Warning: fopen(/home/virtual/enm-kes/journal/upload/ip_log/ip_log_2024-03.txt): failed to open stream: Permission denied in /home/virtual/lib/view_data.php on line 88 Warning: fwrite() expects parameter 1 to be resource, boolean given in /home/virtual/lib/view_data.php on line 89 Dual-Energy X-Ray Absorptiometry: Beyond Bone Mineral Density Determination
Skip Navigation
Skip to contents

Endocrinol Metab : Endocrinology and Metabolism

clarivate
OPEN ACCESS
SEARCH
Search

Articles

Page Path
HOME > Endocrinol Metab > Volume 31(1); 2016 > Article
Review Article
Dual-Energy X-Ray Absorptiometry: Beyond Bone Mineral Density Determination
Yong Jun Choiorcid
Endocrinology and Metabolism 2016;31(1):25-30.
DOI: https://doi.org/10.3803/EnM.2016.31.1.25
Published online: March 16, 2016

Department of Endocrinology and Metabolism, Ajou University School of Medicine, Suwon, Korea.

Corresponding author: Yong Jun Choi. Department of Endocrinology and Metabolism, Ajou University School of Medicine, 164 World cup-ro, Yeongtong-gu, Suwon 16499, Korea. Tel: +82-31-219-4491, Fax: +82-31-219-4497, colsmile@hanmail.net
• Received: December 24, 2015   • Revised: January 15, 2016   • Accepted: January 21, 2016

Copyright © 2016 Korean Endocrine Society

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • 4,269 Views
  • 72 Download
  • 35 Web of Science
  • 29 Crossref
  • 39 Scopus
  • Significant improvements in dual-energy X-ray absorptiometry (DXA) concerning quality, image resolution and image acquisition time have allowed the development of various functions. DXA can evaluate bone quality by indirect analysis of micro- and macro-architecture of the bone, which and improve the prediction of fracture risk. DXA can also detect existing fractures, such as vertebral fractures or atypical femur fractures, without additional radiologic imaging and radiation exposure. Moreover, it can assess the metabolic status by the measurement of body composition parameters like muscle mass and visceral fat. Although more studies are required to validate and clinically use these parameters, it is clear that DXA is not just for bone mineral densitometry.
Dual-energy X-ray absorptiometry (DXA) is indispensable for clinical practice in osteoporosis. DXA is the reference method for measuring bone mineral density (BMD) at the lumbar spine and proximal femur [1]. However, bone strength mostly reflects the integration of bone density and bone quality. BMD accounts for only 70% of bone strength [2]. Refinements in image quality, resolution and acquisition time, combined with more advanced computation power, have extended the utility of DXA from BMD to other functions [3]. It can evaluate bone quality by indirect analysis of micro- and macro-architecture of the bone, which improves the prediction of fracture risk. DXA can also detect existing fractures, such as vertebral and atypical femur fractures (AFFs), without additional radiologic imaging and radiation exposure. As a third example, it can assess the metabolic status by the measurement of body composition [13]. This paper adds to the list, by detailing another application of DXA.
Hip structural analysis
DXA allows the measurement of geometric contributions to bone strength in the proximal femur, which is termed hip structural or hip strength analysis (HSA). HSA programs are commercially available can automatically assess structural variables including femoral neck cross-sectional moment of inertia (CSMI), cross-sectional area (CSA), femoral neck shaft angle, and hip axis length (HAL). In addition, models that combine these structural parameters with age, height, and weight allow the calculation of the femur strength index (FSI), which is a measure of the ability of a hip to withstand a fall on the greater trochanter [4].
The proximal femur remodels itself with age by redistributing bone mass; this mechanically compensates for the declining mass to preserve strength in bending [5]. CSMI reflects the distribution of the mass about a neutral or centroidal axis. The section modulus (Z) is a strength parameter based on the CSMI. Z is a physical property of a section that is inversely related to the maximum bending stress in the section, making it an index of the strength of the section. Z is equal to the CSMI divided by the centroidal distance or distance from the neutral axis to the outermost edge of the section, which in the case of bone, is the subperiosteal surface. Cortical instability may result when excessive cortical thinning is present. This can occur even with redistribution of the remaining mass toward the periphery of the cross-section. This is reflected in the final strength parameter, the buckling ratio (BR; the ratio of the outer radius to the cortical thickness). A ratio >10 indicates the heightened chance of a precipitous loss of strength with local buckling [6]. HSA with DXA enables the in vivo measurement of the CSA, CSMI, Z, and BR [7].
HAL is another geometric measure proposed as an indicator of hip fracture risk for females independent of BMD at the femoral neck. An increase in HAL equivalent to one standard deviation (SD) was associated with a 1.8-fold increase in the risk of hip fracture in women enrolled in the Study of Osteoporotic Fractures [8]. The proprietary FSI was statistically significantly lower in the fractured women compared to the controls. This was true even after adjustment of the FSI for BMD and HAL [4].
HSA with DXA has provided unique insights into the mechanisms of the pathophysiology of osteoporotic fracture. However, the HAS structural parameters are highly correlated with BMD and while predictive of fracture risk, are not currently better predictors of fracture risk. The major limitations of HSA with DXA primarily reflect limitations imposed by the two-dimensional (2D) nature of DXA [5].
Trabecular bone score
Trabecular bone score (TBS) is one the most recently developed diagnostic tools using DXA that could be important in osteoporosis. Micro-architectural deterioration of bone tissue contributes to bone fragility and susceptibility to fracture as low bone mass [9]. Several novel imaging techniques that include quantitative computed tomography (QCT) and high resolution (peripheral) QCT, and minimally invasive approaches for probing bone material properties have been tried to evaluate micro-architectural properties of bone tissue. However, none of these modalities shows better performance than BMD in the prediction of the various types of osteoporotic fractures, and their lack of availability and validation in the clinical setting means that an adjunctive role alongside DXA-measured BMD is unlikely to be feasible in the near future [10]. However, TBS is a novel imaging technique, based on standard DXA images that could prove to be a useful index of bone texture to provide skeletal information in addition to the standard BMD results [11]. TBS uses experimental variograms of 2D projection images, quantifying variation in grey-level texture from pixel to the adjacent pixels. TBS is not a direct measurement of bone microarchitecture but it is related to bone characteristics that include trabecular number, trabecular separation and the connectivity density [1213]. An elevated TBS indicates a strong and fracture-resistant microarchitecture. A low TBS reflects weak, fracture-prone microarchitecture [10]. Another advantage of TBS is that it can be obtained by re-analysis of past lumbar spine DXA images without taking another scans, which allows prior data to be used. The usefulness of TBS in osteoporosis is becoming increasingly clear. Low TBS is associated with both a history of fracture and incidence of new fracture [1012141516]. The effect is independent of BMD and is of sufficient magnitude to enhance risk stratification with BMD. The effect is also partly independent of the World Health Organization fracture risk assessment tool (FRAX), with likely greatest utility for those individuals who lie close to an intervention threshold [1017]. TBS adjusted FRAX probabilities were developed using the Manitoba data [18]. A recent meta-analysis validated this tool and suggested that TBS would have clinical utility, for example in the reclassification of those close to intervention thresholds [16]. A number of smaller investigations have suggested a role for TBS in specific causes of increased fracture risk, such as glucocorticoid excess and type 2 diabetes [101920]. The TBS program is commercially available as TBS iNsight software (Medimap, Geneva, Switzerland) and can be used after installation as an add-on program to the current DXA-operating program.
Vertebral fracture assessment
The presence of vertebral fractures (VFs) suggests that the patient is at increased risk for subsequent osteoporotic fractures. Patients with VFs have a 5-fold increased risk for additional VFs and about 3-fold increased risk for proximal femoral fractures [21]. However, only 30% of VFs are clinically recognized [22]. Standard radiography of the thoracic and lumbar spine is the reference method for detecting VFs, but it cannot be used routinely because of cost and radiation exposure considerations [1]. Vertebral fracture assessment (VFA) is potentially a clinically useful alternative to standard spine radiography for VF identification. Radiation exposure is low, about 3 to 8 micro Sieverts (mSv), compared to 700 to 800 mSv for a lateral radiograph of the lumbar and thoracic spine. Additionally, VFA has the convenience of being done at the same time and location as measurement of BMD by DXA, allowing integration of the two major risk factors for fracture (BMD and prior fracture) in clinical decisions. The digital images can be easily stored and compared as patients are followed-up over time [23].
The fracture-grading method devised by Genant et al. [24] is the most widely used for VFA as standard radiography. The anterior, middle and posterior height of each vertebral body (T7 to L4) are visually estimated on the lateral films. Deformities are graded according to their severity: grade 0 (<20% deformity); grade 1, mild deformities (20% to 25% deformity); grade 2, moderate deformities (25% to 40% deformity); and grade 3, severe deformities (≥40% deformity) [24]. Vertebral height is measured on VFA images manually or automatically using software, but these measurements should be used only for research purposes and not for clinical practice, as vertebral height does not differentiate between VFs and vertebral deformities due to other causes [1]. VFA sensitivity and specificity have been compared to radiographs in studies of postmenopausal women. VFA is an accurate imaging technique to identify grade 2 and 3 fractures in postmenopausal women being evaluated for osteoporosis including those with osteopenia [23252627282930]. Standard spine radiographs possess similar limitations in the accurate identification of grade 1 fractures, patients with scoliosis [2327] and at vertebrae above the level of T7 [232627]. Therefore, VFA is a reliable alternative to spine radiographs for the identification of VFs in postmenopausal women [23].
Detection of atypical femur fracture
Atypical subtrochanteric and diaphyseal fracture (AFF) is a serious complication in patients with osteoporosis, especially for those on prolonged bisphosphonate (BP) therapy. The absolute risk of AFFs in patients on BP therapy is low, ranging from 3.2 to 50 cases per 100,000 person-years. However, long-term use may be associated with higher risk (~100 per 100,000 person-years) [31]. The burden of BP-associated fractures is significant. In-patient hospital stay is lengthy and the injury and its treatment are associated with significant complications [32]. Therefore, early detection of prefracture lesions is important for the prevention of impending subtrochanteric fracture [3334]. Recently, a Korean study reported that assessment of hip DXA images combined with conventional assessment of prodromal symptoms enables detection of more AFFs earlier than assessment based on prodromal symptoms alone [35]. In 2013, the United States Food and Drug Administration (USFDA) approved using the latest generation of Hologic densitometers for detection of radiological changes of AFF. Clinical routine application will require additional studies [3].
Application in sarcopenia
Significant progress in the acquisition time of DXA (5 to 10 minutes) has enabled the rapid assessment of whole body composition or of a region of the body based on whole-body imaging. The measurement of body composition by DXA is a particularly attractive feature because of its noninvasive nature, low cost and very low irradiation (2.6 to 75 mSV) compared to other techniques including computed tomography (CT) and magnetic resonance imaging [13]. One of the applications of body composition assessment is the diagnosis of sarcopenia, an age-related muscle mass decline for which several definitions have been suggested. The European Working Group on Sarcopenia in Older People developed a definition based on three criteria: low muscle mass as measured using DXA or bioimpedence analysis, low muscle strength and low physical performance [136]. Skeletal muscle index (SMI) is usually used for muscle mass computed as the ratio of appendicular skeletal muscle mass over height squared [37]. SMI values more than SDs below values in young individuals generally indicate low muscle mass [1]. Measurements of body composition by DXA are expanding in many fields, such as for evaluation of lipodystrophy in human immunodeficiency virus patients and changes in lean mass in athletes. At present, body composition assessment is reserved for research and is not in routine clinical use [13].
Visceral fat measurement
Abdominal fat (AF) is associated with increased morbidity, independent of age, race, and sex [38]. Increase in visceral AF is particularly important, since it significantly contributes to many metabolic abnormalities associated with body weight gain [3940414243]. Anthropometric measurements such as body mass index, waist circumference and waist-to-hip ratio are commonly used in large epidemiologic studies. However, these measurements actually assess total AF, and therefore cannot differentiate between visceral AF and subcutaneous AF. A newly developed fully automated method for segmenting AF into subcutaneous AF and visceral AF within the android region using DXA has been approved for clinical use by the USFDA [44]. Additional commercial software (CoreScan or Hologic's InnerCore, GE Healthcare, Chicago, IL, USA) is required to measure VF. Technical performance of DXA VF has been demonstrated in both American and Chinese populations. These studies showed a high correlation and small average difference between DXA and CT [4445]. Recently, a Korean study showed that VF measured by DXA is highly correlated with the VF measured by CT and could be a reliable estimate of VF in Korean population [46]. However, additional studies are required for its clinical routine application.
The significant improvements in DXA on the quality, resolution of the images and acquisition time have allowed the development of variable functions. With the evaluation of bone quality by indirect analysis of micro- and macro-architecture, such as HSA and TBS, may improve the prediction of fracture risk. It may also replace or gradually replace conventional radiology with VFA or detection of AF. Moreover, it can assess the metabolic status by the measurement of the whole body composition, such as muscle mass and VF.

CONFLICTS OF INTEREST: No potential conflict of interest relevant to this article was reported.

  • 1. Briot K. DXA parameters: beyond bone mineral density. Joint Bone Spine 2013;80:265–269. ArticlePubMed
  • 2. NIH Consensus Development Panel on Osteoporosis Prevention, Diagnosis, and Therapy. Osteoporosis prevention, diagnosis, and therapy. JAMA 2001;285:785–795. ArticlePubMed
  • 3. Gonzalez Rodriguez E, Favre L, Lamy O, Pralong F, Hans D. DXA imaging: the multifunction Swiss army knife? Rev Med Suisse 2015;11:645–650. PubMed
  • 4. Faulkner KG, Wacker WK, Barden HS, Simonelli C, Burke PK, Ragi S, et al. Femur strength index predicts hip fracture independent of bone density and hip axis length. Osteoporos Int 2006;17:593–599. ArticlePubMedPDF
  • 5. Bonnick SL. HSA: beyond BMD with DXA. Bone 2007;41(1 Suppl 1):S9–S12. ArticlePubMed
  • 6. Roark RJ, Young WC. Roark's formulas for stress and strain; 6th ed. New York: McGraw-Hill; 1989. p. 688.
  • 7. Szulc P, Duboeuf F, Schott AM, Dargent-Molina P, Meunier PJ, Delmas PD. Structural determinants of hip fracture in elderly women: re-analysis of the data from the EPIDOS study. Osteoporos Int 2006;17:231–236. ArticlePubMedPDF
  • 8. Martin RB, Burr DB. Non-invasive measurement of long bone cross-sectional moment of inertia by photon absorptiometry. J Biomech 1984;17:195–201. ArticlePubMed
  • 9. Consensus development conference: diagnosis, prophylaxis, and treatment of osteoporosis. Am J Med 1993;94:646–650. ArticlePubMed
  • 10. Harvey NC, Gluer CC, Binkley N, McCloskey EV, Brandi ML, Cooper C, et al. Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice. Bone 2015;78:216–224. ArticlePubMedPMC
  • 11. Silva BC, Leslie WD, Resch H, Lamy O, Lesnyak O, Binkley N, et al. Trabecular bone score: a noninvasive analytical method based upon the DXA image. J Bone Miner Res 2014;29:518–530. ArticlePubMed
  • 12. Hans D, Goertzen AL, Krieg MA, Leslie WD. Bone microarchitecture assessed by TBS predicts osteoporotic fractures independent of bone density: the Manitoba study. J Bone Miner Res 2011;26:2762–2769. ArticlePubMed
  • 13. Winzenrieth R, Michelet F, Hans D. Three-dimensional (3D) microarchitecture correlations with 2D projection image gray-level variations assessed by trabecular bone score using high-resolution computed tomographic acquisitions: effects of resolution and noise. J Clin Densitom 2013;16:287–296. ArticlePubMed
  • 14. Nassar K, Paternotte S, Kolta S, Fechtenbaum J, Roux C, Briot K. Added value of trabecular bone score over bone mineral density for identification of vertebral fractures in patients with areal bone mineral density in the non-osteoporotic range. Osteoporos Int 2014;25:243–249. ArticlePubMedPDF
  • 15. Iki M, Tamaki J, Kadowaki E, Sato Y, Dongmei N, Winzenrieth R, et al. Trabecular bone score (TBS) predicts vertebral fractures in Japanese women over 10 years independently of bone density and prevalent vertebral deformity: the Japanese Population-Based Osteoporosis (JPOS) cohort study. J Bone Miner Res 2014;29:399–407. ArticlePubMed
  • 16. McCloskey EV, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H, et al. A meta-analysis of trabecular bone score in fracture risk prediction and its relationship to FRAX. J Bone Miner Res 2015 10 24 [Epub]. Article
  • 17. Leslie WD, Johansson H, Kanis JA, Lamy O, Oden A, McCloskey EV, et al. Lumbar spine texture enhances 10-year fracture probability assessment. Osteoporos Int 2014;25:2271–2277. ArticlePubMedPDF
  • 18. McCloskey EV, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H, et al. Adjusting fracture probability by trabecular bone score. Calcif Tissue Int 2015;96:500–509. ArticlePubMedPDF
  • 19. Eller-Vainicher C, Morelli V, Ulivieri FM, Palmieri S, Zhukouskaya VV, Cairoli E, et al. Bone quality, as measured by trabecular bone score in patients with adrenal incidentalomas with and without subclinical hypercortisolism. J Bone Miner Res 2012;27:2223–2230. ArticlePubMed
  • 20. Leslie WD, Aubry-Rozier B, Lamy O, Hans D. Manitoba Bone Density Program. TBS (trabecular bone score) and diabetes-related fracture risk. J Clin Endocrinol Metab 2013;98:602–609. ArticlePubMed
  • 21. Black DM, Arden NK, Palermo L, Pearson J, Cummings SR. Prevalent vertebral deformities predict hip fractures and new vertebral deformities but not wrist fractures. Study of Osteoporotic Fractures Research Group. J Bone Miner Res 1999;14:821–828. ArticlePubMed
  • 22. Link TM, Guglielmi G, van Kuijk C, Adams JE. Radiologic assessment of osteoporotic vertebral fractures: diagnostic and prognostic implications. Eur Radiol 2005;15:1521–1532. ArticlePubMedPDF
  • 23. Laster AJ, Lewiecki EM. ISCD Board of Directors. Vertebral fracture assessment by dual-energy X-ray absorptiometry: insurance coverage issues in the United States. A White Paper of the International Society for Clinical Densitometry. J Clin Densitom 2007;10:227–238. ArticlePubMed
  • 24. Genant HK, Li J, Wu CY, Shepherd JA. Vertebral fractures in osteoporosis: a new method for clinical assessment. J Clin Densitom 2000;3:281–290. ArticlePubMed
  • 25. Gehlbach SH, Bigelow C, Heimisdottir M, May S, Walker M, Kirkwood JR. Recognition of vertebral fracture in a clinical setting. Osteoporos Int 2000;11:577–582. ArticlePubMedPDF
  • 26. Ferrar L, Jiang G, Eastell R, Peel NF. Visual identification of vertebral fractures in osteoporosis using morphometric X-ray absorptiometry. J Bone Miner Res 2003;18:933–938. ArticlePubMed
  • 27. Schousboe JT, Debold CR. Reliability and accuracy of vertebral fracture assessment with densitometry compared to radiography in clinical practice. Osteoporos Int 2006;17:281–289. ArticlePubMedPDF
  • 28. Rea JA, Li J, Blake GM, Steiger P, Genant HK, Fogelman I. Visual assessment of vertebral deformity by X-ray absorptiometry: a highly predictive method to exclude vertebral deformity. Osteoporos Int 2000;11:660–668. ArticlePubMedPDF
  • 29. Binkley N, Krueger D, Gangnon R, Genant HK, Drezner MK. Lateral vertebral assessment: a valuable technique to detect clinically significant vertebral fractures. Osteoporos Int 2005;16:1513–1518. ArticlePubMedPDF
  • 30. Wu C, Genant HK, von Ingersleben G, Chen Y, Johnston C, Econs M, et al. Validation of lateral DXA imaging for assessment of vertebral fractures. J Bone Miner Res 2004;19(Suppl 1):S295.
  • 31. Shane E, Burr D, Abrahamsen B, Adler RA, Brown TD, Cheung AM, et al. Atypical subtrochanteric and diaphyseal femoral fractures: second report of a task force of the American Society for Bone and Mineral Research. J Bone Miner Res 2014;29:1–23. ArticlePubMed
  • 32. Shkolnikova J, Flynn J, Choong P. Burden of bisphosphonate-associated femoral fractures. ANZ J Surg 2013;83:175–181. ArticlePubMed
  • 33. Ahlman MA, Rissing MS, Gordon L. Evolution of bisphosphonate-related atypical fracture retrospectively observed with DXA scanning. J Bone Miner Res 2012;27:496–498. ArticlePubMed
  • 34. McKiernan FE. Atypical femoral diaphyseal fractures documented by serial DXA. J Clin Densitom 2010;13:102–103. ArticlePubMed
  • 35. Kim S, Yang KH, Lim H, Lee YK, Yoon HK, Oh CW, et al. Detection of prefracture hip lesions in atypical subtrochanteric fracture with dual-energy X-ray absorptiometry images. Radiology 2014;270:487–495. ArticlePubMed
  • 36. Cooper C, Dere W, Evans W, Kanis JA, Rizzoli R, Sayer AA, et al. Frailty and sarcopenia: definitions and outcome parameters. Osteoporos Int 2012;23:1839–1848. ArticlePubMedPDF
  • 37. Baumgartner RN, Koehler KM, Gallagher D, Romero L, Heymsfield SB, Ross RR, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998;147:755–763. ArticlePubMedPDF
  • 38. Okosun IS, Liao Y, Rotimi CN, Prewitt TE, Cooper RS. Abdominal adiposity and clustering of multiple metabolic syndrome in White, Black and Hispanic americans. Ann Epidemiol 2000;10:263–270. ArticlePubMed
  • 39. You T, Ryan AS, Nicklas BJ. The metabolic syndrome in obese postmenopausal women: relationship to body composition, visceral fat, and inflammation. J Clin Endocrinol Metab 2004;89:5517–5522. ArticlePubMed
  • 40. Ding J, Visser M, Kritchevsky SB, Nevitt M, Newman A, Sutton-Tyrrell K, et al. The association of regional fat depots with hypertension in older persons of white and African American ethnicity. Am J Hypertens 2004;17:971–976. ArticlePubMedPDF
  • 41. Albu JB, Murphy L, Frager DH, Johnson JA, Pi-Sunyer FX. Visceral fat and race-dependent health risks in obese nondiabetic premenopausal women. Diabetes 1997;46:456–462. ArticlePubMed
  • 42. Ross R, Aru J, Freeman J, Hudson R, Janssen I. Abdominal adiposity and insulin resistance in obese men. Am J Physiol Endocrinol Metab 2002;282:E657–E663. ArticlePubMed
  • 43. Ross R, Fortier L, Hudson R. Separate associations between visceral and subcutaneous adipose tissue distribution, insulin and glucose levels in obese women. Diabetes Care 1996;19:1404–1411. ArticlePubMed
  • 44. Kaul S, Rothney MP, Peters DM, Wacker WK, Davis CE, Shapiro MD, et al. Dual-energy X-ray absorptiometry for quantification of visceral fat. Obesity (Silver Spring) 2012;20:1313–1318. ArticlePubMedPMC
  • 45. Lin H, Yan H, Rao S, Xia M, Zhou Q, Xu H, et al. Quantification of visceral adipose tissue using lunar dual-energy X-ray absorptiometry in Asian Chinese. Obesity (Silver Spring) 2013;21:2112–2117. ArticlePubMed
  • 46. Choi YJ, Seo YK, Lee EJ, Chung YS. Quantification of visceral fat using dual-energy X-ray absorptiometry and its reliability according to the amount of visceral fat in Korean adults. J Clin Densitom 2015;18:192–197. ArticlePubMed

Figure & Data

References

    Citations

    Citations to this article as recorded by  
    • Seated push-up tests: Reliable and valid measures for older individuals when used by primary healthcare providers
      Pakwipa Chokphukiao, Puttipong Poncumhak, Thiwabhorn Thaweewannakij, Roongnapa Intaruk, Sugalya Amatachaya
      Journal of Back and Musculoskeletal Rehabilitation.2023; 36(4): 871.     CrossRef
    • The mandibular bone structure in children by fractal dimension and its correlation with pixel intensity values: a pilot study
      Beatriz Fernandes Arrepia, Thaiza Gonçalves Rocha, Annie Seabra Medeiros, Matheus Diniz Ferreira, Andrea Fonseca-Gonçalves, Maria Augusta Visconti
      Oral Radiology.2023; 39(4): 771.     CrossRef
    • Phase Angle, Inflammation, and Sarcopenia in Late Postoperative Roux-En-Y Gastric Bypass
      Gisele Florêncio, Aglécio Souza, Elinton Chaim, Allan Santos, Louise Duran, Camila Carvalho, Sarah Monte Alegre
      Journal of Clinical Medicine.2023; 12(15): 5124.     CrossRef
    • Obesity history, physical exam, laboratory, body composition, and energy expenditure: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2022
      Karlijn Burridge, Sandra M. Christensen, Angela Golden, Amy B. Ingersoll, Justin Tondt, Harold E. Bays
      Obesity Pillars.2022; 1: 100007.     CrossRef
    • Body Composition as a Modulator of Bone Health Changes in Patients with Inflammatory Bowel Disease
      Iulia Soare, Anca Sirbu, Miruna Popa, Sorina Martin, Cristian George Tieranu, Bogdan Mateescu, Mircea Diculescu, Carmen Barbu, Simona Fica
      Life.2022; 12(2): 272.     CrossRef
    • Deep learning for screening primary osteopenia and osteoporosis using spine radiographs and patient clinical covariates in a Chinese population
      Liting Mao, Ziqiang Xia, Liang Pan, Jun Chen, Xian Liu, Zhiqiang Li, Zhaoxian Yan, Gengbin Lin, Huisen Wen, Bo Liu
      Frontiers in Endocrinology.2022;[Epub]     CrossRef
    • Validity and feasibility of using a seated push-up test among community-dwelling older adults
      Puttipong Poncumhak, Supaporn Phadungkit, Pakwipa Chokphukiao, Roongnapa Intaruk, Pipatana Amatachaya, Sugalya Amatachaya
      Hong Kong Physiotherapy Journal.2022; 42(02): 125.     CrossRef
    • Calcium status assessment at the population level: Candidate approaches and challenges
      Ziaul H. Rana, Megan W. Bourassa, Filomena Gomes, Anuradha Khadilkar, Rubina Mandlik, Victor Owino, John M. Pettifor, Daniel E. Roth, Julie Shlisky, Prashanth Thankachan, Connie M. Weaver
      Annals of the New York Academy of Sciences.2022; 1517(1): 93.     CrossRef
    • Does the Severity of Obesity Influence Bone Mineral Density Values in Premenopausal Women?
      Emneh Hammoud, Hechmi Toumi, Christophe Jacob, Antonio Pinti, Eric Lespessailles, Rawad El Hage
      Journal of Clinical Densitometry.2021; 24(2): 225.     CrossRef
    • Uremic Sarcopenia and Its Possible Nutritional Approach
      Annalisa Noce, Giulia Marrone, Eleonora Ottaviani, Cristina Guerriero, Francesca Di Daniele, Anna Pietroboni Zaitseva, Nicola Di Daniele
      Nutrients.2021; 13(1): 147.     CrossRef
    • Effect of Tissue-Selective Estrogen Complex on Hip Structural Geometry in Postmenopausal Women: A 12-Month Study
      Bo Mi Kim, Sung Eun Kim, Dong-Yun Lee, DooSeok Choi
      Frontiers in Endocrinology.2021;[Epub]     CrossRef
    • A Core Omnigenic Non-coding Trait Governing Dex-Induced Osteoporotic Effects Identified Without DEXA
      Li Lu, Yanzhen Cai, Xiaoling Luo, Zhangting Wang, Sin Hang Fung, Huanhuan Jia, Chi Lam Yu, Wai Yee Chan, Kai Kei Miu, Wende Xiao
      Frontiers in Pharmacology.2021;[Epub]     CrossRef
    • Association between rs12742784 polymorphism and hip fracture, bone mineral density, and EPHB2 mRNA expression levels in elderly Chinese women
      Z. Ruan, Y. Zhu, Z. Lin, H. Long, R. Zhao, B. Sun, L. Cheng, S. Zhao
      Climacteric.2020; 23(1): 93.     CrossRef
    • The Performance of a Calcaneal Quantitative Ultrasound Device, CM-200, in Stratifying Osteoporosis Risk among Malaysian Population Aged 40 Years and Above
      Shaanthana Subramaniam, Chin-Yi Chan, Ima Nirwana Soelaiman, Norazlina Mohamed, Norliza Muhammad, Fairus Ahmad, Pei-Yuen Ng, Nor Aini Jamil, Noorazah Abd Aziz, Kok-Yong Chin
      Diagnostics.2020; 10(4): 178.     CrossRef
    • Influence of sarcopenia on bone health parameters in a group of eumenorrheic obese premenopausal women
      Emneh Hammoud, Hechmi Toumi, Christophe Jacob, Antonio Pinti, Eric Lespessailles, Rawad El Hage
      Journal of Bone and Mineral Metabolism.2020; 38(3): 385.     CrossRef
    • Sex differences in disease activity and efficacy of treatment in spondyloarthritis: is body composition the cause?
      Sebastián Ibáñez Vodnizza, Irene van der Horst-Bruinsma
      Current Opinion in Rheumatology.2020; 32(4): 337.     CrossRef
    • The Effect of Self-Reported Lactose Intolerance and Dairy Consumption on Bone Mineral Density among American Hip Arthroplasty Patients: A Cross-Sectional Study
      Nikola K. Hamilton, Omorogieva Ojo, Amanda Rodrigues Amorim Adegboye
      International Journal of Environmental Research and Public Health.2020; 17(19): 7182.     CrossRef
    • A Prospective, Controlled, Multicenter Study to Evaluate the Clinical Outcome of Implant Treatment in Women with Osteoporosis/Osteopenia: 5-Year Results
      A. Temmerman, L. Rasmusson, A. Kübler, A. Thor, J. Merheb, M. Quirynen
      Journal of Dental Research.2019; 98(1): 84.     CrossRef
    • Assessment of BMD and Statistical Analysis for Osteoporosis Detection
      S. M. Nazia Fathima, R. Tamil Selvi, M. Parisa Beham
      Biomedical and Pharmacology Journal.2019; 12(04): 1907.     CrossRef
    • The association between CD31hiEmcnhi endothelial cells and bone mineral density in Chinese women
      Yong Zhu, Zhe Ruan, Zhangyuan Lin, Haitao Long, Ruibo Zhao, Buhua Sun, Liang Cheng, Lanhua Tang, Zhuying Xia, Changjun Li, Shushan Zhao
      Journal of Bone and Mineral Metabolism.2019; 37(6): 987.     CrossRef
    • Body composition in patients with chronic obstructive pulmonary disease
      E. V. Bolotova, A. V. Dudnikova, V. V. Yavlyanskaya
      Russian Pulmonology.2018; 28(4): 453.     CrossRef
    • Fat Mass Lowers the Response to Tumor Necrosis Factor-α Blockers in Patients with Ankylosing Spondylitis
      Sebastián E. Ibáñez Vodnizza, Michael T. Nurmohamed, Ingrid M. Visman, J. Christiaan van Denderen, Willem F. Lems, Francisca Jaime, Irene E. van der Horst–Bruinsma
      The Journal of Rheumatology.2017; 44(9): 1355.     CrossRef
    • Articles inEndocrinology and Metabolismin 2016
      Won-Young Lee
      Endocrinology and Metabolism.2017; 32(1): 62.     CrossRef
    • Muscle wasting in male TNF-α blocker naïve ankylosing spondylitis patients: a comparison of gender differences in body composition
      Sebastián Ibáñez Vodnizza, Ingrid M. Visman, Christiaan van Denderen, Willem F. Lems, Francisca Jaime, Michael T. Nurmohamed, Irene E. van der Horst-Bruinsma
      Rheumatology.2017; 56(9): 1566.     CrossRef
    • Measurement of lean body mass using bioelectrical impedance analysis: a consideration of the pros and cons
      Giuseppe Sergi, Marina De Rui, Brendon Stubbs, Nicola Veronese, Enzo Manzato
      Aging Clinical and Experimental Research.2017; 29(4): 591.     CrossRef
    • Comparisons of TBS and lumbar spine BMD in the associations with vertebral fractures according to the T-scores: A cross-sectional observation
      Jie-Eun Lee, Kyoung Min Kim, Lee-Kyung Kim, Kyong Young Kim, Tae Jung Oh, Jae Hoon Moon, Sung Hee Choi, Soo Lim, Sang Wan Kim, Chan Soo Shin, Hak Chul Jang
      Bone.2017; 105: 269.     CrossRef
    • The Influence of Tribological Pairings and Other Factors on Migration Patterns of Short Stems in Total Hip Arthroplasty
      Thilo Floerkemeier, Michael Schwarze, Christof Hurschler, Jens Gronewold, Henning Windhagen, Gabriela von Lewinski, Stefan Budde
      BioMed Research International.2017; 2017: 1.     CrossRef
    • Associations Between Fat Mass and Multisite Pain: A Five‐Year Longitudinal Study
      Feng Pan, Laura Laslett, Leigh Blizzard, Flavia Cicuttini, Tania Winzenberg, Changhai Ding, Graeme Jones
      Arthritis Care & Research.2017; 69(4): 509.     CrossRef
    • Serum CX3CL1/fractalkine concentrations are positively associated with disease severity in postmenopausal osteoporotic patients
      Yi-Ding Chen, Ci-You Huang, Hai-Ying Liu, Wei-Feng Yao, Wei-guo Wu, Yu-Lian Lu, Wen Wang
      British Journal of Biomedical Science.2016; 73(3): 121.     CrossRef

    • PubReader PubReader
    • Cite
      CITE
      export Copy
      Close
    • XML DownloadXML Download

    Endocrinol Metab : Endocrinology and Metabolism