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(1) Borga M, West J, Bell JD, et al. Advanced body composition assessment: from body mass index to body composition profiling. J Investig Med. Jun 2018; 66(5): 1-9. PMID 29581385 2. Barone M, Losurdo G, Iannone A, et al. Assessment of body composition: Intrinsic methodological limitations and statistical pitfalls. Nutrition. Oct 2022; 102: 111736. PMID 35810580 3. Murphy J, Bacon SL, Morais JA, et al. Intra-Abdominal Adipose Tissue Quantification by Alternative Versus Reference Methods: A Systematic Review and Meta-Analysis. Obesity (Silver Spring). Jul 2019; 27(7): 1115-1122. PMID 31131996 4. Sheean P, Gonzalez MC, Prado CM, et al. American Society for Parenteral and Enteral Nutrition Clinical Guidelines: The Validity of Body Composition Assessment in Clinical Populations. JPEN J Parenter Enteral Nutr. Jan 2020; 44(1): 12-43. PMID 31216070 5. Calella P, Valerio G, Brodlie M, et al. Tools and Methods Used for the Assessment of Body Composition in Patients With Cystic Fibrosis: A Systematic Review. Nutr Clin Pract. Oct 2019; 34(5): 701-714. PMID 30729571 6. Calella P, Valerio G, Brodlie M, et al. Cystic fibrosis, body composition, and health outcomes: a systematic review. Nutrition. Nov 2018; 55-56: 131-139. PMID 29981489 5 7. Bundred J, Kamarajah SK, Roberts KJ. Body composition assessment and sarcopenia in patients with pancreatic cancer: a systematic review and meta-analysis. HPB (Oxford). Dec 2019; 21(12): 1603- 1612. PMID 31266698 8. Alves FD, Souza GC, Biolo A, et al. Comparison of two bioelectrical impedance devices and dual- energy X-ray absorptiometry to evaluate body composition in heart failure. J Hum Nutr Diet. Dec 2014; 27(6): 632-8. PMID 24684316 9. Ziai S, Coriati A, Chabot K, et al. Agreement of bioelectric impedance analysis and dual-energy X-ray absorptiometry for body composition evaluation in adults with cystic fibrosis. J Cyst Fibros. Sep 2014; 13(5): 585-8. PMID 24522087 10. Elkan AC, Engvall IL, Tengstrand B, et al. Malnutrition in women with rheumatoid arthritis is not revealed by clinical anthropometrical measurements or nutritional evaluation tools. Eur J Clin Nutr. Oct 2008; 62(10): 1239-47. PMID 17637600 11. Jensky-Squires NE, Dieli-Conwright CM, Rossuello A, et al. Validity and reliability of body composition analysers in children and adults. Br J Nutr. Oct 2008; 100(4): 859-65. PMID 18346304 12. Kullberg J, Brandberg J, Angelhed JE, et al. Whole-body adipose tissue analysis: comparison of MRI, CT and dual energy X-ray absorptiometry. Br J Radiol. Feb 2009; 82(974): 123-30. PMID 19168691 13. Liem ET, De Lucia Rolfe E, L'Abée C, et al. Measuring abdominal adiposity in 6 to 7-year-old children. Eur J Clin Nutr. Jul 2009; 63(7): 835-41. PMID 19127281 14. Bedogni G, Agosti F, De Col A, et al. Comparison of dual-energy X-ray absorptiometry, air displacement plethysmography and bioelectrical impedance analysis for the assessment of body composition in morbidly obese women. Eur J Clin Nutr. Nov 2013; 67(11): 1129-32. PMID 24022260 15. Monteiro PA, Antunes Bde M, Silveira LS, et al. Body composition variables as predictors of NAFLD by ultrasound in obese children and adolescents. BMC Pediatr. Jan 29 2014; 14: 25. PMID 24476029 16. Tompuri TT, Lakka TA, Hakulinen M, et al. Assessment of body composition by dual-energy X-ray absorptiometry, bioimpedance analysis and anthropometrics in children: the Physical Activity and Nutrition in Children study. Clin Physiol Funct Imaging. Jan 2015; 35(1): 21-33. PMID 24325400 17. Alves Junior CAS, de Lima LRA, de Souza MC, et al. Anthropometric measures associated with fat mass estimation in children and adolescents with HIV. Appl Physiol Nutr Metab. May 2019; 44(5): 493- 498. PMID 30286302 18. Barr RD, Inglis D, Athale U, et al. The Influence of Body Composition on Bone Health in Long-term Survivors of Acute Lymphoblastic Leukemia in Childhood and Adolescence: Analyses by Dual-energy Radiograph Absorptiometry and Peripheral Quantitative Computed Tomography. J Pediatr Hematol Oncol. Nov 01 2022; 44(8): 423-431. PMID 35482464 19. Chang CC, Chen YK, Chiu HC, et al. Assessment of Sarcopenia and Obesity in Patients with Myasthenia Gravis Using Dual-Energy X-ray Absorptiometry: A Cross-Sectional Study. J Pers Med. Nov 03 2021; 11(11). PMID 34834491 20. Smoot BJ, Mastick J, Shepherd J, et al. Use of Dual-Energy X-Ray Absorptiometry to Assess Soft Tissue Composition in Breast Cancer Survivors With and Without Lymphedema. Lymphat Res Biol. Aug 2022; 20(4): 391-397. PMID 34793255 21. Dandache C, Confavreux CB, Gavoille A, et al. Peripheral but not axial muscle mass is associated with early mortality in bone metastatic lung cancer patients at diagnosis. Joint Bone Spine. Sep 2023; 90(5): 105613. PMID 37442335 22. Wang LH, Leung DG, Wagner KR, et al. Lean tissue mass measurements by dual-energy X-ray absorptiometry and associations with strength and functional outcome measures in facioscapulohumeral muscular dystrophy. Neuromuscul Disord. Sep 2023; 33(9): 63-68. PMID 37400350 23. Dawra S, Gupta P, Yadav N, et al. Association between the Distribution of Adipose Tissue and Outcomes in Acute Pancreatitis: A Comparison of Methods of Fat Estimation. Indian J Radiol Imaging. Jan 2023; 33(1): 12-18. PMID 36855725 24. Woolcott OO, Bergman RN. Defining cutoffs to diagnose obesity using the relative fat mass (RFM): Association with mortality in NHANES 1999-2014. Int J Obes (Lond). Jun 2020; 44(6): 1301-1310. PMID 31911664 25. Staunstrup LM, Nielsen HB, Pedersen BK, et al. Cancer risk in relation to body fat distribution, evaluated by DXA-scans, in postmenopausal women - the Prospective Epidemiological Risk Factor (PERF) study. Sci Rep. Mar 29 2019; 9(1): 5379. PMID 30926844 6 26. Reina D, Gómez-Vaquero C, Díaz-Torné C, et al. Assessment of nutritional status by dual X-Ray absorptiometry in women with rheumatoid arthritis: A case-control study. Medicine (Baltimore). Feb 2019; 98(6): e14361. PMID 30732168 27. Sinclair M, Hoermann R, Peterson A, et al. Use of Dual X-ray Absorptiometry in men with advanced cirrhosis to predict sarcopenia-associated mortality risk. Liver Int. Jun 2019; 39(6): 1089-1097. PMID 30746903 28. Lindqvist C, Brismar TB, Majeed A, et al. Assessment of muscle mass depletion in chronic liver disease: Dual-energy x-ray absorptiometry compared with computed tomography. Nutrition. May 2019; 61: 93- 98. PMID 30703575 29. Dordevic AL, Bonham M, Ghasem-Zadeh A, et al. Reliability of Compartmental Body Composition Measures in Weight-Stable Adults Using GE iDXA: Implications for Research and Practice. Nutrients. Oct 12 2018; 10(10). PMID 30321991 30. Bazzocchi A, Ponti F, Cariani S, et al. Visceral fat and body composition changes in a female population after RYGBP: a two-year follow-up by DXA. Obes Surg. Mar 2015; 25(3): 443-51. PMID 25218013 31. Franzoni E, Ciccarese F, Di Pietro E, et al. Follow-up of bone mineral density and body composition in adolescents with restrictive anorexia nervosa: role of dual-energy X-ray absorptiometry. Eur J Clin Nutr. Feb 2014; 68(2): 247-52. PMID 24346474 32. Iyengar NM, Arthur R, Manson JE, et al. Association of Body Fat and Risk of Breast Cancer in Postmenopausal Women with Normal Body Mass Index: A Secondary Analysis of a Randomized Clinical Trial and Observational Study. JAMA Oncol. Feb 01 2019; 5(2): 155-163. PMID 30520976 33. Ashby-Thompson M, Heshka S, Rizkalla B, et al. Validity of dual-energy x-ray absorptiometry for estimation of visceral adipose tissue and visceral adipose tissue change after surgery-induced weight loss in women with severe obesity. Obesity (Silver Spring). May 2022; 30(5): 1057-1065. PMID 35384351 34. Sherlock SP, Palmer J, Wagner KR, et al. Dual-energy X-ray absorptiometry measures of lean body mass as a biomarker for progression in boys with Duchenne muscular dystrophy. Sci Rep. Nov 05 2022; 12(1): 18762. PMID 36335191 35. Nguyen AL, Herath M, Burns M, et al. The value of whole-body dual-energy x-ray absorptiometry in assessing body composition in patients with inflammatory bowel disease: a prospective study. Eur J Gastroenterol Hepatol. Jan 01 2024; 36(1): 52-61. PMID 37942750 36. Arthur RS, Xue X, Kamensky V, et al. The association between DXA-derived body fat measures and breast cancer risk among postmenopausal women in the Women's Health Initiative. Cancer Med. Feb 2020; 9(4): 1581-1599. PMID 31875358 37. Garvey WT, Mechanick JI, Brett EM, et al. AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS AND AMERICAN COLLEGE OF ENDOCRINOLOGY COMPREHENSIVE CLINICAL PRACTICE GUIDELINES FOR MEDICAL CARE OF PATIENTS WITH OBESITY. Endocr Pract. Jul 2016; 22 Suppl 3: 1-203. PMID 27219496 38. American College of Radiology. ACR-SPR-SSR Practice Parameter for the Performance of Dual- Energy X-ray Absorptiometry (DXA). 2018; https://gravitas.acr.org/PPTS/DownloadPreviewDocument?DocId=48. Accessed July 20, 2025.? 

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Medical Policy Whole Body Dual X-Ray Absorptiometry to Determine Body Composition Table of Contents • Policy: Commercial • Coding Information
• Information Pertaining to All Policies
• Policy: Medicare • Description
• References
• Authorization Information • Policy History

Policy Number: 577

BCBSA Reference Number: 6.01.40 (For Plan internal use only) NCD/LCD: NA

Related Policies
• Bone Mineral Density Studies, #450
• Vertebral Fracture Assessment with Densitometry, #449 Policy Commercial Members: Managed Care (HMO and POS), PPO, and Indemnity
Medicare HMO BlueSM and Medicare PPO BlueSM Members

Dual x-ray absorptiometry (DXA) body composition studies are considered INVESTIGATIONAL.

Prior Authorization Information
Inpatient • For services described in this policy, precertification/preauthorization IS REQUIRED for all products if the procedure is performed inpatient.
Outpatient • For services described in this policy, see below for products where prior authorization might be required if the procedure is performed outpatient.


Outpatient Commercial Managed Care (HMO and POS) This is not a covered service. Commercial PPO and Indemnity This is not a covered service. Medicare HMO BlueSM This is not a covered service. Medicare PPO BlueSM This is not a covered service. CPT Codes / HCPCS Codes / ICD Codes Inclusion or exclusion of a code does not constitute or imply member coverage or provider reimbursement. Please refer to the member’s contract benefits in effect at the time of service to determine coverage or non-coverage as it applies to an individual member.

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Providers should report all services using the most up-to-date industry-standard procedure, revenue, and diagnosis codes, including modifiers where applicable. CPT Codes There is no specific CPT code for this service.

ICD Diagnosis Codes Investigational for all diagnoses.

Description Body Composition Measurement Body composition measurements can be used to quantify and assess the relative proportions of specific body compartments such as fat and lean mass (eg, bones, tissues, organs, muscles).1, These measurements may be more useful in informing diagnosis, prognosis, or therapy than standard assessments (eg, body weight, body mass index) that do not identify the contributions of individual body compartments or their particular relationships with health and disease. While these body composition measurements have been most frequently utilized for research purposes, they may be useful in clinical settings to: • Evaluate the health status of undernourished patients, those impacted by certain disease states (eg, anorexia nervosa, cachexia), or those undergoing certain treatments (eg, antiretroviral therapy, bariatric surgery). • Evaluate the risk of heart disease or diabetes by measuring visceral fat versus total body fat. • Assess body composition changes related to growth and development (eg, infancy, childhood), aging (eg, sarcopenia), and certain disease states (eg, HIV, diabetes). • Evaluate patients in situations where body mass index is suspected to be discordant with total fat mass (eg, body-building, edema).

A variety of techniques have been researched, including most commonly, anthropomorphic measures, bioelectrical impedance, and dual-energy x-ray absorptiometry (DXA). All of these techniques are based in part on assumptions about the distribution of different body compartments and their density, and all rely on formulas to convert the measured parameter into an estimate of body composition. Therefore, all techniques will introduce variation based on how the underlying assumptions and formulas apply to different populations of subjects (ie, different age groups, ethnicities, or underlying conditions). Techniques using anthropomorphics, bioelectrical impedance, underwater weighing, and DXA are briefly reviewed below. Anthropomorphic Techniques Anthropomorphic techniques for the estimation of body composition include measurements of skinfold thickness at various sites, bone dimensions, and limb circumference.1,2, These measurements are used in various equations to predict body density and body fat. Due to its ease of use, measurement of skinfold thickness is 1 of the most common techniques. The technique is based on the assumption that the subcutaneous adipose layer reflects total body fat but this association may vary with age and sex. Skinfold thickness measurement precision and utility can also be affected by operator experience and a lack of applicable reference data for specific patient populations or percentile extremes. Bioelectrical Impedance Bioelectrical impedance analysis is based on the relation between the volume of the conductor (ie, human body), the conductor's length (ie, height), the components of the conductor (ie, fat and fat-free mass), and its impedance.1,2, The technique involves attaching surface electrodes to various locations on the arm and foot. Alternatively, the patient can stand on pad electrodes. Estimates of body composition are based on the assumption that the overall conductivity of the human body is closely related to lean tissue. The impedance value is then combined with anthropomorphic data and certain other patient-specific parameters (eg, age, gender, ethnicity) to give body compartment measures. These measures are

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calculated based on device manufacturer-specific regression models, which are generally proprietary. Bioelectrical impedance measures can be affected by fat distribution patterns, hydration status, ovulation, and temperature. Underwater Weighing Underwater weighing requires the use of a specially constructed tank in which the subject is seated on a suspended chair.1,The subject is then submerged in the water while exhaling; the difference between weight in air and weight in water is used to estimate total body fat percentage. While valued as a research tool, weighing people underwater is typically not suitable for routine clinical use. This technique is based on the assumption that the body can be divided into 2 compartments with constant densities: adipose tissue, with a density of 0.9 g/cm3, and lean body mass (ie, muscle and bone), with a density of 1.1 g/cm3. One limitation of the underlying assumption is the variability in density between muscle and bone; eg, bone has a higher density than muscle, and bone mineral density varies with age and other conditions. Also, the density of body fat may vary, depending on the relative components of its constituents (eg, glycerides, sterols, glycolipids). Dual-energy X-ray Absorptiometry While the cited techniques assume 2 body compartments, DXA can estimate 3 body compartments consisting of fat mass, lean body mass, and bone mass.1,2, DXA systems use a source that generates x- rays at 2 energies. The differential attenuation of the 2 energies is used to estimate the bone mineral content and soft tissue composition. When 2 x-ray energies are used, only 2 tissue compartments can be measured; therefore, soft tissue measurements (ie, fat and lean body mass) can only be measured in areas in which no bone is present. DXA can also determine body composition in defined regions (ie, the arms, legs, and trunk). DXA measurements are based in part on the assumption that the hydration of fat- free mass remains constant at 73%. Hydration, however, can vary from 67% to 85% and can vary by disease state. Other assumptions used to derive body composition estimates are considered proprietary by DXA manufacturers. The use of DXA for bone mineral density assessment in patients diagnosed with or at risk of osteoporosis is addressed separately in policy #450. Vertebral fracture assessment with densitometry by DXA is addressed separately in policy #449. Summary Description Using low-dose x-rays of 2 different energy levels, whole-body dual-energy x-ray absorptiometry (DXA) measures lean tissue mass, total and regional body fat, as well as bone density. DXA scans have become a tool for research on body composition (eg, as a more convenient replacement for underwater weighing). This evidence review addresses potential applications in clinical care rather than research use of the technology. Summary of Evidence For individuals who have a clinical condition associated with abnormal body composition who receive dual-energy x-ray absorptiometry (DXA) body composition studies, the evidence includes systematic reviews and several cross-sectional studies comparing DXA with other techniques. Relevant outcomes are symptoms and change in disease status. The available studies were primarily conducted in research settings and often used DXA body composition studies as a reference standard. Systematic reviews with meta-analyses exploring the clinical validity of DXA measurements against reference methods for the quantification of fat mass indicate strong overall agreement between these modalities, but raise concerns regarding precision and reliability in some populations, particularly those without existing clinical conditions for which risk of adverse outcomes is influenced by abnormal visceral adiposity. More importantly, no studies were identified in which DXA body composition measurements were actively used in patient management. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome. For individuals who have a clinical condition managed by monitoring changes in body composition over time who receive serial DXA body composition studies, the evidence includes several prospective studies monitoring patients over time. Relevant outcomes are symptoms and change in disease status. The studies used DXA as a tool to measure body composition and were not designed to assess the accuracy

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of DXA. None of the studies used DXA findings to make patient management decisions or addressed how serial body composition assessment might improve health outcomes. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome.

Policy History Date Action 11/2025 Annual policy review. Policy updated with literature review through July 20, 2025; no references added. Policy statement unchanged. 11/2024 Annual policy review. References updated. Policy statements unchanged. 11/2023 Annual policy review. Description, summary, and references updated. Policy statements unchanged. 10/2022 Annual policy review. Description, summary, and references updated. Policy statements unchanged. 10/2021 Annual policy review. Policy statements unchanged. 11/2020 Annual policy review. Description, summary, and references updated. Policy statements unchanged. 10/2019 Annual policy review. Description, summary, and references updated. Policy statements unchanged. 10/2018 Annual policy review. Description, summary, and references updated. Policy statements unchanged. 1/2016 Annual policy review. New references added. 2/2016 Annual policy review. Abbreviation in policy statement changed to DXA.
2/2015 Annual policy review. New references added. 3/2014 Annual policy review. New references added. 11/2011-4/2012 Medical policy ICD 10 remediation: Formatting, editing and coding updates.
No changes to policy statements.
12/2011 New policy describing ongoing non-coverage. Effective 12/2011.
Information Pertaining to All Blue Cross Blue Shield Medical Policies Click on any of the following terms to access the relevant information: Medical Policy Terms of Use Managed Care Guidelines Indemnity/PPO Guidelines Clinical Exception Process Medical Technology Assessment Guidelines

References

  1. Borga M, West J, Bell JD, et al. Advanced body composition assessment: from body mass index to body composition profiling. J Investig Med. Jun 2018; 66(5): 1-9. PMID 29581385
  2. Barone M, Losurdo G, Iannone A, et al. Assessment of body composition: Intrinsic methodological limitations and statistical pitfalls. Nutrition. Oct 2022; 102: 111736. PMID 35810580
  3. Murphy J, Bacon SL, Morais JA, et al. Intra-Abdominal Adipose Tissue Quantification by Alternative Versus Reference Methods: A Systematic Review and Meta-Analysis. Obesity (Silver Spring). Jul 2019; 27(7): 1115-1122. PMID 31131996
  4. Sheean P, Gonzalez MC, Prado CM, et al. American Society for Parenteral and Enteral Nutrition Clinical Guidelines: The Validity of Body Composition Assessment in Clinical Populations. JPEN J Parenter Enteral Nutr. Jan 2020; 44(1): 12-43. PMID 31216070
  5. Calella P, Valerio G, Brodlie M, et al. Tools and Methods Used for the Assessment of Body Composition in Patients With Cystic Fibrosis: A Systematic Review. Nutr Clin Pract. Oct 2019; 34(5): 701-714. PMID 30729571
  6. Calella P, Valerio G, Brodlie M, et al. Cystic fibrosis, body composition, and health outcomes: a systematic review. Nutrition. Nov 2018; 55-56: 131-139. PMID 29981489

5

  1. Bundred J, Kamarajah SK, Roberts KJ. Body composition assessment and sarcopenia in patients with pancreatic cancer: a systematic review and meta-analysis. HPB (Oxford). Dec 2019; 21(12): 1603-
  2. PMID 31266698
  3. Alves FD, Souza GC, Biolo A, et al. Comparison of two bioelectrical impedance devices and dual- energy X-ray absorptiometry to evaluate body composition in heart failure. J Hum Nutr Diet. Dec 2014; 27(6): 632-8. PMID 24684316
  4. Ziai S, Coriati A, Chabot K, et al. Agreement of bioelectric impedance analysis and dual-energy X-ray absorptiometry for body composition evaluation in adults with cystic fibrosis. J Cyst Fibros. Sep 2014; 13(5): 585-8. PMID 24522087
  5. Elkan AC, Engvall IL, Tengstrand B, et al. Malnutrition in women with rheumatoid arthritis is not revealed by clinical anthropometrical measurements or nutritional evaluation tools. Eur J Clin Nutr. Oct 2008; 62(10): 1239-47. PMID 17637600
  6. Jensky-Squires NE, Dieli-Conwright CM, Rossuello A, et al. Validity and reliability of body composition analysers in children and adults. Br J Nutr. Oct 2008; 100(4): 859-65. PMID 18346304
  7. Kullberg J, Brandberg J, Angelhed JE, et al. Whole-body adipose tissue analysis: comparison of MRI, CT and dual energy X-ray absorptiometry. Br J Radiol. Feb 2009; 82(974): 123-30. PMID 19168691
  8. Liem ET, De Lucia Rolfe E, L'Abée C, et al. Measuring abdominal adiposity in 6 to 7-year-old children. Eur J Clin Nutr. Jul 2009; 63(7): 835-41. PMID 19127281
  9. Bedogni G, Agosti F, De Col A, et al. Comparison of dual-energy X-ray absorptiometry, air displacement plethysmography and bioelectrical impedance analysis for the assessment of body composition in morbidly obese women. Eur J Clin Nutr. Nov 2013; 67(11): 1129-32. PMID 24022260
  10. Monteiro PA, Antunes Bde M, Silveira LS, et al. Body composition variables as predictors of NAFLD by ultrasound in obese children and adolescents. BMC Pediatr. Jan 29 2014; 14: 25. PMID 24476029
  11. Tompuri TT, Lakka TA, Hakulinen M, et al. Assessment of body composition by dual-energy X-ray absorptiometry, bioimpedance analysis and anthropometrics in children: the Physical Activity and Nutrition in Children study. Clin Physiol Funct Imaging. Jan 2015; 35(1): 21-33. PMID 24325400
  12. Alves Junior CAS, de Lima LRA, de Souza MC, et al. Anthropometric measures associated with fat mass estimation in children and adolescents with HIV. Appl Physiol Nutr Metab. May 2019; 44(5): 493-
  13. PMID 30286302
  14. Barr RD, Inglis D, Athale U, et al. The Influence of Body Composition on Bone Health in Long-term Survivors of Acute Lymphoblastic Leukemia in Childhood and Adolescence: Analyses by Dual-energy Radiograph Absorptiometry and Peripheral Quantitative Computed Tomography. J Pediatr Hematol Oncol. Nov 01 2022; 44(8): 423-431. PMID 35482464
  15. Chang CC, Chen YK, Chiu HC, et al. Assessment of Sarcopenia and Obesity in Patients with Myasthenia Gravis Using Dual-Energy X-ray Absorptiometry: A Cross-Sectional Study. J Pers Med. Nov 03 2021; 11(11). PMID 34834491
  16. Smoot BJ, Mastick J, Shepherd J, et al. Use of Dual-Energy X-Ray Absorptiometry to Assess Soft Tissue Composition in Breast Cancer Survivors With and Without Lymphedema. Lymphat Res Biol. Aug 2022; 20(4): 391-397. PMID 34793255
  17. Dandache C, Confavreux CB, Gavoille A, et al. Peripheral but not axial muscle mass is associated with early mortality in bone metastatic lung cancer patients at diagnosis. Joint Bone Spine. Sep 2023; 90(5):
  18. PMID 37442335
  19. Wang LH, Leung DG, Wagner KR, et al. Lean tissue mass measurements by dual-energy X-ray absorptiometry and associations with strength and functional outcome measures in facioscapulohumeral muscular dystrophy. Neuromuscul Disord. Sep 2023; 33(9): 63-68. PMID 37400350
  20. Dawra S, Gupta P, Yadav N, et al. Association between the Distribution of Adipose Tissue and Outcomes in Acute Pancreatitis: A Comparison of Methods of Fat Estimation. Indian J Radiol Imaging. Jan 2023; 33(1): 12-18. PMID 36855725
  21. Woolcott OO, Bergman RN. Defining cutoffs to diagnose obesity using the relative fat mass (RFM): Association with mortality in NHANES 1999-2014. Int J Obes (Lond). Jun 2020; 44(6): 1301-1310. PMID 31911664
  22. Staunstrup LM, Nielsen HB, Pedersen BK, et al. Cancer risk in relation to body fat distribution, evaluated by DXA-scans, in postmenopausal women - the Prospective Epidemiological Risk Factor (PERF) study. Sci Rep. Mar 29 2019; 9(1): 5379. PMID 30926844

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  1. Reina D, Gómez-Vaquero C, Díaz-Torné C, et al. Assessment of nutritional status by dual X-Ray absorptiometry in women with rheumatoid arthritis: A case-control study. Medicine (Baltimore). Feb 2019; 98(6): e14361. PMID 30732168
  2. Sinclair M, Hoermann R, Peterson A, et al. Use of Dual X-ray Absorptiometry in men with advanced cirrhosis to predict sarcopenia-associated mortality risk. Liver Int. Jun 2019; 39(6): 1089-1097. PMID 30746903
  3. Lindqvist C, Brismar TB, Majeed A, et al. Assessment of muscle mass depletion in chronic liver disease: Dual-energy x-ray absorptiometry compared with computed tomography. Nutrition. May 2019; 61: 93-
  4. PMID 30703575
  5. Dordevic AL, Bonham M, Ghasem-Zadeh A, et al. Reliability of Compartmental Body Composition Measures in Weight-Stable Adults Using GE iDXA: Implications for Research and Practice. Nutrients. Oct 12 2018; 10(10). PMID 30321991
  6. Bazzocchi A, Ponti F, Cariani S, et al. Visceral fat and body composition changes in a female population after RYGBP: a two-year follow-up by DXA. Obes Surg. Mar 2015; 25(3): 443-51. PMID 25218013
  7. Franzoni E, Ciccarese F, Di Pietro E, et al. Follow-up of bone mineral density and body composition in adolescents with restrictive anorexia nervosa: role of dual-energy X-ray absorptiometry. Eur J Clin Nutr. Feb 2014; 68(2): 247-52. PMID 24346474
  8. Iyengar NM, Arthur R, Manson JE, et al. Association of Body Fat and Risk of Breast Cancer in Postmenopausal Women with Normal Body Mass Index: A Secondary Analysis of a Randomized Clinical Trial and Observational Study. JAMA Oncol. Feb 01 2019; 5(2): 155-163. PMID 30520976
  9. Ashby-Thompson M, Heshka S, Rizkalla B, et al. Validity of dual-energy x-ray absorptiometry for estimation of visceral adipose tissue and visceral adipose tissue change after surgery-induced weight loss in women with severe obesity. Obesity (Silver Spring). May 2022; 30(5): 1057-1065. PMID 35384351
  10. Sherlock SP, Palmer J, Wagner KR, et al. Dual-energy X-ray absorptiometry measures of lean body mass as a biomarker for progression in boys with Duchenne muscular dystrophy. Sci Rep. Nov 05 2022; 12(1): 18762. PMID 36335191
  11. Nguyen AL, Herath M, Burns M, et al. The value of whole-body dual-energy x-ray absorptiometry in assessing body composition in patients with inflammatory bowel disease: a prospective study. Eur J Gastroenterol Hepatol. Jan 01 2024; 36(1): 52-61. PMID 37942750
  12. Arthur RS, Xue X, Kamensky V, et al. The association between DXA-derived body fat measures and breast cancer risk among postmenopausal women in the Women's Health Initiative. Cancer Med. Feb 2020; 9(4): 1581-1599. PMID 31875358
  13. Garvey WT, Mechanick JI, Brett EM, et al. AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS AND AMERICAN COLLEGE OF ENDOCRINOLOGY COMPREHENSIVE CLINICAL PRACTICE GUIDELINES FOR MEDICAL CARE OF PATIENTS WITH OBESITY. Endocr Pract. Jul 2016; 22 Suppl 3: 1-203. PMID 27219496
  14. American College of Radiology. ACR-SPR-SSR Practice Parameter for the Performance of Dual- Energy X-ray Absorptiometry (DXA). 2018; https://gravitas.acr.org/PPTS/DownloadPreviewDocument?DocId=48. Accessed July 20, 2025.
  15. International Society for Clinical Densitometry. 2019 ISCD Official Positions - Adult. 2019; https://iscd.org/wp-content/uploads/2021/09/2019-Official-Positions-Adult-1.pdf. Accessed July 20, 2025.
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