (QCT);
      3. Radiographic absorptiometry (photodensitometry);
      4. Single energy X-ray absorptiometry (SEXA);
      5. Ultrasound bone mineral density studies (e.g., Achilles + Bone Sonometer, Sahara, SoundScan);
    5. Vertebral fracture assessment (VFA) with dual energy x-ray absorptiometry (DEXA or DXA) (also known as morphometric x-ray absorptiometry) as an adjunct to bone mineral density measurement to calculate FRAX scores;
    6. Trabecular bone score for evaluation of fracture risk in persons who meet criteria for bone mass measurement above.

  2. Experimental, Investigational, or Unproven

    The following interventions are considered experimental, investigational, or unproven because the effectiveness of these approaches has not been established:

    1. Bone mass measurement for all other indications (e.g., evaluation of osteoporosis/osteoporotic fractures in persons with schizophrenia who are on anti-psychotic medications, and monitoring individuals who are on anti-depressive agents) for indications other than the ones listed; 
    2. Bone mass measurement by dual photon absorptiometry (DPA), dual X-ray and laser (DXL), single photon absorptiometry (SPA), or pulse-echo ultrasound (e.g., Bindex); 
    3. Vertebral fracture assessment (VFA) using any imaging modality other than DEXA;

      Note: Examples of vertebral fracture assessment application packages that have received 510(k) marketing clearance are the Instant Vertebral Assessment (IVA) (Hologic, Inc.) and Dual Energy Vertebral Assessment (DVA) (previously known as Lateral Vertebral Assessment (LVA) (GE Lunar Medical Systems).

    4. Cone beam computed tomography for detection of low bone mass (including evaluation of post-menopausal osteoporosis); 
    5. Finite element analysis for evaluation of fracture risk, rotator cuff, and all other indications (e.g., diagnosis of osteoporosis, guidance to initiate therapy for osteoporosis, and monitoring of therapy) because its clinical value has not been established;
    6. Measurement of advanced glycation end-products (AGEs) by skin auto-fluorescence (SAF) for assessment of fracture risk because its clinical value has not been established;
    7. Radiofrequency echographic multi spectrometry (REMS) for assessment of bone status; 
    8. The use of urinary phthalate as a predictor for fracture risk.

  3. Policy Limitations and Exclusions 

    Note: Aetna considers radiological computer-assisted prioritization / artificial intelligence (AI) software (e.g., HealthVCF) not medically necessary to aid in the identification of vertebral compression fractures during computed tomography (CT) scanning of the chest or abdomen, as the software does not provide diagnostic information beyond triage and prioritization of radiological medical images, and should not be used in place of full member evaluation, or relied upon to make or confirm diagnosis. 

  4. Related Policies

Table:

CPT Codes / HCPCS Codes / ICD-10 Codes
Code Code Description

CPT codes covered if selection criteria are met:
76977 Ultrasound bone density measurement and interpretation, peripheral site(s), any method [not covered for monitoring osteoporosis drug therapy]
77078 Computerized tomography, bone mineral density study, 1 or more sites [not covered for monitoring osteoporosis drug therapy]
77080 - 77081 Dual energy x-ray absorptiometry (DXA), bone density study, 1 or more sites
77085 Dual-energy X-ray absorptiometry (DXA), bone density study, 1 or more sites; axial skeleton (eg, hips, pelvis, spine), including vertebral fracture assessment
77086 Vertebral fracture assessment via dual-energy X-ray absorptiometry (DXA)
77089 Trabecular bone score (TBS), structural condition of the bone microarchitecture; using dual X-ray absorptiometry (DXA) or other imaging data on gray-scale variogram, calculation, with interpretation and report on fracture-risk
77090      technical preparation and transmission of data for analysis to be performed elsewhere
77091      technical calculation only
77092      interpretation and report on fracture-risk only by other qualified health care professional

CPT codes not covered for indications listed in the CPB:
Measurement of advanced glycation end-products by skin auto-fluorescence, Urinary phthalate as a predictor for fracture risk –no specific code
0508T Pulse-echo ultrasound bone density measurement resulting in indicator of axial bone mineral density, tibia
0554T Bone strength and fracture risk using finite element analysis of functional data, and bone-mineral density, utilizing data from a computed tomography scan; retrieval and transmission of the scan data, assessment of bone strength and fracture risk and bone mineral density, interpretation and report
0555T     retrieval and transmission of the scan data
0556T     assessment of bone strength and fracture risk and bone mineral density
0557T     interpretation and report
0691T Automated analysis of an existing computed tomography study for vertebral fracture(s), including assessment of bone density when performed, data preparation, interpretation, and report
0743T Bone strength and fracture risk using finite element analysis of functional data and bone mineral density (BMD), with concurrent vertebral fracture assessment, utilizing data from a computed tomography scan, retrieval and transmission of the scan data, measurement of bone strength and BMD and classification of any vertebral fractures, with overall fracture-risk assessment, interpretation and report
0749T Bone strength and fracture-risk assessment using digital X-ray radiogrammetry-bone mineral density (DXR-BMD) analysis of bone mineral density (BMD) utilizing data from a digital X ray, retrieval and transmission of digital X-ray data, assessment of bone strength and fracture risk and BMD, interpretation and report
0750T Bone strength and fracture-risk assessment using digital X-ray radiogrammetry-bone mineral density (DXR-BMD) analysis of bone mineral density (BMD) utilizing data from a digital X ray, retrieval and transmission of digital X-ray data, assessment of bone strength and fracture risk and BMD, interpretation and report; with single-view digital X-ray examination of the hand taken for the purpose of DXR-BMD
0815T Ultrasound-based radiofrequency echographic multi-spectrometry (REMS), bone-density study and fracture-risk assessment, 1 or more sites, hips, pelvis, or spine
70486 Computed tomography, maxillofacial area; without contrast material [not covered for osteoporosis screening]
70487      with contrast material(s) [Not covered for Cone beam computed tomography]
70488      without contrast material, followed by contrast material(s) and further sections [Not covered for Cone beam computed tomography]
78350 Bone density (bone mineral content) study, one or more sites; single photon absorptiometry
78351 Bone density (bone mineral content) study, one or more sites; dual photon absorptiometry, one or more sites

Other CPT codes related to the CPB:
71250 Computed tomography, thorax, diagnostic; without contrast material
71260 Computed tomography, thorax, diagnostic; with contrast material(s)
74150 Computed tomography, abdomen; without contrast material
74160 Computed tomography, abdomen; with contrast material(s)

HCPCS codes covered if selection criteria are met:
G0130 Single energy x-ray absorptiometry (SEXA) bone density study, one or more sites; appendicular skeleton (peripheral) (e.g., radius, wrist, heel) [not covered for monitoring osteoporosis drug therapy]

Other HCPCS codes related to the CPB:
J1050 Injection, medroxyprogesterone acetate, 1 mg
J1950 Injection, leuprolide acetate (for depot suspension), per 3.75 mg
J9202 Goserelin acetate implant, per 3.6 mg
J9217 Leuprolide acetate (for depot suspension), 7.5 mg
J9218 Leuprolide acetate, per 1 mg
J9219 Leuprolide acetate implant, 65 mg

ICD-10 codes covered if selection criteria are met:
E05.00 - E05.91 Thyrotoxicosis [hyperthyroidism]
E20.0 - E20.9 Hypoparathyroidism
E28.39 Other primary ovarian failure
E29.1 Testicular hypofunction
E34.50 - E34.52 Androgen insensitivity syndrome
G40.001 - G40.919 Epilepsy and recurrent seizures
K90.0 Celiac disease
M80.011A – M80.88XS Osteoporosis with current pathological fracture
M81.0 - M81.8 Osteoporosis without current pathological fracture [not covered for post-menopausal osteoporosis]
M84.411A – M84.48XS Pathologic fracture, not elsewhere classified
M85.80 - M85.9 Other specified disorders of bone density and structure [osteopenia] [Low bone mass]
N92.4 Excessive bleeding in the premenopausal period
N95.0 - N95.9 Menopausal and other perimenopausal disorders
Q96.0 - Q96.9 Turner's Syndrome
R56.1 Post traumatic seizures
R56.9 Unspecified convulsions
S12.000A – S12.9XXS Fracture of cervical vertebra and other parts of the neck
S22.000A – S22.089S Fracture of thoracic vertebra
S32.000A – S32.059S Fracture of lumbar vertebra
S32.10XA – S32.19XS Fracture of sacrum
S32.2XXA – S32.2XXS Fracture of coccyx
Z13.820 Encounter for screening for osteoporosis
Z78.0 Asymptomatic postmenopausal state
Z79.51 - Z79.52 Long term (current) use of steroids [glucocorticoid therapy]
Z79.811 Long term (current) use of aromatase inhibitors
Z79.890 Hormone replacement therapy (postmenopausal)
Z79.899 Other long term (current) drug therapy [covered for individuals on long-term anticonvulsant therapy only]

ICD-10 codes not covered for indications listed in the CPB:
F20.0 - F20.9 Schizophrenia
F32.0 – F33.9 Major depressive disorders [monitoring individuals who are on anti-depressive agents]
I12.0 - I12.9 Hypertensive chronic kidney disease
I13.0 - I13.2 Hypertensive heart and chronic kidney disease
N18.1 - N18.9 Chronic kidney disease (CKD)
Q60.0 - Q60.6 Renal agenesis and other reduction defects of kidney [congenital]
Q61.00 - Q61.9 Cystic kidney diseases [congenital]
Z13.828 Encounter for screening for other musculoskeletal disorder [assessment of bone status]

Background

This policy is adapted from guidelines for bone mineral density (BMD) screening from the Centers for Medicare and Medicaid Services, National Institutes of Health, the American Association of Clinical Endocrinologists, and the American Gastroenterological Association.

Osteoporosis is a cause of significant morbidity and mortality in men as well as post-menopausal women.  It is a disease characterized by low bone density and increased bone fragility, which reduce bone strength.  Post-menopausal osteoporosis is due to rapid bone loss that occurs with the decline in endogenous estrogen following menopause.  However, in both men and women, increasing age and low BMD are 2 important independent risk factors for an initial vertebral or non-vertebral fracture.  While the incidence of vertebral fracture increases with age, the increase is greater among women than men; however, mortality after fracture is higher among men.  According to the literature, the diagnostic criteria for post-menopausal osteoporosis in women are well established; however, there is ongoing debate about the appropriate T-scores and BMD thresholds to diagnose osteoporosis in men (Bonnick, 2006).

Primary osteoporosis is an aged-related disease characterized by low bone mass, microarchitectural deterioration of bone tissue leading to enhanced bone fragility, and a consequent increase in fracture risk in the absence of other recognizable causes of bone loss.  Present intervention efforts are directed largely at identifying those peri-menopausal women who are the most likely to be at risk for future fracture, and providing preventive bisphosphonate therapy along with adequate calcium intake and weight bearing exercise.  Secondary osteoporosis has an identifiable cause of bone loss.  Many, but not all, patients receiving long-term therapy with glucocorticoids have rapid loss of bone; those who do, need to be identified for consideration of medication adjustments.  Bone mass also is reduced in some patients with asymptomatic primary hyper-parathyroidism, that has been diagnosed as a result of multi-phasic screening tests.  Whether these latter patients undergo parathyroidectomy may depend on there being a progressive loss of bone, presumed to be parathyroid hormone-dependent, and treatable by correction of the hyper-parathyroidism.  Lastly, since not all patients with vertebral abnormalities have significant osteoporosis, identifying those who do, enables the costs and risks of follow-up and therapy to be directed and limited to those that require more extensive intervention.

Bone mass loss has also been associated with long-term (i.e., longer than 2 years) use of Depo-Provera Contraceptive Injection (CI) therapy.  Depo-Provera CI therapy is indicated for the prevention of pregnancy.  It reduces serum estrogen levels and is associated with significant loss of BMD as bone metabolism accommodates to a lower estrogen level.  According to the prescribing information for Depo-Provera, BMD should be evaluated when a woman needs to continue to use Depo-Provera CI long-term (i.e., longer than 2 years).  This loss of BMD is of particular concern during adolescence and early adulthood, a critical period of bone accretion.  It is unknown if use of Depo-Provera CI by younger women will reduce peak bone mass and increase the risk for osteoporotic fracture in later life.  In both adults and adolescents, the decrease in BMD appears to be at least partially reversible after Depo-Provera CI is discontinued and ovarian estrogen production increases (Pfizer, Inc., 2006).

The rationale for densitometry lies in the assumption that the strength or resistance of a bone to fracture is closely related to the mass of the mineral present in the bone; the lower the bone density, the greater the fracture risk.  Although BMD can be measured by some multi-purpose imaging devices such as quantitative computed tomography (QCT) scanners, specific densitometry tests emit lower radiation and cost less.  Single-photon absorptiometry (SPA), dual-photon absorptiometry (DPA), and dual-energy radiographic (x-ray) absorptiometry, (DEXA, DXA, DER, DRA) all calculate bone mass on the basis of tissue absorption of photons derived from either a radionuclide or an x-ray tube.

In the past, SPA and DPA were the most commonly used methods of measurement.  These methods have largely been replaced by DEXA.  Single-photon absorptiometry measures the distal third of the radius which is composed mainly of cortical bone whereas most non-traumatic fractures occur in the axial skeleton (spine) and proximal femur (hip), which have a significant amount of trabecular bone.  Measuring trabecular bone mass in the ultradistal radius or calcaneus (heel) has been more difficult because of bone tapering and irregularities.

Dual photon absorptiometry measures trabecular bone but costs more, takes longer, and the patient must lie down; apparent changes in serial DPA results must be carefully interpreted because the aging of the Gd-153 source can result in an apparent increase in bone mineral content.  

Dual-energy radiographic (x-ray) absorptiometry, available since 1987, is the current standard of care for bone mass measurement.  It uses an x-ray tube, instead of an isotope to generate dual energy photons, resulting in higher image resolution and greater speed than DPA. DEXA has replaced DPA; previous DPA manufacturers have switched to producing DEXA scanners.

Some authorities have advocated annual bone mineral density screening.  The International Society for Clinical Densitometry, an association of providers with an interest in bone density measurement, recommends annual testing to detect continued bone loss in patients receiving treatment.  The position statement included a series of recommendations, but did not provide analysis to support these recommendations.  In addition, the American College of Radiology has recommended annual testing in patients receiving treatment.

However, the clinical literature on the accuracy and precision of bone density measurement does not support a recommendation for annual screening.  Erlichman and Holohan (1996) reviewed the literature on commonly used bone densitometry techniques, including DEXA.  They found that, although reviews of recent studies report DEXA accuracy error from 3 to 6 %, other data indicate that DEXA accuracy error of ashed bone specimens of 9 %.  (Measurements obtained by densitometers are compared with an independent standard measurement of bone mass, such as ashed bone sections.  The accuracy error is determined by how much the measurement varies from this accepted or "true" value.)

Dual-energy radiographic (x-ray) absorptiometry scans of the femur have a precision error from 0.5 % to 3 %.  Precision error is the variability in the measurements occurring with repeated measurements of the same object.  A technique's precision is critical for serial measurements that correctly document bone loss over time.  Factors such as patient positioning, calibration and standardization procedures, and differences in operator technique can result in large measurement variations.  The precision of measurements is reduced outside of the controlled conditions of a clinical trial setting.

The requisite minimum intervals between measurements that are necessary to reliably detect a reduction in bone mass are related to the precision attainable with current instruments and the rate of bone mass loss, assuming that the accuracy of the instrument is invariable.  If one assumed a 1 % precision error, an annual rate of bone loss of 3 % would be required to reliably detect bone mass loss after 1 year.

But Erlichman and Holohan (1996) explained that it is unlikely that yearly densitometry would be clinically indicated given the fact that 1 % precision error is rarely attained and that a 3 % annual loss in bone mass would be distinctly uncommon.  Precision errors in the range of 2 to 3 % and annual bone mass losses of 1 to 2 % are parameters more representative of published data.  In those instances, the minimum interval between densitometry measures necessary to document bone mass loss would be between 3.7 and 6 years.

Furthermore, there are no clinical data that demonstrate improved outcomes in osteoporosis patients who are screened annually.  Clinical trials of the bisphosphonate alendronates for the treatment of osteoporosis have found that failure to respond to therapy is a rare event.

A clinical practice guideline on osteoporosis in men issued by the American College of Physicians (ACP) (Qaseem et al, 2008) recommended that physicians periodically assess elderly men for risk factors for osteoporosis.  Although osteoporosis is often viewed as a disease of women, studies show that osteoporotic factures in men are associated with significant morbidity and mortality, resulting in substantial disease burden, death, and healthcare costs.  The prevalence of osteoporosis is estimated to be 7 % in white men, 5 % in black men, and 3 % in Hispanic men.  Data on prevalence of osteoporosis in Asian-American men and other ethnic groups are lacking.  The guideline recommended that clinicians assess risk factors for osteoporosis in older men and obtain a DXA scan for men at increased risk for osteoporosis who are candidates for drug therapy.  Risk factors for osteoporosis in men include age greater than 70 years, low body weight (body mass index [BMI] less than 20 to 25 kg/m2 or lower), weight loss (greater than 10 %), lack of regular physical activity, such as walking, climbing stairs, carrying weights, housework, or gardening, use of oral corticosteroids, previous osteoporotic fracture, and androgen deprivation therapy.  The ACP also recommended further research to evaluate osteoporosis screening tests in men and that, presently, non-DXA tests are either "too insensitive or have insufficient data to reach conclusions."

Metabolic bone diseases that fall under the generic term "renal osteodystrophy" represent abnormal development of bone and major long-term complications in end-stage renal disease.  Chronic kidney disease (CKD) is associated with an increased risk of fracture.  Decreased bone mass and disruption of micro-architecture occur early in the course of CKD and worsens with the progressive decline in renal function so that at the time of initiation of dialysis at least 50 % of patients have had a fracture.  Despite the excess fracture risk, and the associated increases in morbidity and mortality, little is known about the factors that are associated with an increase in fracture risk; and the utility of bone mass measurements in patients with CKD is unclear.  Jamal (2010) reviewed the epidemiology and etiology of fractures in patients with CKD; and summarized published data that described the association between bone mass measurements and fracture in patients with CKD.  Patients with CKD suffer from fractures due to impairments in bone quantity, bone quality, as well as abnormalities of neuromuscular function.  The complex etiology of fractures combined with the technical limitations of BMD testing, both by DEXA and by peripheral QCT, limits the clinical utility of bone mass measurements for fracture prediction in CKD; this is particularly true among patients with stages 4 and 5 CKD.  As such, clinicians should not routinely order BMD testing in patients with CKD.  The author concluded that further research, to ascertain if BMD together with other non-invasive measures to assess bone strength can predict fracture, is needed.

The conclusions of this assessment are consistent with those of an earlier assessment of BMD testing for renal disease prepared by the Agency for Health Care Policy and Research (Ehrlichman and Holohan, 1996), which concluded that BMD measurements are not able to differentiate uremic bone diseases or predict fracture risk in patients with renal osteodystrophy.  As a result, BMD measurements currently do not provide useful information that could support therapeutic decisions in the management of these patients.

The U.S. Preventive Services Task Force updated its 2002 recommendation on screening for osteoporosis (USPSTF, 2011).  The USPSTF evaluated evidence on the diagnostic accuracy of risk assessment instruments for osteoporosis and fractures, the performance of DEXA and peripheral bone measurement tests in predicting fractures, the harms of screening for osteoporosis, and the benefits and harms of drug therapy for osteoporosis in women and men.  The USPSTF recommends screening for osteoporosis in women aged 65 years or older and in younger women whose fracture risk is equal to or greater than that of a 65-year old white woman who has no additional risk factors (Grade B recommendation).  The USPSTF concluded that the current evidence is insufficient to assess the balance of benefits and harms of screening for osteoporosis in men.

The European Association of Urology’s guidelines on "Male hypogonadism" (Dohle et al, 2012) states that "In men with an abnormal BMD, BMD measurements should be repeated 6 and 12 months after the start of TRT [testosterone replacement therapy] and thereafter annually".  (Level of evidence: 4 [Evidence obtained from expert committee reports or opinions or clinical experience of respected authorities]; Grade of recommendation: C [Made despite the absence of directly applicable clinical studies of good quality]).

The Clinical Practice Guidelines for the Care of Girls and Women with Turner Syndrome (Gravholt, et al., 2017) recommends a DEXA scan every 5 years due to the increased risk of osteoporosis in these patients.

Dual X-ray and laser (DXL) is a technique that is currently being examined as a means for bone mass measurement.  This approach employs 2 X-ray beams in conjunction with a laser.  This technique supposedly has the advantage of filtering out any influence that adipose tissue inside and outside the bone may have on the accuracy of DXA measurements; DXL has been studied mainly on the heel.

Kullenberg and Falch (2003) compared the prevalence of osteoporosis (using a T-score threshold of -2.5 for heel measurements) by DXL technology with that obtained by DXA measurements at the femoral neck, spine and forearm.   The prevalence of osteoporosis for women aged 50 years or older was 28 % for DXL measurements of the heel bone and 30, 22 and 32 % for DXA measurements of the lumbar spine, femoral neck and forearm, respectively.  Bone mineral density was also measured by DXL in the heel bone and by DXA in spine and femoral neck in 251 women (mean age of 62 +/- 14.5 years) when attending an osteoporosis clinic.  The sensitivity and specificity for osteoporosis and osteopenia for the DXL measurements were calculated assuming a low T-score at the spine or femoral neck as the criterion for a correct diagnosis.  The sensitivity was found to be 80 % for osteoporosis and 82 % for osteopenia and the specificity was 82 % for osteoporosis and 89 % for osteopenia.  The authors concluded that DXL measurement at the heel bone, using a T-score threshold of -2.5 for classification of osteoporosis, is in concordance with the World Health Organization (WHO) definition of osteoporosis.

Martini et al (2004) evaluated the reproducibility and the diagnostic accuracy of a new device for the assessment of BMD of the heel (DXL Calscan).  This technique associates X-ray absorptiometry to the measure of heel thickness with a laser beam.  The calcaneus BMD, calcaneus quantitative sonography (QUS), and lumbar spine and total-body BMD, were evaluated in 40 post-menopausal women.  On the basis of the BMD T-score measured by DXA of L2 to L4, 20 women were classified as osteoporotic and 20 women were considered non-osteoporotic according to the WHO classification.  The short-term coefficient of variation of the DXL was 2.4 % and 1.7 % in osteoporotic and non-osteoporotic women, respectively.  The calcaneus BMD was lower in osteoporotic than in non-osteoporotic women.  Among osteoporotic patients, 14 patients had a T-score lower than -2.5 at Calscan, whereas only 4 patients classified as non-osteoporotic based on the lumbar spine BMD were mis-classified by Calscan.  In these patients, the sensitivity and specificity of heel ultrasound measurements were 70 % and 85 %, respectively.  The DXL BMD was highly correlated with the total-body BMD, Stiffness at the calcaneus, and the L2 to L4 BMD.  The authors concluded that the Calscan DXL appeared easy to use; the time of examination was relatively short; the reproducibility was sufficiently good; and the diagnostic accuracy and relationships with other devices were good.

Salminen and colleagues (2005) examined the relationship between calcaneal and axial BMD in an elderly female population.  These researchers also investigated the influence of changing the reference populations on T-score values.  Bone mineral density was determined in 388 women (mean age of 73 years) participating in a cross-sectional study.  BMD values were determined at the left hip and the lumbar spine, L1 to L4, using Hologic QDR 4500 equipment for DXA.  The calcaneal measurements were made with DEXA-T, a device using a DXL technique that combines DXA measurement with measurement of the heel thickness using a laser reflection technique.  DEXA-T is an older version of the Calscan DXL device now commercially available.  T-score values were calculated for hip measurements with both the original reference population of the Hologic device and the NHANES III reference population. T-scores for heel measurements were calculated with the original reference population of the peripheral device and the Calscan database, a new calcaneal reference population.  Changing the reference populations had a great influence on both the heel and the hip T scores, especially those of the femoral neck where the percentage of subjects identified as osteoporotic decreased from 53 % to 23 %.  The authors concluded that, with the NHANES III and the larger Calscan database, using the cut-off point of -2.5 standard deviation (SD), the heel measurements had optimal accuracy for detecting osteoporosis at either the combination of the lumbar spine and the femoral neck or the combination of the lumbar spine, the femoral neck, the total hip and the trochanter.  BMD measurements of the calcaneus with DXL correlated fairly well with measurements at axial sites at the group level, while in individual subjects large deviations were observed between all the measured sites.  They also stated that the influence of the reference populations on the T-scores is substantial when different DXA methods are being compared; the total number of subjects classified as osteoporotic varied from 7 % to 53 % between the sites and with different reference populations.

de Klerk et al (2009) compared BMD expressed in T-scores measured by DXA and DXL (Calscan).  The aim of this study was to define threshold T-scores on the Calscan that could exclude or predict osteoporosis correctly in comparison with DXA.  Patients 50 years of age or older attending the emergency department with a fracture were offered osteoporosis screening and enrolled in this study.  BMD was measured at the hip and spine using DXA and at the calcaneus using Calscan.  A T-score measured by DXA less than or equal to -2 SD below the reference population was defined as manifest osteoporosis and was the treatment threshold.  During a 10-month study period, 182 patients were screened with both devices. The mean DXA-T-score was -1.63 SD (range of -4.9 to 2.1) and Calscan T-score -1.91 SD (range of -5.3 to 1.4).  There was a significant correlation between both devices (r = 0.47, p < 0.01). Using an upper threshold for the Calscan T-score of -1.3 SD, 47 patients could be classified as non-osteoporotic with 89.3 % sensitivity (95 % confidence intervals [CI]: 80.0 to 95.3 %). Using a lower threshold for the Calscan T-score of -2.9 SD, 34 patients could be classified by the Calscan as osteoporotic with 90.7 % specificity (95 % CI: 83.5 to 95.4).  The remaining 101 patients could only be correctly classified by DXA-T-scores.  The authors concluded that although DXA is the established modality worldwide in measuring BMD it is restricted to specialized centers.  Peripheral bone densitometers like the Calscan are widely available.  When BMD measurements with DXA were compared to Calscan measurements it was possible to correctly classify 81 of 182 patients based on the Calscan T-score.  Of these 81 patients 34 could be classified as manifest osteoporotic and 47 as non-osteoporotic.  Thus, the authors concluded that Calscan seems to be a promising technique that might be used as a screening device, especially when DXA is not easily available.

Yumru et al (2009) compared DXL heel measurements of BMD and DEXA total hip and lumbar spine BMD measurements for their ability to detect osteoporosis and osteopenia according to WHO criteria.  The study included 164 women aged 40 to 83 years.  DXL heel measurements were recorded for all patients and 89 of the women underwent DEXA.  For DXL heel measurements/DEXA lumbar spine measurements, the relative sensitivity was 50 %, relative specificity was 97 % and relative reliability (Kappa score) was 0.55 for osteoporosis detection. For detecting osteoporosis or osteopenia, the relative sensitivity increased to 86 % but the relative specificity reduced to 38 % and the relative reliability was considerably lower (Kappa score 0.21).  The authors concluded that although previous studies have shown DXL heel measurement to be a good technique in the diagnosis and assessment of osteoporosis based on BMD, particularly for fast, cost-effective bone scanning, they suggested that there are currently insufficient data to prove its use as a standard measurement technique for BMD.

In a systematic review for an American College of Physicians (ACP)’s guideline on "Screening for osteoporosis in men" (Liu et al, 2008) evaluated:

  1. risk factors for osteoporotic fracture in men that may be mediated through low BMD, and
  2. the performance of non-DXA tests in identifying men with low BMD. 

Studies identified through the MEDLINE database (1990 to July 2007) were included for analysis.  Articles that assessed risk factors for osteoporotic fracture in men or evaluated a non-DXA screening test against a gold standard of DXA were selected.  Researchers performed independent dual abstractions for each article, determined performance characteristics of screening tests, and assessed the quality of included articles.  A published meta-analysis of 167 studies evaluating risk factors for low BMD-related fracture in men and women found high-risk factors to be increased age (greater than 70 years), low body weight (BMI less than 20 to 25 kg/m2), weight loss (greater than 10 %), physical inactivity, prolonged corticosteroid use, and previous osteoporotic fracture.  An additional 102 studies assessing 15 other proposed risk factors were reviewed; most had insufficient evidence in men to draw conclusions.  Twenty diagnostic study articles were reviewed.  At a T-score threshold of -1.0, calcaneal ultrasonography had a sensitivity of 75 % and specificity of 66 % for identifying DXA-determined osteoporosis (DXA T-score, -2.5).  At a risk score threshold of -1, the Osteoporosis Self-Assessment Screening Tool had a sensitivity of 81 % and specificity of 68 % to identify DXA-determined osteoporosis.  The authors concluded that key risk factors for low BMD-mediated fracture include increased age, low body weight, weight loss, physical inactivity, prolonged corticosteroid use, previous osteoporotic fracture, and androgen deprivation therapy.  Moreover, they stated that non-DXA tests either are too insensitive or have insufficient data to reach conclusions.

Indeed, the AAP’s clinical practice guideline on "Screening for osteoporosis in men" (Qaseem et al, 2008) recommended that clinicians obtain dual-energy x-ray absorptiometry for men who are at increased risk for osteoporosis and are candidates for drug therapy.  Furthermore, UpToDate reviews on "Screening for osteoporosis" (Kleerekoper, 2012) and "Osteoporotic fracture risk assessment" (Lewiecki, 2012) mentioned the use of dual energy x-ray absorptiometry, but not DXL.

Wren et al (2014) noted that early assessment of bone mass may be useful for predicting future osteoporosis risk if bone measures "track" during growth.  This prospective, longitudinal, multi-center study examined tracking of bone measures in children and adolescents over 6 years to sexual and skeletal maturity.  A total of 240 healthy male and 293 healthy female patients, aged 6 to 17 years, underwent yearly evaluations of height, weight, BMI, skeletal age, Tanner stage, and DEXA bone measurements of the whole body, spine, hip, and forearm for 6 years.  All subjects were sexually and skeletally mature at final follow-up.  Correlation was performed between baseline and 6-year follow-up measures, and change in DEXA Z-scores was examined for subjects who had baseline Z less than -1.5.  DEXA Z-scores (r = 0.66 to 0.87) had similar tracking to anthropometric measures (r = 0.6 to -0.74).  Tracking was stronger for BMD compared with bone mineral content and for girls compared with boys.  Tracking was weakest during mid- to late-puberty but improved when Z-scores were adjusted for height.  Almost all subjects with baseline Z less than -1.5 had final Z-scores below average, with the majority remaining less than -1.0.  The authors concluded that bone status during childhood is a strong predictor of bone status in young adulthood, when peak bone mass is achieved.  They stated that these findings suggested that bone mass measurements in children and adolescents may be useful for early identification of individuals at risk for osteoporosis later in life.

In a pilot study, Aubry-Rozier et al (2014) compared vertebral fracture assessments (VFA) and lateral X-rays in terms of inter- and intra-observer reliability and degree of correlation for the detection of syndesmophytes in ankylosing spondylitis (AS).  These researchers recruited 19 patients with AS and recent lumbar or cervical lateral X-rays with at least 1 syndesmophyte.  Each patient underwent DEXA with measurement of BMD and dorso-lumbar VFA.  Intra- and inter-reader reliability for VFA and X-rays were measured using 2 independent, blinded observers and Cohen's kappa values.  An adapted modified Stoke Ankylosing Spondylitis Spinal Score (amSASSS) was generated with each method, and these 2 values correlated.  For X-rays, intra-observer and inter-observer agreement were 94.3 % (κ = 0.83) and 98.6 % (κ = 0.96), respectively; for VFA, corresponding values were 92.8 % (κ = 0.79) and 93.8 % (κ = 0.82).  Overall agreement between the 2 techniques was 88.6 % (κ = 0.72).  The Pearson correlation coefficient for the 2 methods was 0.95 for the modified Stoke Ankylosing Spondylitis Spinal Score.  Per DEXA-generated BMD, greater than 50 % of patients were osteopenic and 10 % osteoporotic.  The authors concluded that in terms of reproducibility and correlation with X-rays, performing a VFA appeared to be a candidate for assessing radiographic damage in AS, thought further research is needed to justify this indication.

In January 2018, the American Medical Association (AMA) issued a new Category III CPT code for Bindex measurement. Bindex is a hand-held, portable pulse‑echo ultrasound device that can be used to help diagnose osteoporosis. Unlike other quantitative ultrasound that measures sound speed and attenuation in the heel, Bindex measures the cortical bone thickness of the tibia and the algorithm calculates the Density Index, a parameter which estimates bone mineral density at the hip as measured with DXA. Bindex detects osteoporosis with 90% sensitivity and specificity compared with axial dual‑energy X‑ray absorptiometry (DXA). Bindex can be connected to and used with any laptop or desktop computer's USB socket.

Bindex is intended to be used alongside current algorithmic fracture risk assessment tools (FRAX or QFracture). If these suggest an intermediate or high risk of osteoporosis fracture, Bindex could be used to determine whether referral for DXA scan is needed (in the case of confirmed intermediate risk) or not (if low risk). Treatment could be considered for those at high fracture risk or high risk for osteoporosis as measured with Bindex.

The evidence comes from two studies including 1,127 participants recruited in the USA and Finland. The studies show reasonable agreement for osteoporosis risk when determined in women with intermediate risk using FRAX and Bindex compared with FRAX and DXA. One study (Karjalainen et al. 2016) examined the association between dual‑energy X‑ray absorptiometry (DXA) measurements at the proximal femur and Bindex (measured at the tibia), using a diagnostic threshold for the density index based on International Society for Clinical Densitometry (ISCD) and National Osteoporosis Society guidelines. The study by Schousboe et al. (2017) estimated the diagnostic accuracy of Bindex using the threshold density index from the Karjalainen et al. (2016) study.

Karjalainen et al (2016) stated that due to the lack of diagnostics in primary health care, over 75% of osteoporotic patients are not diagnosed. A new ultrasound method for primary health care is proposed. Results suggest applicability of ultrasound method for osteoporosis diagnostics at primary health care. There is a lack of effective screening and diagnostics of osteoporosis at primary health care. In this study, a new ultrasound (US) method is proposed for osteoporosis diagnostics. A total of 572 Caucasian women (age 20 to 91 years) were examined using pulse-echo US measurements in the tibia and radius. This method provides an estimate of bone mineral density (BMD), i.e. density index (DI). Areal BMD measurements at the femoral neck (BMD(neck)) and total hip (BMD(total)) were determined by using axial dual-energy X-ray absorptiometry (DXA) for women older than 50 years of age (n = 445, age = 68.8 ± 8.5 years). The osteoporosis thresholds for the DI were determined according to the International Society for Clinical Densitometry (ISCD). Finally, the FRAX questionnaire was completed by 425 participants. Osteoporosis was diagnosed in individuals with a T-score -2.5 or less in the total hip or femoral neck (n = 75). By using the ISCD approach for the DI, only 28.7% of the subjects were found to require an additional DXA measurement. These results suggest that combination of US measurement and FRAX in osteoporosis management pathways would decrease the number of DXA measurements to 16% and the same treatment decisions would be reached at 85.4% sensitivity and 78.5% specificity levels. The authors concluded that the present results demonstrate a significant correlation between the ultrasound and DXA measurements at the proximal femur. The thresholds presented here with the application to current osteoporosis management pathways show promise for the technique to significantly decrease the amount of DXA referrals and increase diagnostic coverage; however, these results need to be confirmed in future studies.

Schousboe et al (2017) stated pulse-echo ultrasonometry can be used as a pre-screen for hip osteoporosis before dual-energy x-ray absorptiometry (DXA), potentially allowing DXA to be avoided for the majority of post-menopausal women. Pulse-echo ultrasound measures of tibia cortical thickness are also associated with radiographically confirmed prior fractures, independent of femoral neck bone mineral density. The aim of this trial was to estimate how well a pulse-echo ultrasound device discriminates those who have from those who do not have hip osteoporosis (femoral neck bone mineral density [BMD] or total hip BMD T-score ≤ -2.5), and to estimate the association of pulse-echo ultrasound measures with prevalent (radiographically confirmed) clinical fractures. Five hundred fifty-five post-menopausal women age 50 to 89 had femoral neck and total hip BMD measured by dual-energy x-ray absorptiometry (DXA), and pulse-echo ultrasound measures of distal radius, proximal tibia, distal tibia cortical thickness, and multi- and single-site density indices (DI). Using previously published threshold ultrasound values, the authors estimated the proportion of women who would avoid a follow-up DXA after pulse-echo ultrasonometry, and the sensitivity and specificity of this for the detection of hip osteoporosis. Logistic regression models were used to estimate the associations of pulse-echo ultrasound measures with radiographically confirmed clinical fractures within the prior 5 years. Using multi-site and single-site DI measures, follow-up DXA could be avoided for 73 and 69 % of individuals, respectively, while detecting hip osteoporosis with 80-82 % sensitivity and 81 % specificity. Radiographically confirmed prior fracture was associated with ultrasound measures of single-site DI (odds ratio (OR) 1.55, 95 % CI. 1.06 to 2.26) and proximal tibia cortical thickness (OR 1.47, 95 % CI 1.10 to 1.96), adjusted for age, body mass index, and femoral neck BMD. The authors concluded that pulse-echo ultrasonometry can be used as an initial screening test for hip osteoporosis. Prospective studies of how well pulse-echo ultrasound measures predict subsequent clinical fractures are warranted.

A medical technology innovation briefing by the National Institute for Health and Clinical Excellence (NICE, 2017) noted that there are no prospective studies showing the effect of Bindex on the need for DXA scans, and limited data on the correlation between tibial bone thickness and femoral bone mineral density (citing Karjalainen et al (2016) and Schousboe et al (2017)). Also, the Bindex density index threshold values are only validated in women of white European family origin, which may limit the generalizability of the results. There are no nationally recognized or U.S. governmental position statements or practice guidelines that address the use of pulse-echo ultrasound to determine osteoporosis risk or for screening.

Bone Mass Measurement for Individuals on Anti-Depressive Agents

Ham and co-workers (2017) stated that longitudinal studies showed conflicting results regarding the association between use of selective serotonin reuptake inhibitors (SSRIs) and BMD.  These investigators examined the association between duration of SSRI use and BMD, and change in BMD ([INCREMENT]BMD).  Data from the population-based Rotterdam Study cohort (1991 to 2008) were used.  In total, 4,915 men and 5,831 post-menopausal women, aged 45 years and older, were included, having measurement visits at 4- to 5-year intervals.  Multi-variable linear mixed models were applied to examine the association between SSRI use, based on pharmacy records, duration of SSRI use, and repeated measures of BMD, and changes in BMD, compared with non-use.  Femoral neck BMD (grams per centimeters squared) was measured at 4 visits, comprising 19,861 BMD measurements; 3 [INCREMENT]BMD periods were examined, comprising 7,897 [INCREMENT]BMD values.  Change in BMD was expressed in the annual percentage [INCREMENT]BMD between 2 consecutive visits.  In men and women, these researchers observed no association between SSRI and BMD when compared with non-use (women: mean difference [MD], 0.007 g/cm2; 95 % CI: -0.002 to 0.017; p = 0.123).  These investigators did not find an association between duration of SSRI use and [INCREMENT]BMD (women: annual percentage change, -0.081; 95 % CI:, -0.196 to 0.033; p = 0.164).  The authors concluded that use of SSRIs was not associated with BMD or [INCREMENT]BMD, after taking duration of treatment into account, in middle-aged and elderly individuals.  Thus, these findings questioned previously raised concerns on the adverse effects of SSRIs on BMD.

Schweiger and colleagues (2018) noted that anti-depressive agents are one of the fastest-growing classes of prescribed drugs.  However, the effects of anti-depressive agents on bone density are controversial.  In a meta-analysis, these investigators evaluated the state of research on the relationship between the use of tricyclic antidepressants (TCAs) or SSRIs and BMD in women.  The database searched was PubMed.  The meta-analysis included human studies in women fulfilling the following criteria: an assessment of BMD in the lumbar spine, the femoral neck or the total hip; a comparison of the BMD of depressed individuals using anti-depressive agents (SSRIs or TCAs), and a control group that did not use anti-depressive agents; measurement of BMD using DXA; and calculations of the mean BMD and SD or standard error (SE).  A total of 4 studies were identified, which included 934 women using anti-depressive agents and 5,767 non-using individuals.  The results showed that no significant negative composite weighted mean effect sizes were identified for the comparisons between SSRI users and non-users.  Similarly, no significant negative composite weighted mean effect sizes were identified for the comparisons between TCA users and non-users, indicating similar BMD in SSRI or TCA users and non-users.  The authors concluded that the findings of this meta-analysis showed that the association between anti-depressant medication and BMD has not been extensively researched.  Only 4studies fulfilled the inclusion criteria.  The global result of the literature review and meta-analysis was that the use of anti-depressive agents was not associated with lower or higher BMD.  This result applied to both SSRIs and TCAs and to all measurement locations (lumbar spine, femoral neck and total hip).  Moreover, the se researchers stated that given the high prevalence of anti-depressive agent use, there is a need for prospective cohort studies with linkage to prescription registries as well as controlled trials in populations that are well characterized in terms of depressive disorder, BMD and intensity of exposure to anti-depressive agents.  Such studies should include a broader spectrum of age groups.  It may be useful to study the effects of anti-depressant agents on bone micro-architecture using high-resolution peripheral quantitative computed tomography (HR-pQCT), which allows assessment of parameters of bone strength independent of BMD.

In a systematic review and meta-analysis, Zhou and associates (2018) examined the effect of SSRI medication on BMD.  These investigators searched PubMed, Scopus, ISI Web of Knowledge, the Cochrane Library, and PsycINFO for all English-written studies examining the effects of SSRIs on BMD and published before November 2017; BMD was compared between non-SSRI users and SSRI users using a random-effect model with standardized mean differences (SMD) and 95 % CIs.  Furthermore, sub-group analyses were performed based on study design, age, and sex in order to find the origins of high heterogeneity.  A total of 11 studies met the inclusion criteria and were used for the meta-analysis.  This study demonstrated that the use of SSRIs was significantly associated with lower BMD values (SMD - 0.40; 95 % CI: - 0.79 to 0.00; p = 0.05) and BMD Z-scores (SMD - 0.28; 95 % CI: - 0.50 to - 0.05; p = 0.02) of the lumbar spine, but not of the total hip and femoral neck.  In addition, SSRI use was associated with a greater bone loss in the elderly.  The authors concluded that SSRI use is a risk factor of lower BMD of the lumbar spine, especially for the elderly.  Moreover, they stated that future studies into the relationship between SSRI use and bone metabolism and bone mass need to be conducted with larger sample sizes for both men and women at different bone sites.

Bone Mass Measurement for Individuals with Spinal Cord Injury

Soleyman-Jahi and colleagues (2018) noted that spinal cord injury (SCI) results in accelerated BMD loss and disorganization of trabecular bone architecture.  The mechanisms underlying post-SCI osteoporosis are complex and different from other types of osteoporosis.  Findings of studies investigating efficacy of pharmacological or rehabilitative interventions in SCI-related osteoporosis are controversial.  These investigators reviewed the literature pertaining to prevention and evidence-based treatments of SCI-related osteoporosis.  In this systematic review, Medline, Embase, PubMed, and the Cochrane Library were used to identify papers from 1946 to December 31, 2015.  The search strategy involved the following keywords: spinal cord injury, osteoporosis, and bone loss.  A total of 56 studies were included according to the inclusion criteria.  Only 16 randomized controlled trials (RCTS) involving 368 patients were found.  These researchers found following evidences for effectiveness of bisphosphonates in prevention of BMD loss in acute SCI: very low-quality evidence for clodronate and etidronate, low-quality evidence for alendronate, and moderate-quality evidence for zoledronic acid.  Low-quality evidence showed no effectiveness for tiludronate.  In chronic SCI cases, these investigators found low-quality evidence for effectiveness of vitamin D3 analogs combined with 1-alpha vitamin D2.  However, low-quality inconsistent evidence exists for alendronate.  For non-pharmacologic interventions, very low-quality evidence exists for effectiveness of standing with or without treadmill walking in acute SCI.  Other low-quality evidences indicated that electrical stimulation, tilt-table standing, and ultrasound provided no significant effects.  Very low-quality evidence did not show any benefit for low-intensity (3 days per week) cycling with functional electrical stimulator in chronic SCI.  The authors concluded that no recommendations could be made from this review, regarding overall low quality of evidence as a result of high risk of bias, low sample size in most of the studies, and notable heterogeneity in type of intervention, outcome measurement, and duration of treatment.  Thy stated that future high-quality RCT studies with higher sample sizes and more homogeneity are needed to provide high-quality evidence and make applicable recommendations for prevention and treatment of SCI-related bone loss.

Bone Mineral Density and Anti-Psychotic Medications

Wang and associates (2014) examined the effects of conventional and atypical anti-psychotics on BMD and serum prolactin levels (PRL) in patients with schizophrenia.  A total of 163 first-episode inpatients with schizophrenia were recruited, to whom 1 of 3 conventional anti-psychotics (perphenazine, sulpiride, and chlorpromazine) or 1 of 3 atypical anti-psychotics (clozapine, quetiapine, and aripiprazole) was prescribed for 12 months as appropriate; BMD and PRL were tested before and after treatment.  Same measures were conducted in 90 matched healthy controls.  Baseline BMD of postero-anterior L1 to L4 ranged from 1.04 ± 0.17 to 1.42 ± 1.23, and there was no significant difference between the patients group and healthy control group.  However, post-treatment BMD values in patients (ranging from 1.02 ± 0.15 to 1.23 ± 0.10) were significantly lower than that in healthy controls (ranging from 1.15 ± 0.12 to 1.42 ± 1.36).  The BMD values after conventional anti-psychotics were significantly lower than that after atypical anti-psychotics.  The PRL level after conventional anti-psychotics (53.05 ± 30.25 ng/ml) was significantly higher than that after atypical anti-psychotics (32.81 ± 17.42 ng/ml).  Conditioned relevance analysis revealed significant negative correlations between the PRL level and the BMD values after conventional anti-psychotics.  The authors concluded that the increase of PRL might be an important risk factor leading to a high prevalence of osteoporosis in patients with schizophrenia on long-term conventional anti-psychotic medication.

De Hert and colleagues (2016) noted that the use of anti-psychotic medications can increase PRL levels, causing hyperprolactinemia (HPRL).  Although the occurrence of osteoporosis within the population of patients with schizophrenia has been recognized, the precise nature of the association between anti-psychotic treatment, PRL, osteoporosis, and the disease itself appeared to be elusive.  These investigators reviewed the literature regarding the association between osteoporosis and PRL and summarized the available evidence with respect to the impact of PRL-elevating anti-psychotics on BMD and fractures in non-elderly patients with schizophrenia.  The authors concluded that although long-standing HPRL can have an impact on the rate of bone metabolism and, when associated with hypogonadism, may lead to decreased bone density in both female and male subjects, the relative contribution of anti-psychotic-induced HPRL in bone mineral loss in patients with schizophrenia remains unclear.  They stated that methodological shortcomings of existing studies, including the lack of prospective data and the focus on measurements of BMD instead of bone turnover markers, precluded definitive conclusions regarding the relationship between PRL-raising anti-psychotics and BMD loss in patients with schizophrenia.  They stated that more well-designed prospective studies of these biomarkers are needed to establish the precise relationship between anti-psychotics, PRL levels and osteoporosis/osteoporotic risk.

Cone Beam Computed Tomography for Detection of Low Bone Mass (including Evaluation of Post-Menopausal Osteoporosis)

Mostafa and colleagues (2016) examined the feasibility of using mandibular cone beam computed tomography (CBCT) radiomorphometric indices and box-counting fractal dimension (FD) to
  1. detect osteoporosis in post-menopausal women,
  2. compare them with the healthy control group, and
  3. correlate the findings with the BMD measured by DXA. 

This study consisted of 50 post-menopausal women, with age ranging from 55 to 70 years.  Based on their DXA results, they were classified into osteoporotic and control groups.  Mandibular CBCT radiomorphomertic indices and FD analysis were measured.  Significant differences were found for the CT cortical index scores (CTCI), CT mental index (CTMI) and CT mandibular index (CTI) between the control and osteoporotic groups.  The control group showed higher mean values than the osteoporotic group.  For FD values, no significant differences were found between the 2 groups.  The authors concluded that these findings suggested that radiomorphometric indices that were assessed using CBCT could be used as a useful adjuvant tool to refer patients at risk of osteoporosis for further densitometric analysis.  Regarding FD, further research must be conducted to evaluate the usefulness of using this tool in CBCT images to diagnose osteoporosis.  Moreover, they stated that further research should contain a larger sample size of female populations of different age groups and menstruation conditions.  Also, further research should include patients with osteopenia, as this may give further information about the mandibular osseous changes at the initial stages of the disease.


Brasileiro and associates (2017) correlated radiometric indices from CBCT images and BMD in post-menopausal women.  A total of 60 post-menopausal women with indications for dental implants and CBCT evaluation were selected; DXA was performed, and patients were divided into
  1. normal,
  2. osteopenia, and
  3. osteoporosis groups, according to the WHO criteria. 

Cross-sectional images were used to evaluate the CTMI, the computed tomography index (inferior) (CTI (I)) and computed tomography index (superior) (CTI (S)).  Student's t test was used to compare the differences between the indices of the groups' intraclass correlation coefficient (ICC).  Statistical analysis showed a high degree of inter-observer and intra-observer agreement for all measurements (ICC > 0.80).  The mean values of CTMI, CTI (S), and CTI (I) were lower in the osteoporosis group than in osteopenia and normal patients (p < 0.05).  In comparing normal patients and women with osteopenia, there was no statistically significant difference in the mean value of CTI (I) (p = 0.075).  The authors concluded that quantitative CBCT indices may help dentists to screen for women with low spinal and femoral BMD so that they can refer post-menopausal women for bone densitometry.

Guerra and co-workers (2017) systematically reviewed the literature about the capability of CBCT images to identify individuals with low BMD.  As the literature is scarce regarding this topic, the purpose of this systematic review was also to guide future research in this area.  A detailed search was performed in 5 databases without restrictions of time or languages.  Additionally, a grey literature search was conducted.  The Quality Assessment Tool for Diagnostic Accuracy Studies-2 was applied to evaluate the methodological design of selected studies.  With the inclusion of only 6 studies, the evidence was limited to endorse the use of CBCT assertively as a diagnostic tool for low BMD.  All of the 3 studies that analyzed radiomorphometric indices found that the linear measurements of the mandibular inferior cortex were lower in osteoporotic individuals; CBCT-derived radiographic density vertebral and mandibular measurements were also capable for differentiating individuals with osteoporosis from individuals with normal BMD.  The analysis of the cervical vertebrae showed high accuracy measurements.  The authors concluded that this systematic review indicated a scarcity of studies regarding the potential of CBCT for screening individuals with low BMD.  However, the studies indicated that radiomorphometric indices and CBCT-derived radiographic density should be promising tools for differentiating individuals with osteoporosis from individuals with normal BMD.

Furthermore, an UpToDate review on "Clinical manifestations, diagnosis, and evaluation of osteoporosis in postmenopausal women" (Rosen and Drezner, 2017) states "Several different methods are available to measure bone density.  DXA gives an accurate and precise estimate of BMD.  Thus, in clinical practice, DXA is the technology used for diagnostic classification".  It does not mention cone beam computed tomography as a diagnostic tool.

Poiana et al (2023) noted that CBCT is often used in the pre-operative qualitative and quantitative assessment of dental implant sites, offering dimensional accuracy, spatial resolution, gray density, and contrast comparable to those of classical CT scan, yet with disputable ability to determine bone mass density.  These investigators carried out a systematic review of the literature using the PubMed and SCOPUS databases, with terms referring to low bone mass and cone-beam computed tomography (CBCT).  A total of 16 studies were included in the review.  The results revealed different perspectives; however, the evidence favored the use of CBCT, combined with DXA evaluation, for the assessment of the osteoporosis status of the aging population and, more specifically, in post-menopausal women.  Radiographic density (RD) values of the dens and the left part of the 1st cervical vertebra show the strongest correlation coefficients and the highest sensitivity, specificity, and accuracy for predicting osteoporosis (OP) in the lumbar vertebrae and the femoral neck.  The authors concluded that the findings of this review suggested the potential of CBCT as a screening tool for patients with low bone mass using different radio-morphometric indices.  These investigators stated that linear measurements of the inferior mandibular cortex were lower in osteoporotic individuals, indicating the potential of CBCT also as a diagnostic tool for this disease.

Finite Element Analysis

Johannesdottir and associates (2018) reviewed the ability of CT-based methods (e.g., finite element analysis [FEA]) to predict incident hip and vertebral fractures.  These investigators stated that CT-based techniques with concurrent calibration all showed strong associations with incident hip and vertebral fracture, predicting hip and vertebral fractures as well as, and sometimes better than, dual-energy X-ray absorptiometry areal biomass density (DXA aBMD).  There is growing evidence for use of routine CT scans for bone health assessment.  These investigators noted that CT-based techniques provide a robust approach for osteoporosis diagnosis and fracture prediction.  It remains to be seen if further technical advances will improve fracture prediction compared to DXA aBMD.  Future work should include more standardization in CT analyses, establishment of treatment intervention thresholds, and more studies to determine whether routine CT scans can be efficiently used to expand the number of individuals who undergo evaluation for fracture risk.

Groenen and colleagues (2018) noted that current FE models predicting failure behavior comprise single vertebrae, thereby neglecting the role of the posterior elements and intervertebral discs. These investigators developed a more clinically relevant, case-specific non-linear FE model of 2 functional spinal units able to predict failure behavior in terms of the vertebra predicted to fail; deformation of the specimens; stiffness; and load to failure.  In addition, they examined the effect of different bone density-mechanical properties relationships (material models) on the prediction of failure behavior.  Twelve 2 functional spinal units (T6 to T8, T9 to T11, T12 to L2, and L3 to L5) with and without artificial metastases were destructively tested in axial compression.  These experiments were simulated using CT-based case-specific non-linear FE models.  Bone mechanical properties were assigned using 4 commonly used material models.  In 10 of the 11 specimens, the FE model was able to correctly indicate which vertebrae failed during the experiments.  However, predictions of the three-dimensional (3D) deformations of the specimens were less promising.  Whereas stiffness of the whole construct could be strongly predicted (R2  = 0.637 to 0.688, p < 0.01), these researchers obtained weak correlations between FE predicted and experimentally determined load to failure, as defined by the total reaction force exhibiting a drop in force (R2  = 0.219 to 0.247, p > 0.05). Furthermore, they found that the correlation between predicted and experimental fracture loads did not strongly depend on the material model implemented, but the stiffness predictions did. The authors concluded that whereas the FE model was able to correctly indicate which vertebrae failed during the experiments, it had difficulties predicting the 3D deformation of the specimens.  In addition, stiffness could be strongly predicted by this model, but these researchers obtained weak correlations between FE predicted and experimentally determined vertebral strength.  Thus, this work showed that, in its current state, the FE models may be used to identify the weakest vertebra, but that substantial improvements are needed to quantify in-vivo failure loads.

These investigators stated that the FE model might profit from more realistic intervertebral discs (IVDs) models.  In contrast to the bone material behavior, the IVD properties used in this study were not case‐specific but obtained from the literature.  However, both the type of material model and values for coefficients used in previous FE studies varied highly.  The effect of these varying parameters on predictions of vertebral stiffness and/or bone strength is not well-studied.  Thus, effort could be put in determining (case‐specific) mechanical properties of IVD tissue, and, subsequently, in examining how implementing these properties in FE models affects the failure behavior of both single vertebra and 2 functional spinal units.  In addition, gaining more insight into the effect of IVD properties on endplate failure would be valuable, as endplate failure could not be captured correctly by the current FE model.  For this reason, emphasis should also be put on further characterizing and adequately simulating the endplates’ mechanical properties.  Furthermore, in case of sufficient resources and anatomical specimens, it would be interesting to combine testing of 2 functional spinal units with single vertebra tests; thus, the validity of the material models could be better tested.  These researchers also stated that whereas in the experiments soft tissues, including the spinal ligaments and facet capsules, were left intact, these structures were not accounted for in the FE simulations.  Spinal ligaments may contribute to the specimens’ stiffness and strength, especially when moving in flexion, extension, or lateral bending.  As these researchers allowed the specimens to pivot around the load application point, such movements could occur.  Adding ligaments and facet capsules to the FE model provides loading conditions being more realistic and better mimicking the experimental conditions, which potentially results in a better predictive capacity of the FE model.

Rajapakse and Chang (2018) noted that hip fractures have catastrophic consequences.  These investigators reviewed recent developments in high-resolution magnetic resonance imaging (MRI)-guided FEA of the hip as a means to determine subject-specific bone strength.  Despite the ability of DXA to predict hip fracture, the majority of fractures occur in patients who do not have BMD T scores less than - 2.5.  Thus, without other detection methods, these individuals go undetected and untreated.  Of methods available to image the hip, MRI is currently the only one capable of depicting bone microstructure in-vivo.  Availability of micro-structural MRI allowed generation of patient-specific micro-FE models that can be used to simulate real-life loading conditions and determine bone strength.  The authors concluded that MRI-based FEA enabled radiation-free approach to evaluate hip fracture strength.  These researchers stated that with further validation, this technique could become a potential clinical tool in managing hip fracture risk.

Allaire and co-workers (2019) stated that previous studies showed vertebral strength from CT-based FEA may be associated with vertebral fracture risk.  These investigators found vertebral strength had a strong association with new vertebral fractures, suggesting that vertebral strength measures may identify those at risk for vertebral fracture and may be a useful clinical tool.  In a case-control study, these researchers examined the association between vertebral strength by QCT-based FEA and incident vertebral fracture (VF).  In addition, they determined sensitivity and specificity of previously proposed diagnostic thresholds for fragile bone strength and low BMD in predicting VF.  A total of 26 incident VF cases (13 men, 13 women) and 62 age- and sex-matched controls aged 50 to 85 years were selected from the Framingham multi-detector CT cohort.  Vertebral compressive strength, integral volumetric BMD (vBMD), trabecular vBMD, CT-based BMC, and CT-based aBMD were measured from CT scans of the lumbar spine.  Lower vertebral strength at baseline was associated with an increased risk of new or worsening VF after adjusting for age, BMI, and prevalent VF status (OR = 5.2 per 1 SD decrease, 95 % CI: 1.3 to 19.8).  Area under receiver operating characteristic (ROC) curve comparisons revealed that vertebral strength better predicted incident VF than CT-based aBMD (AUC = 0.804 versus 0.715, p = 0.05); but was not better than integral vBMD (AUC = 0.815) or CT-based BMC (AUC = 0.794).  Furthermore, proposed fragile bone strength thresholds trended toward better sensitivity for identifying VF than that of aBMD-classified osteoporosis (0.46 versus 0.23, p = 0.09).  The authors concluded that the findings of this study showed an association between vertebral strength measures and incident vertebral fracture in men and women.  These researchers stated that although limited by a small sample size (n = 26), these findings also suggested that bone strength estimates by CT-based FEA provided equivalent or better ability to predict incident vertebral fracture compared to CT-based aBMD.  These findings need to be validated by well-designed studies.

Westbury and colleagues (2019) noted that high-resolution peripheral QCT (HRpQCT) is increasingly used for examining associations between bone micro-architectural and FEA parameters and fracture.  These researchers hypothesized that combining bone micro-architectural parameters, geometry, BMD and FEA estimates of bone strength from HRpQCT may improve discrimination of fragility fractures.  The analysis sample comprised of 359 subjects (aged 72 to 81 years) from the Hertfordshire Cohort Study (HCS).  Fracture history was determined by self-report and vertebral fracture assessment.  Subjects underwent HRpQCT scans of the distal radius and DXA scans of the proximal femur and lateral spine.  Poisson regression with robust variance estimation was used to derive relative risks (RRs) for the relationship between individual bone micro-architectural and FEA parameters and previous fracture.  Cluster analysis of these parameters was then performed to identify phenotypes associated with fracture prevalence.  Receiver operating characteristic analysis suggested that bone micro-architectural parameters improved fracture discrimination compared to areal BMD (aBMD) alone, whereas further inclusion of FEA parameters resulted in minimal improvements.  Cluster analysis (k-means) identified 4 clusters.  The first had lower Young modulus, cortical thickness, cortical volumetric density and Von Mises stresses compared to the wider sample; fracture rates were only significantly greater among women (RR [95 % CI] compared to lowest risk cluster: 2.55 [1.28 to 5.07], p = 0.008).  The second cluster in women had greater trabecular separation, lower trabecular volumetric density and lower trabecular load with an increase in fracture rate compared to lowest risk cluster (1.93 [0.98 to 3.78], p = 0.057).  These findings may help inform intervention strategies for the prevention and management of osteoporosis.  The authors concluded that micro-architectural deterioration, bone geometry and, in women, FEA-derived bone strength contributed to an increased risk of previous fracture.  Cluster analysis revealed a cortical and a trabecular deficiency phenotype, which both showed lower aBMD in men and women.  Only women with the cortical deficiency phenotype had significantly increased risk of previous fractures.  In this cohort, adding bone micro-architectural parameters to aBMD could better predict previous fracture, but further addition of FEA conferred little benefit.

The authors stated that this study had several drawbacks.  First, a healthy responder bias has been observed in HCS and examining subject characteristics according to inclusion status has revealed healthier lifestyles at baseline for subjects included in the analysis sample compared to those who were not.  However, these analyses were internal, so bias would only arise if the associations of Interest differed systematically between those who were included in the analysis sample and those who were not; this appeared unlikely.  Second, temporal causation could not be inferred as this study had a cross-sectional design.  It may be that the differences in bone microstructure observed were secondary to re-modelling in response to fracture, rather than properties of the bone that predispose to fracture, especially as these researchers had only collected information regarding previous fractures.  Third, fracture status was missing for some subjects, although this information was available for the vast majority (91.9 %) of the analysis sample.  Fourth, the low numbers of reported fractures and a relatively small sample size, along with the lack of stability regarding cluster analysis algorithms in general, may limit the generalizability of findings.  However, the similarity of the clusters observed to those in other analyses and their biological plausibility suggested that they were robust.

Furthermore, an UpToDate review on "Osteoporotic fracture risk assessment" (Lewiecki, 2019) lists FEA as one of the new and emerging technologies.  It states that "Finite element analysis (FEA) uses computer models of images and data from QCT of the spine or hip to assess bone strength.  QCT-based FEA can be used to predict vertebral fracture in postmenopausal women and is comparable with spine DXA in predicting vertebral fractures in men; it is also comparable with hip DXA in predicting hip fractures in postmenopausal women and older men.  FEA cannot be used to diagnose osteoporosis, initiate therapy, or monitor therapy.  While all of these technologies have provided insight into skeletal properties other than BMD that determine bone strength, their role in clinical practice has not been defined.  These techniques are used primarily in research settings".

Redepenning and colleagues (2019) noted that finite element modeling serves as a promising tool for investigating underlying rotator cuff biomechanics and pathology.  However, there are currently no concrete guidelines for reporting in finite element model studies.  This has compromised the reliability, validity, and reproducibility of literature due to omission of pertinent items within publications.  Recently a Finite Element Model Grading Procedure has been proposed as a reporting guideline for model developers.  These researchers conducted a systematic review of rotator cuff focused finite element models and characterized the reporting quality of those articles.  A comprehensive literature search was performed in PubMed, Web of Science, and Embase to find relevant articles.  Each article was graded and given a reporting quality ranking based on a score generated from the Finite Element Model Grading Procedure.  These investigators found that only 5/22 articles had scores of 75 % or higher and fell within the "exceptional" reporting quality range.  Most of the articles (16/22) fell within the "good" reporting quality range with scores between 50 % and 75 %.  However, 9/16 articles within the "good" reporting quality range had scores below 60 %.  The authors concluded that this study indicated that improved guidelines and standards for good reporting practices must be made in the field of finite element modeling.  Furthermore, it supported the use of the Finite Element Model Grading Procedure as an objective method for evaluating the quality of finite element model reporting in the literature.

Measurement of Advanced Glycation End-Products by Skin Auto-Fluorescence for Assessment of Fracture Risk

Willett et al (2022) stated that the accumulation of advanced glycation end-products (AGEs) in the organic matrix of bone with aging and chronic disease such as diabetes is thought to increase fracture risk independently of bone mass.  However, currently, there has not been a clinical study to examine if inhibiting the accumulation of AGEs is effective in preventing low-energy, fragility fractures.  Moreover, unlike with cardiovascular or kidney disease, there are also no pre-clinical studies reporting that AGE inhibitors or breakers could prevent the age- or diabetes-related decrease in the ability of bone to resist fracture.  These researchers examined the case for a long-standing hypothesis that AGE accumulation in bone tissue degrades the toughening mechanisms by which bone resists fracture.  Previous research into the role of AGEs in bone has primarily measured pentosidine, an AGE cross-link, or bulk fluorescence of hydrolysates of bone.  While significant correlations exist between these measurements and mechanical properties of bone, multiple AGEs are both non-fluorescent and non-crosslinking.  Since clinical studies are equivocal on whether circulating pentosidine is an indicator of elevated fracture risk, there needs to be a more complete understanding of the different types of AGEs including non-crosslinking adducts and multiple non-enzymatic cross-links in bone extracellular matrix and their specific contributions to hindering fracture resistance (biophysical and biological).  By doing so, effective strategies to target AGE accumulation in bone with minimal side effects could be examined in pre-clinical and clinical studies that aim to prevent fragility fractures in conditions that bone mass is not the underlying culprit.  The authors stated that the main drawback of this study was that most human cadaveric tissue and in-vivo animal model studies reported negative correlations between AGEs and toughness rather than demonstrating causation or mechanistic insight.  A second drawback pertained to the lack of validated protocols to detect and quantify the different types of AGEs.

Brandt et al (2022) noted that the role of AGEs in bone fragility especially in diabetic bone disease is increasingly recognized and studied.  As skeletal frailty in diabetes does not correlate with BMD in the same way as in post-menopausal osteoporosis, BMD may not be a suitable measure of bone quality in diabetic patients.  Abundant research exists upon the effect of AGEs on bone, and though full understanding of the mechanisms of actions does not yet exist, there is little doubt of the clinical relevance; therefore, the measurement of AGEs as well as possible treatment effects on AGEs have become issues of interest.  In a systematic review, these investigators examined results of measurements of AGEs.  They reviewed available evidence on AGE measurements in clinical research, as well as the precision of skin auto-fluorescence (SAF; a validated non-invasive measure of tissue AGEs) measurement by AGE Reader (DiagnOptics B.V., Groningen, the Netherlands); and commented on treatment of osteoporosis in patients with and without diabetes with respects to AGEs.  The authors concluded that various AGE measures correlated well, both fluorescent and non-fluorescent and in different tissues, and that more than 1 target of measure may be used.  However, pentosidine has shown good correlation with both bone measures and fracture risk in existing literature and results on SAF as a surrogate measurement is promising as some corresponding associations with fracture risk and bone measures have been reported.  Moreover, these investigators stated that as SAF measurements performed with the AGE Reader displayed high precision and allowed for a non-invasive procedure, conducting AGE measurements using this method has great potential and further research of its applicability is encouraged.  These researchers stated that AGEs are promising candidates for explaining the increased bone fragility in diabetes; however, further investigation is needed on the exact relationship between AGEs and bone biomechanical competence and fracture risk.

Yavuz and Apaydin (2022) stated that although the risk of bone fracture is increased in patients with type 2 diabetes (T2DM), BMD is increased rather than decreased.  Accumulation of AGEs adversely influences the fracture resistance of bone in T2DM.  In a cross-sectional, case-control study, these researchers hypothesized that SAF is also associated with BMD levels in patients with T2DM; and examined the association of SAF with BMD and the presence of osteoporosis.  This trial included 237 patients with T2DM (F/M: 133/104, 56.2 ± 11.9 years) and 100 age- and sex-matched controls (F/M: 70/30, 54.8 ± 8.8 years).  SAF was employed to detect the accumulation of AGEs in skin collagen using AGE Reader.  furthermore, BMD was measured with DEXA.  Patients with T2DM had higher SAF values compared to control group (2.21 ± 0.53 AU versus 1.79 ± 0.33 AU, p < 0.001).  Male subjects had higher SAF compared to women (2.34 ± 0.53 AU versus 2.11 ± 0.50 AU, p < 0.001).  Subjects with below -2.5 femoral neck or lumbar T scores had higher SAF measurements compared to subjects with normal T scores (2.46 ± 0.53 AU versus 2.18 ± 0.52 AU, p = 0.006).  Femoral neck BMD was lower in subjects with T2DM (0.946 ± 0.345 g/cm2 versus 1.005 ± 0.298 g/cm2, p = 0.002).  There was a negative correlation between SAF and femoral neck BMD (r = -0.24, p < 0.001), femoral neck T scores (r = -0.24, p < 0.001), L1 to L4 BMD (r = -0.10, p = 0.005), L1 to L4 T score (r = -0.16, p = 0.001) and a positive correlation between SAF and age (r = 0.44, p < 0.001), BMI (r = 0.16, p = 0.002) and hemoglobin A1c (HbA1c) (r = 0.37, p < 0.001).  The authors concluded that accumulation of skin AGEs was increased, and BMD levels were decreased in patients with T2DM.  A negative association between SAF and BMD was detected, indicating a relationship between higher AGE accumulation and low BMD and osteoporosis in diabetic patients.  Moreover, these researchers stated that prospective, long-term studies are needed to identify the practical use of SAF measurement in diabetic bone disease.

Liu et al (2022) noted that AGEs that abnormally accumulate in diabetic patients have been reported to damage bone health.  These investigators examined the association between SAF-AGEage (SAF - AGEs × age/100) and low bone density (LBD)/osteoporosis or major osteoporotic fractures (MOFs) in patients with T2DM.  This study was nested in the prospective REACTION (Risk Evaluation of Cancers in Chinese Diabetic Individuals) Trial and included 1,214 eligible subjects.  SAF was used to measure skin AGEs (SAF-AGEs).  Fracture events were determined by an in-person clinical follow-up.  Binary logistic regression analysis, linear regression analysis, and a restricted cubic spline nested in logistic models were used to test outcomes.  The overall prevalence of LBD/osteoporosis in middle-aged or elderly T2DM patients was 35.7 % (n = 434), and the overall incidence of MOFs was 10.5 % (n = 116).  Logistic analysis showed a significantly positive relationship between quartiles of SAF-AGEage and the risk of LBD/osteoporosis (OR 2.02, 95 % CI: 1.34 to 3.03; OR 3.63, 95 % CI: 2.44 to 5.39; and OR 6.51, 95 % CI: 4.34 to 9.78) for the multivariate-adjusted models, respectively.  SAF-AGEage was associated with MOFs with a multivariate-adjusted OR of 1.02 (95 % CI: 0.52 to 2.02), 2.42 (95 % CI: 1.32 to 4.46), and 2.70 (95 % CI: 1.48 to 4.91), respectively.  Stratified analyses showed that SAF-AGEage was significantly associated with MOFs only in females, non-smokers, non-drinkers, individuals with lower BMI, and those without LBD/osteoporosis.  Linear regression analyses showed that higher SAF-AGEs were associated with a higher level of serum N-terminal pro-peptide of type I procollagen (s-PINP) and serum carboxy-terminal cross-linking peptide of type I collagen (s-CTX), with a multivariate-adjusted OR of 1.02 (95 % CI: 0.24 to 1.80) and 6.30 (95 % CI: 1.77 to 10.83), respectively.  The authors concluded that SAF‐AGEage was positively associated with the prevalence of LBD/osteoporosis in patients with T2DM.  These investigators also found a positive association between SAF‐AGEs and s‐PINP and s‐CTX.  There was an association between SAF‐AGEage and the incidence of MOFs that was independent of BMD.  Moreover, these researchers stated that larger prospective studies are needed to examine the effects of AGEs on bone fractures in T2DM patients.

The authors stated that this study had 2 main drawbacks.  First, the loss to follow‐up for MOFs was 9.3 % due to incorrect contact details, death, no response, etc.  Second, the subjects were from 2 communities located in urban Beijing.  The findings obtained from these participants may be generalizable to at least the wider middle‐aged and elderly Beijing and Chinese T2DM population.  However, further investigation is needed to confirm the generalizability of these findings.

Haffer et al (2023( noted that impaired bone integrity and muscle function are described as osteosarcopenia, which is associated with falls, fragility fractures, and reduced quality of life (QOL).  Bone integrity is influenced by bone quantity (BMD) and quality (micro-architecture and collagen).  The accumulation of AGEs stiffens collagen fibers and increases bone fragility.  The relationship between para-spinal muscle composition and bone collagen properties has not been evaluated.  In a prospective, cross-sectional study, these researchers examined if an accumulation of AGEs is associated with impaired para-spinal muscle composition.  Intra-operative bone biopsies from the posterior superior iliac spine were obtained and evaluated with multi-photon microscopy for fluorescent AGE cross-link density (fAGEs).  Pre-operative MRI measurements at L4 included the musculus (m.) psoas and combined m. multifidus and m. erector spinae (posterior paraspinal musculature, PPM).  Muscle segmentation on axial images (cross-sectional area, CSA) and calculation of a pixel intensity threshold method to differentiate muscle (functional CSA [fCSA]) and intra-muscular fat (FAT).  Quantitative CT was carried out at the lumbar spine.  Univariate and multi-variable regression models were used to examine associations between fAGEs and para-spinal musculature.  A total of 107 prospectively enrolled patients (50.5 % women, age of 60.7 years, BMI 28.9 kg/m 2 ) were analyzed.  In all, 41.1 % and 15.0 % of the patients showed osteopenia and osteoporosis, respectively.  Univariate linear regression analysis revealed a significant association between cortical fAGEs and CSA in the psoas (ρ = 0.220, p = 0.039) but not in the PPM.  Trabecular fAGEs demonstrated no significant associations to PPM or psoas musculature.  In the multi-variable analysis, higher cortical fAGEs were associated with increased FAT (β = 1.556; p = 0.002) and CSA (β = 1.305; p = 0.005) in the PPM after adjusting for co-variates.  The authors concluded that this was the 1st investigation showing that an accumulation of non-enzymatic collagen cross-linking product fAGEs in cortical bone was associated with increased intramuscular fat in the lumbar para-spinal musculature.

Radiofrequency Echographic Multi Spectrometry (REMS)

Radiofrequency echographic multi spectrometry (REMS) is a non-invasive, non-ionizing technology that uses an ultrasound-based technique for evaluating the bone status at axial skeletal sites. REMS analyzes raw, unfiltered native ultrasound signals obtained during an ultrasound scan of the lumbar spine (L1 to L4) and proximal femur. "The measured data are synthesized into a patient-specific spectrum that is compared to reference spectral models matched by gender, age, site, and BMI in a database. The spectral modifications introduced by the physical properties of bone structure that back-diffuse the ultrasound signals are identified via a comparison procedure to determine an estimate of the BMD and the consequent diagnostic classification of healthy, osteopenic, or osteoporotic" (Al Refaie et al, 2023).

Al Refaie and colleagues (2023) state that there has been growing interest in identifying new parameters and technologies capable of diagnosing osteoporosis and predicting the risk of fragility fractures in a simple and economically sustainable way. Thus, the authors performed a systematic literature review to evaluate the data on the REMS technique for assessing bone status. Their review included literature from the REMS inception in 2019 to January 31, 2023, obtained from PubMed-Medline, Cochrane Library, ClinicalTrials.gov, and SCOPUS databases. Study designs found in the literature on validation of the REMS technique included a mutlicenter, cross-sectional observational studies by Di Paola et al (2019) and Cortet et al (2021); cross-sectional observational studies by Kirilova et al (2019), Nowakowska-Plaza et al (2021), Amorin et al (2021), Sergio et al (2022), and Lalli et al (2022) and; longitudinal observational (5 year studies) by Adami et al (2020) and Pisani et al (2023). Study designs found in the literature on the use of REMS technology in real-life clinical practice include six cross-sectional observational studies (Bojincă et al, 2019; Rolla et al, 2020; Caffarelli et al, 2021; Caffarelli et al, 2022a, 2022b; and Fassio et al, 2023) and one cross-sectional case-control observational study (Degennaro et al, 2021). The authors state that the literature "confirmed diagnostic concordance between BMD values obtained using DXA and REMS. Furthermore, REMS has adequate precision and repeatability characteristics, is able to predict the risk of fragility fractures, and may be able to overcome some of the limitations of DXA". The authors concluded that REMS could become the method of choice for the assessment of bone status in children, in women of childbearing age or who are pregnant, and in several secondary osteoporosis conditions due to its good precision and replicability, its transportability, and the absence of ionizing radiation. In addition, REMS may allow qualitative and not just quantitative assessments of bone status. However, the authors acknowledge that future works and ongoing research is warranted to (i) help understand the role of REMS in diagnosis and follow-up in osteoporosis patients with respect to DXA, and (ii) help understand target populations in which REMS could represent a better alternative to DXA in assessing bone quality and fracture risk.

An UpToDate review on "Osteoporotic fracture risk assessment" (Lewiecki, 2023) states that new technologies and non-BMD DXA measurements have been developed that allow noninvasive assessment of bone strength. The author acknowledges that REM was evaluated in a large, multicenter European study (Cortet et al, 2021) in which REMS was able to "discriminate patients with and without osteoporosis (DXA T-score equal to or less than -2.5) at the femoral neck with sensitivity and specificity of 90.4 and 95.5 percent, respectively; for the lumbar spine scans, sensitivity was 90.9 percent and specificity was 95.1 percent"; however, this technique is primarily used in research settings and its role in clinical practice has not been defined. 

Radiological Computer-Assisted Prioritization / Artificial Intelligence (AI) Software

HealthVCF (Zebra Medical Vision Ltd.), which received U.S. FDA 510(k) premarket notification clearance in May 2020 (K192901), is a radiological computer-assisted prioritization software product that uses an artificial intelligence (AI) algorithm to analyze chest and abdominal CT scans which flags images suggestive of vertebral compression fractures and provides passive notification to the workstation of the presence of this finding in the scan. These flags are viewed by the clinician in Bone Health and Fracture Liaison Service programs in the medical setting via a worklist application on their Picture Archiving and Communication System (PACS). "Zebra’s HealthVCF device works in parallel to and in conjunction with the standard care of workflow within bone health programs, and completely independent of the standard of care workflow within the radiology department. After a chest or abdominal CT scan has been performed, a copy of the study is automatically retrieved and processed by the HealthVCF device. The device performs the analysis of the study and returns a notification about a suspected vertebral compression fractures to the Zebra Worklist to notify the clinicians in Bone Health and Fracture Prevention Programs reviewing the chest and abdominal CTs for at-risk patients. The clinician is then able to review the study earlier and recall the patient for further evaluation". HealthVCF does not send a proactive alert directly to the user, nor provide diagnostic information beyond triage and prioritization. Furthermore, HealthVCF does not remove cases from the radiology worklist, and should not be used in place of full patient evaluation, or relied upon to make or confirm diagnosis. The final diagnosis is provided by a clinician after reviewing the scan itself (FDA, 2020).

There are no published peer-reviewed studies that report the effect of HealthVCF on patient outcomes or clinical management.

Repeat DXA Scan in Post-Menopausal Women

Crandall et al (2020) stated that repeated BMD testing to screen for osteoporosis requires resources.  For patient counseling and optimal resource use, it is important for clinicians to know whether repeated BMD measurement (compared with baseline BMD measurement alone) improves the ability to discriminate between post-menopausal women who will and will not experience a fracture.  These researchers examined if a 2nd BMD measurement approximately 3 years after the initial assessment would be associated with improved ability to estimate fracture risk beyond the baseline BMD measurement alone.  The Women's Health Initiative is a prospective, observational study.  Subjects in the present cohort study included 7,419 women with a mean (SD) follow-up of 12.1 (3.4) years between 1993 and 2010 at 3 U.S. clinical centers.  Data analysis was carried out between May 2019 and December 2019.  Incident major osteoporotic fracture (i.e., hip, clinical spine, forearm, or shoulder fracture), hip fracture, baseline BMD, and absolute change in BMD were examined.  The area under the ROC (AU-ROC) for baseline BMD, absolute change in BMD, and the combination of baseline BMD and change in BMD were calculated to evaluate incident fracture risk discrimination during follow-up.  Of 7,419 participants, the mean (SD) age at baseline was 66.1 (7.2) years, the mean (SD) BMI was 28.7 (6.0), and 1,720 (23 %) were non-white individuals.  During the study follow-up (mean [SD] 9.0 [3.5] years after the 2nd BMD measurement), 139 women (1.9 %) experienced hip fractures, and 732 women (9.9 %) experienced major osteoporotic fracture.  In discriminating between women who experienced hip fractures and those who did not, AU-ROC values were 0.71 (95 % CI: 0.67 to 0.75) for baseline total hip BMD, 0.61 (95 % CI: 0.56 to 0.65) for change in total hip BMD, and 0.73 (95 % CI: 0.69 to 0.77) for the combination of baseline total hip BMD and change in total hip BMD.  Femoral neck and lumbar spine BMD values had similar discrimination for hip fracture.  For discrimination of major osteoporotic fracture, AU-ROC values were 0.61 (95 % CI: 0.59 to 0.63) for baseline total hip BMD, 0.53 (95 % CI: 0.51 to 0.55) for change in total hip BMD, and 0.61 (95 % CI: 0.59 to 0.63) for the combination of baseline total hip BMD and change in total hip BMD.  Femoral neck and lumbar spine BMD values had similar ability to discriminate between women who experienced major osteoporotic fracture and those who did not.  Associations between change in bone density and fracture risk did not differ by subgroup, including diabetes, age, race/ethnicity, BMI, or baseline BMD T-score.  The authors concluded that the findings of this study suggested that a 2nd BMD assessment approximately 3 years after the initial measurement was not associated with improved discrimination between women who did and did not experience subsequent hip fracture or major osteoporotic fracture beyond the baseline BMD value alone and should not routinely be performed.

Zweig et al (2021) recommended that “Do not routinely repeat bone density testing 3 years after initial screening in post-menopausal patients who do not have osteoporosis”.  The strength of the recommendation was “A” based on several large, good-quality prospective, cohort studies (Crandall et al, 2020).

Tomosynthesis-Based Trabecular Bone Analysis and Diabetes Mellitus

Fujii and colleagues (2016) determined femoral neck strength in patients with diabetes mellitus by using trabecular bone analysis values and tomosynthesis images and compared its parameters between vertebral compression fracture and non-fracture groups.  A total of 49 patients with diabetes mellitus were included.  Within 1 week, patients underwent DXA, tomosynthesis, and CT covering the T10 vertebral body to the hip joints.  The trabecular patterns of tomosynthesis images were extracted, and the total strut length, bone volume per tissue volume, and 5 textural features (homogeneity, entropy, correlation, contrast, and variance) were obtained as the indices of tomosynthesis images.  Failure load of the femoral neck, which was determined with the CT-based finite-element method (FEM), was used as the reference standard for bone strength.  A forward step-wise multiple regression analysis for evaluating the availability of the tomosynthesis image indices was performed.  The BMD at DXA and tomosynthesis image indices were compared between the vertebral compression fracture (n = 16) and non-fracture groups (n = 33) according to Genant semi-quantitative morphometric methods by using 1-way analysis of variance.  The combination of BMD with the bone volume per tissue volume at the principal tensile group and the correlation at the principal compressive group showed the highest correlation to the failure load at CT FEM, and the correlation (r2 = 0.83) was higher than that between the failure load and the BMD alone (r2 = 0.76; p < 0.001).  The averages of the bone volume per tissue volume and entropy at the principal tensile group in the vertebral compression fracture group were lower than those in the non-fracture group (p = 0.017 and p = 0.029, respectively), but there was no difference in BMD.  The authors concluded that tomosynthesis-based trabecular bone analysis is technically feasible and, in combination with BMD measurements, can potentially be used to determine bone strength in patients with diabetes mellitus.

Trabecular Bone Score for Evaluation of Fracture Risk

Jose et al (2021) noted that obesity has long been considered to have a protective effect on bone, but specific complications in those with morbid obesity are known to have a detrimental impact on bone architecture.  These researchers examined the bone micro-architecture (trabecular bone score [TBS]) and BMD in post-menopausal women with morbid obesity compared to obese and non-obese age-matched women.  A total of 85 consecutive post-menopausal women with morbid obesity (BMI of 35 kg/m2 or higher) were enrolled and compared to age-matched obese (n = 80) and non-obese post-menopausal controls (n = 85).  The BMD and TBS were assessed in all subjects using a Hologic-QDR 4500-W Discovery-A DXA scanner.  The mean BMD (g/cm2) at the femoral neck in women with morbid obesity was found to be significantly lower as compared to the age-matched post-menopausal obese controls (0.723 versus 0.762, p = 0.002).  The BMD at the lumbar spine and hip showed similar trends but were not statistically significant.  The bone micro-architecture was found to be significantly lower in those with morbid obesity (1.205) as compared to the other 2 groups (obesity 1.244; non-obese 1.228) (p < 0.013).  The authors concluded that although obesity was associated with a better bone density and bone micro-architecture in post-menopausal women, a paradoxical lower value was observed in those with morbid obesity.

Johnson et al (2022) stated that there is limited information regarding the comprehensive bone health in Indian post-menopausal women with neck of femur fracture.  In a cross-sectional study, these researchers examined the BMD, TBS, proximal hip geometry, and bone mineral biochemistry in post-menopausal women with and without femoral neck fractures.  This trial was carried out at a tertiary care center in South India; BMD, TBS, and hip structural analysis (HSA) were assessed using a DXA scanner.  Bone mineral biochemical profiles were also studied.  A total of 90 post-menopausal women with acute femoral neck fracture with mean (SD) age of 63.2 (6.1) years and 90 age-matched controls were included.  The prevalence of osteoporosis was higher among cases as compared to controls (83.3 % versus 47.8 %; p < 0.001).  Degraded bone micro-architecture (TBS value of less than 1.200) was more frequent among women with hip fracture as compared to controls (46.7 % versus 31.1 %; p = 0.032).  Cross-sectional moment of inertia (CSMI) was significantly lower at the narrow neck (NN) and inter-trochanteric (IT) region in cases (p < 0.05) and buckling ratio (BR) was significantly higher at all 3 sites in post-menopausal women with femoral neck fracture as compared controls.  Multi-variate logistic regression analysis showed that femoral neck osteoporosis, low CSMI at NN and high BR at NN and femoral shaft emerged as factors significantly associated with femoral neck fractures.  The authors concluded that this study highlighted impaired parameters of proximal hip geometry and a low TBS may be significantly associated with femoral neck fractures in post-menopausal women.

Shevroja et al (2022) noted that lumbar spine BMD and TBS are both assessed in the lumbar spine DXA scans in the same region of interest, L1 to L4.  These investigators examined the ability to predict osteoporotic fractures of all the possible adjacent lumbar spine vertebrae combinations used to calculate BMD and TBS and examined if any of these combinations would perform better at osteoporotic fracture prediction than the traditional L1 to L4 combination.  Lumbar spine-DXA scans were carried out using Discovery A System (Hologic).  The incident VFs and major osteoporotic fractures (MOFs) were assessed from VF assessments using Genant's method or questionnaires (non-VF MOF).  These researchers ran logistic models using TBS and BMD to predict MOF, VF, and non-VF MOF, combining different adjustment factors (age, fracture level, or BMD).  A total of 1,632 women (mean ± SD), age of 64.4 ± 7.5 years, BMI of 25.9 ± 4.5 kg/m2, were followed for 4.4 years and 133 experienced MOF.  The association of 1 SD decrease L1 to L3 BMD with the ORs of MOF was 1.32 (95 % CI: 1.15 to 1.53), L2 to L4 BMD was 1.25 (95 % CI: 1.09 to 1.42), and L1 to L4 BMD was 1.30 (95 %CI: 1.14 to 1.48).  One SD decrease in L1 to L3 TBS was more strongly associated with the odds of having a MOF (OR 1.64, 95 % CI: 1.34 to 2.00), than 1 SD decrease in L2 to L4 TBS (OR 1.48, 95 % CI: 1.21-1.81), or in L1 to L4 TBS (OR 1.60, 95 % CI: 1.32 to 1.95).  The authors concluded that these findings suggested that the exclusion of L4 and the inclusion of L1 in general in the lumbar spine BMD and TBS calculations improved their performance in fracture risk prediction.  This could be explained by the fact that the lower-level lumbar vertebrae might be more exposed to erroneous positioning of the individual during the lumbar spine DXA acquisition and of the degenerative disease`s presence.  These investigators were limited to suggest the use of L1 to L3, which is the combination appearing more promising from these findings, instead of the L1 to L4 because further investigations of its specificity, precision, and sensitivity in fracture prediction would be needed to support such recommendation. 

It should be noted that TBS can be incorporated into the calculation of the FRAX score.

Urinary Phthalate As a Predictor for Fracture Risk

Reeves et al (2021) stated that phthalates are endocrine-disrupting chemicals that could disrupt normal physiologic function, triggering detrimental impacts on bone.  These researchers examined associations between urinary phthalate biomarkers and BMD in post-menopausal women participating in the prospective Women's Health Initiative (WHI).  They included WHI participants enrolled in the BMD sub-study and selected for a nested case-control study of phthalates and breast cancer (n = 1,255).  These investigators measured 13 phthalate biomarkers and creatinine (Cr) in 2 to 3 urine samples per participant collected over 3 years, when all participants were cancer-free.  Total hip and femoral neck BMD were measured at baseline and year 3, concurrent with urine collection, via DEXA.  These researchers fitted multi-variable generalized estimating equation models and linear mixed-effects models to estimate cross-sectional and longitudinal associations, respectively, with stratification on post-menopausal hormone therapy (HT) use.  In cross-sectional analyses, mono-3-carboxypropyl phthalate (MCPP) and the sum of di-isobutyl phthalate (DIP) metabolites were inversely associated with total hip BMD among HT nonusers, but not among HT users.  Longitudinal analyses showed greater declines in total hip BMD among HT nonusers and with highest concentrations of MCPP (-1.80 %; 95 % CI: -2.81 % to -0.78 %) or mono-carboxy-nonyl phthalate (MCNP) (-1.84 %; 95 % CI: -2.80 % to -0.89 %); similar associations were observed with femoral neck BMD.  Among HT users, phthalate biomarkers were not associated with total hip or femoral neck BMD change.  The authors concluded that certain phthalate biomarkers were associated with greater percentage decreases in total hip and femoral neck BMD.  These findings suggested that phthalate exposure may have clinically important effects on BMD, and potentially fracture risk.  These researchers stated that this study was the 1st prospective evaluation of urinary phthalate biomarkers in relation to BMD.  They stated that additional studies are needed to either confirm or refute these findings.  If confirmed, reduction of phthalate exposure, via personal choices (perhaps especially reduced intake of ultra-processed foods) and/or public health policy changes (including broader advocacy and legislative efforts), may be relevant for maintaining bone health.

The authors stated that this study had several drawbacks.  First, the statistically significant results may reflect a type I error, especially given that results were not adjusted for multiple comparisons.  However, the consistency of the longitudinal findings for mono-carboxy-octyl phthalate (MCOP) and MCNP indicated that these were not spurious associations.  Second, it was possible that MCOP and MCNP are markers of poor diet or of some other, unmeasured, component of food packaging, as opposed to the causal agents themselves.  Third, these investigators measured urinary phthalate metabolites as biomarkers of exposure to parent phthalates.  Phthalates are metabolized and the metabolites are excreted quickly following exposure, and moderate within-person variability in metabolite urinary concentrations is well known.  Therefore, a single measure of urinary phthalate biomarkers represents only short-term phthalate exposure.  Accordingly, the resultant non-differential misclassification of exposure may have attenuated true associations, especially if the effects were small.  It was possible that other phthalate biomarkers are related to BMD but that these researchers lacked the statistical power to detect such associations.  Fourth, these finding may not be generalizable to other populations of post-menopausal women, given the limited racial/ethnic diversity and higher socioeconomic status of WHI participants compared to the general population.  However, the mechanisms linking phthalates to BMD are unlikely to vary by race/ethnicity.  Fifth, these results could not demonstrate causality, only statistical associations.

Heilmann et al (2022) noted that exposure to phthalates may impact BMD via a variety of mechanisms.  Studies of phthalate exposure and BMD in humans are scarce.  These investigators synthesized published data on the association between phthalate metabolites and BMD in humans and provided methodological suggestions for future research.  A single investigator searched PubMed for relevant studies, including observational studies of phthalate exposure and BMD in children and post-menopausal women.  A total of 12 studies were screened with 5 meeting the eligibility criteria and included for review.  A quality assessment form was used as a quality measure and key information was extracted from the included studies.  In 1 prospective study among post-menopausal women, higher levels of MCOP and MCNP were significantly associated with lower BMD among non-users of HT.  In cross-sectional studies of post-menopausal women, mono-ethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), MCPP, and mono-benzyl phthalate (MBzP) were negatively associated with BMD, and MCNP was positively associated with BMD, but these findings were not replicated across studies.  In studies of fetal exposure to phthalates and childhood BMD, significant positive associations between MCPP and BMD in children at age 12 years were found in 1 study, while associations were null in the other study.  The authors concluded that studies among post-menopausal women provided suggestive evidence of an association between urinary phthalate metabolite concentration and decreased BMD.  Results from studies of childhood BMD were inconclusive given the limited data and their limitations.  These researchers stated that further investigation is needed to address limitations and further examine the association between phthalate exposure and human BMD.  Moreover, these investigators stated that future studies of phthalates and BMD should employ repeat measures of the exposure and outcome, evaluate additional measures of bone health and microarchitecture, and allow for extended follow-up throughout critical periods of the life course.  The increasing clinical and economic burden of fractures and osteoporosis indicates a need to elucidate the association between phthalate exposure and BMD.

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