Subscribe to RSS
Please copy the URL and add it into your RSS Feed Reader.
https://www.thieme-connect.de/rss/thieme/en/10.1055-s-00000070.xml
Download PDF
Semin Musculoskelet Radiol 2020; 24(04): 375-385
DOI: 10.1055/s-0040-1708824
DOI: 10.1055/s-0040-1708824
Review Article
Quantitative Imaging of Body Composition
Funding Martin Torriani was funded in part by the National Institutes of Health Nutrition and Obesity Research Center at Harvard (P30 DK040561).
Abstract
Body composition refers to the amount and distribution of lean tissue, adipose tissue, and bone in the human body. Lean tissue primarily consists of skeletal muscle; adipose tissue comprises mostly abdominal visceral adipose tissue and abdominal and nonabdominal subcutaneous adipose tissue. Hepatocellular and myocellular lipids are also fat pools with important metabolic implications. Importantly, body composition reflects generalized processes such as increased adiposity in obesity and age-related loss of muscle mass known as sarcopenia.
In recent years, body composition has been extensively studied quantitatively to predict overall health. Multiple imaging methods have allowed precise estimates of tissue types and provided insights showing the relationship of body composition to varied pathologic conditions. In this review article, we discuss different imaging methods used to quantify body composition and describe important anatomical locations where target tissues can be measured.
Keywords
body composition - dual-energy X-ray absorptiometry - magnetic resonance imaging - computed tomography - quantitative imagingPublication History
Article published online:
29 September 2020
© 2020. Thieme. All rights reserved.
Thieme Medical Publishers
333 Seventh Avenue, New York, NY 10001, USA.
-
References
- 1 Visser M, Goodpaster BH, Kritchevsky SB. , et al. Muscle mass, muscle strength, and muscle fat infiltration as predictors of incident mobility limitations in well-functioning older persons. J Gerontol A Biol Sci Med Sci 2005; 60 (03) 324-333
- 2 Marcus RL, Addison O, Kidde JP, Dibble LE, Lastayo PC. Skeletal muscle fat infiltration: impact of age, inactivity, and exercise. J Nutr Health Aging 2010; 14 (05) 362-366
- 3 Shachar SS, Williams GR, Muss HB, Nishijima TF. Prognostic value of sarcopenia in adults with solid tumours: a meta-analysis and systematic review. Eur J Cancer 2016; 57: 58-67
- 4 Kamarajah SK, Bundred J, Tan BHL. Body composition assessment and sarcopenia in patients with gastric cancer: a systematic review and meta-analysis. Gastric Cancer 2019; 22 (01) 10-22
- 5 Vrieling A, Kampman E, Knijnenburg NC. , et al. Body composition in relation to clinical outcomes in renal cell cancer: a systematic review and meta-analysis. Eur Urol Focus 2018; 4 (03) 420-434
- 6 Boshier PR, Heneghan R, Markar SR, Baracos VE, Low DE. Assessment of body composition and sarcopenia in patients with esophageal cancer: a systematic review and meta-analysis. Dis Esophagus 2018;31(08):
- 7 Deluche E, Leobon S, Desport JC, Venat-Bouvet L, Usseglio J, Tubiana-Mathieu N. Impact of body composition on outcome in patients with early breast cancer. Support Care Cancer 2018; 26 (03) 861-868
- 8 Rossi F, Valdora F, Bignotti B, Torri L, Succio G, Tagliafico AS. Evaluation of body computed tomography-determined sarcopenia in breast cancer patients and clinical outcomes: a systematic review. Cancer Treat Res Commun 2019; 21: 100154
- 9 Oliveira A, Vaz C. The role of sarcopenia in the risk of osteoporotic hip fracture. Clin Rheumatol 2015; 34 (10) 1673-1680
- 10 Chang C-D, Wu JS, Mhuircheartaigh JN. , et al. Effect of sarcopenia on clinical and surgical outcome in elderly patients with proximal femur fractures. Skeletal Radiol 2018; 47 (06) 771-777
- 11 Yoo T, Lo WD, Evans DC. Computed tomography measured psoas density predicts outcomes in trauma. Surgery 2017; 162 (02) 377-384
- 12 Li Y, Liu B, Li Y. , et al. Epicardial fat tissue in patients with diabetes mellitus: a systematic review and meta-analysis. Cardiovasc Diabetol 2019; 18 (01) 3
- 13 Borga M, West J, Bell JD. , et al. Advanced body composition assessment: from body mass index to body composition profiling. J Investig Med 2018; 66 (05) 1-9
- 14 Garg MK, Kharb S. Dual energy X-ray absorptiometry: pitfalls in measurement and interpretation of bone mineral density. Indian J Endocrinol Metab 2013; 17 (02) 203-210
- 15 Fourman LT, Kileel EM, Hubbard J. , et al. Comparison of visceral fat measurement by dual-energy X-ray absorptiometry to computed tomography in HIV and non-HIV. Nutr Diabetes 2019; 9 (01) 6
- 16 Bredella MA, Gill CM, Keating LK. , et al. Assessment of abdominal fat compartments using DXA in premenopausal women from anorexia nervosa to morbid obesity. Obesity (Silver Spring) 2013; 21 (12) 2458-2464
- 17 Rutten IJG, van Dijk DPJ, Kruitwagen RFPM, Beets-Tan RG, Olde Damink SW, van Gorp T. Loss of skeletal muscle during neoadjuvant chemotherapy is related to decreased survival in ovarian cancer patients. J Cachexia Sarcopenia Muscle 2016; 7 (04) 458-466
- 18 Goodpaster BH, Kelley DE, Thaete FL, He J, Ross R. Skeletal muscle attenuation determined by computed tomography is associated with skeletal muscle lipid content. J Appl Physiol (1985) 2000; 89 (01) 104-110
- 19 Kramer H, Pickhardt PJ, Kliewer MA. , et al. Accuracy of liver fat quantification with advanced CT, MRI, and ultrasound techniques: prospective comparison with MR spectroscopy. AJR Am J Roentgenol 2017; 208 (01) 92-100
- 20 Brown JC, Cespedes Feliciano EM, Caan BJ. The evolution of body composition in oncology-epidemiology, clinical trials, and the future of patient care: facts and numbers. J Cachexia Sarcopenia Muscle 2018; 9 (07) 1200-1208
- 21 Chung H, Cobzas D, Birdsell L. , et al. (2009) Automated segmentation of muscle and adipose tissue on CT images for human body composition analysis. In: Miga MI, Wong KH. , ed. Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling. Bellingham, WA: SPIE; 2009: 72610K
- 22 Weston AD, Korfiatis P, Kline TL. , et al. Automated abdominal segmentation of CT scans for body composition analysis using deep learning. Radiology 2019; 290 (03) 669-679
- 23 Wang Y, Qiu Y, Thai T, Moore K, Liu H, Zheng B. A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images. Comput Methods Programs Biomed 2017; 144: 97-104
- 24 Lee H, Troschel FM, Tajmir S. , et al. Pixel-level deep segmentation: artificial intelligence quantifies muscle on computed tomography for body morphometric analysis. J Digit Imaging 2017; 30 (04) 487-498
- 25 Hemke R, Buckless CG, Tsao A. , et al. Deep learning for automated segmentation of pelvic muscles, fat, and bone from CT studies for body composition assessment. Skeletal Radiol 2020; 49 (03) 387-395
- 26 Shen W, Punyanitya M, Wang Z. , et al. Total body skeletal muscle and adipose tissue volumes: estimation from a single abdominal cross-sectional image. J Appl Physiol (1985) 2004; 97 (06) 2333-2338
- 27 Derstine BA, Holcombe SA, Ross BE, Wang NC, Su GL, Wang SC. Skeletal muscle cutoff values for sarcopenia diagnosis using T10 to L5 measurements in a healthy US population. Sci Rep 2018; 8 (01) 11369
- 28 Irlbeck T, Massaro JM, Bamberg F, O'Donnell CJ, Hoffmann U, Fox CS. Association between single-slice measurements of visceral and abdominal subcutaneous adipose tissue with volumetric measurements: the Framingham Heart Study. Int J Obes 2010; 34 (04) 781-787
- 29 Faron A, Luetkens JA, Schmeel FC, Kuetting DLR, Thomas D, Sprinkart AM. Quantification of fat and skeletal muscle tissue at abdominal computed tomography: associations between single-slice measurements and total compartment volumes. Abdom Radiol (NY) 2019; 44 (05) 1907-1916
- 30 Dabiri S, Popuri K, Cespedes Feliciano EM, Caan BJ, Baracos VE, Beg MF. Muscle segmentation in axial computed tomography (CT) images at the lumbar (L3) and thoracic (T4) levels for body composition analysis. Comput Med Imaging Graph 2019; 75: 47-55
- 31 Murray TÉ, Williams D, Lee MJ. Osteoporosis, obesity, and sarcopenia on abdominal CT: a review of epidemiology, diagnostic criteria, and management strategies for the reporting radiologist. Abdom Radiol (NY) 2017; 42 (09) 2376-2386
- 32 Tong Y, Udupa JK, Torigian DA. , et al. Chest fat quantification via CT based on standardized anatomy space in adult lung transplant candidates. PLOS One 2017; 12 (01) e0168932
- 33 Hu HH, Chen J, Shen W. Segmentation and quantification of adipose tissue by magnetic resonance imaging. MAGMA 2016; 29 (02) 259-276
- 34 Dixon WT. Simple proton spectroscopic imaging. Radiology 1984; 153 (01) 189-194
- 35 Reeder SB, Hu HH, Sirlin CB. Proton density fat-fraction: a standardized MR-based biomarker of tissue fat concentration. J Magn Reson Imaging 2012; 36 (05) 1011-1014
- 36 Gu J, Liu S, Du S. , et al. Diagnostic value of MRI-PDFF for hepatic steatosis in patients with non-alcoholic fatty liver disease: a meta-analysis. Eur Radiol 2019; 29 (07) 3564-3573
- 37 Lee K, Shin Y, Huh J. , et al. Recent issues on body composition imaging for sarcopenia evaluation. Korean J Radiol 2019; 20 (02) 205-217
- 38 Gloor M, Fasler S, Fischmann A. , et al. Quantification of fat infiltration in oculopharyngeal muscular dystrophy: comparison of three MR imaging methods. J Magn Reson Imaging 2011; 33 (01) 203-210
- 39 Baum T, Cordes C, Dieckmeyer M. , et al. MR-based assessment of body fat distribution and characteristics. Eur J Radiol 2016; 85 (08) 1512-1518
- 40 Boesch C, Kreis R. Observation of intramyocellular lipids by 1H-magnetic resonance spectroscopy. Ann N Y Acad Sci 2000; 904: 25-31
- 41 Karampinos DC, Ruschke S, Dieckmeyer M. , et al. Quantitative MRI and spectroscopy of bone marrow. J Magn Reson Imaging 2018; 47 (02) 332-353
- 42 Torriani M. Measuring muscle lipids with 1H-MR spectroscopy. Skeletal Radiol 2007; 36 (07) 607-608
- 43 Torriani M, Thomas BJ, Halpern EF, Jensen ME, Rosenthal DI, Palmer WE. Intramyocellular lipid quantification: repeatability with 1H MR spectroscopy. Radiology 2005; 236 (02) 609-614
- 44 Torriani M, Thomas BJ, Bredella MA, Ouellette H. Intramyocellular lipid quantification: comparison between 3.0- and 1.5-T (1)H-MRS. Magn Reson Imaging 2007; 25 (07) 1105-1111
- 45 Bredella MA, Torriani M, Thomas BJ. , et al. Peak growth hormone-releasing hormone-arginine-stimulated growth hormone is inversely associated with intramyocellular and intrahepatic lipid content in premenopausal women with obesity. J Clin Endocrinol Metab 2009; 94 (10) 3995-4002
- 46 Torriani M, Thomas BJ, Barlow RB, Librizzi J, Dolan S, Grinspoon S. Increased intramyocellular lipid accumulation in HIV-infected women with fat redistribution. J Appl Physiol (1985) 2006; 100 (02) 609-614
- 47 Bredella MA, Ghomi RH, Thomas BJ. , et al. Breath-hold 1H-magnetic resonance spectroscopy for intrahepatic lipid quantification at 3 Tesla. J Comput Assist Tomogr 2010; 34 (03) 372-376
- 48 Dichtel LE, Eajazi A, Miller KK, Torriani M, Bredella MA. Short- and long-term reproducibility of intrahepatic lipid quantification by 1H-MR spectroscopy and CT in obesity. J Comput Assist Tomogr 2016; 40 (05) 678-682
- 49 Braun LR, Feldpausch MN, Czerwonka N. , et al. Effects of Pitavastatin on insulin sensitivity and liver fat: A randomized clinical trial. J Clin Endocrinol Metab 2018; 103 (11) 4176-4186
- 50 Stanley TL, Feldpausch MN, Oh J. , et al. Effect of tesamorelin on visceral fat and liver fat in HIV-infected patients with abdominal fat accumulation: a randomized clinical trial. JAMA 2014; 312 (04) 380-389
- 51 Bredella MA, Gerweck AV, Lin E. , et al. Effects of GH on body composition and cardiovascular risk markers in young men with abdominal obesity. J Clin Endocrinol Metab 2013; 98 (09) 3864-3872
- 52 Bredella MA, Fazeli PK, Daley SM. , et al. Marrow fat composition in anorexia nervosa. Bone 2014; 66: 199-204
- 53 Yu EW, Greenblatt L, Eajazi A, Torriani M, Bredella MA. Marrow adipose tissue composition in adults with morbid obesity. Bone 2017; 97: 38-42
- 54 Singhal V, Miller KK, Torriani M, Bredella MA. Short- and long-term reproducibility of marrow adipose tissue quantification by 1H-MR spectroscopy. Skeletal Radiol 2016; 45 (02) 221-225
- 55 Sampath SC, Sampath SC, Bredella MA, Cypess AM, Torriani M. Imaging of brown adipose tissue: state of the art. Radiology 2016; 280 (01) 4-19
- 56 Chu K, Bos SA, Gill CM. , et al. Brown adipose tissue and cancer progression. Skeletal Radiol 2020; 49 (04) 635-639
- 57 Bredella MA, Gill CM, Rosen CJ, Klibanski A, Torriani M. Positive effects of brown adipose tissue on femoral bone structure. Bone 2014; 58: 55-58
- 58 Oliveira AL, Azevedo DC, Bredella MA, Stanley TL, Torriani M. Visceral and subcutaneous adipose tissue FDG uptake by PET/CT in metabolically healthy obese subjects. Obesity (Silver Spring) 2015; 23 (02) 286-289
- 59 Veld J, O'Donnell EK, Reagan MR. , et al. Abdominal adipose tissue in MGUS and multiple myeloma. Skeletal Radiol 2016; 45 (09) 1277-1283
- 60 Boutin RD, Yao L, Canter RJ, Lenchik L. Sarcopenia: current concepts and imaging implications. AJR Am J Roentgenol 2015; 205 (03) W255-66
- 61 Bundred J, Kamarajah SK, Roberts KJ. Body composition assessment and sarcopenia in patients with pancreatic cancer: a systematic review and meta-analysis. HPB (Oxford) 2019; 21 (12) 1603-1612
- 62 Troschel AS, Troschel FM, Best TD. , et al. Computed tomography-based body composition analysis and its role in lung cancer care. J Thorac Imaging 2020; 35 (02) 91-100
- 63 Chang KV, Chen JD, Wu WT, Huang KC, Hsu CT, Han DS. Association between loss of skeletal muscle mass and mortality and tumor recurrence in hepatocellular carcinoma: a systematic review and meta-analysis. Liver Cancer 2018; 7 (01) 90-103
- 64 Zhang H, Lin S, Gao T. , et al. Association between sarcopenia and metabolic syndrome in middle-aged and older non-obese adults: a systematic review and meta-analysis. Nutrients 2018; 10 (03) 10
- 65 Chang K-V, Hsu T-H, Wu W-T, Huang KC, Han DS. Is sarcopenia associated with depression? A systematic review and meta-analysis of observational studies. Age Ageing 2017; 46 (05) 738-746
- 66 Sternby H, Mahle M, Linder N. , et al. Mean muscle attenuation correlates with severe acute pancreatitis unlike visceral adipose tissue and subcutaneous adipose tissue. United European Gastroenterol J 2019; 7 (10) 1312-1320
- 67 Sebro R, O'Brien L, Torriani M, Bredella MA. Assessment of trunk muscle density using CT and its association with degenerative disc and facet joint disease of the lumbar spine. Skeletal Radiol 2016; 45 (09) 1221-1226
- 68 Fox CS, Massaro JM, Hoffmann U. , et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation 2007; 116 (01) 39-48
- 69 Britton KA, Fox CS. Ectopic fat depots and cardiovascular disease. Circulation 2011; 124 (24) e837-e841
- 70 Mancio J, Azevedo D, Saraiva F. , et al. Epicardial adipose tissue volume assessed by computed tomography and coronary artery disease: a systematic review and meta-analysis. Eur Heart J Cardiovasc Imaging 2018; 19 (05) 490-497
- 71 Bettencourt N, Toschke AM, Leite D. , et al. Epicardial adipose tissue is an independent predictor of coronary atherosclerotic burden. Int J Cardiol 2012; 158 (01) 26-32
- 72 Wang C-P, Hsu H-L, Hung W-C. , et al. Increased epicardial adipose tissue (EAT) volume in type 2 diabetes mellitus and association with metabolic syndrome and severity of coronary atherosclerosis. Clin Endocrinol (Oxf) 2009; 70 (06) 876-882
- 73
Yerramasu A,
Dey D,
Venuraju S.
, et al.
Increased volume of epicardial fat is an independent risk factor for accelerated progression
of sub-clinical coronary atherosclerosis. Atherosclerosis 2012; 220 (01) 223-230
MissingFormLabel
- 74 Pierdomenico SD, Pierdomenico AM, Cuccurullo F, Iacobellis G. Meta-analysis of the relation of echocardiographic epicardial adipose tissue thickness and the metabolic syndrome. Am J Cardiol 2013; 111 (01) 73-78
- 75 Nerlekar N, Brown AJ, Muthalaly RG. , et al. Association of epicardial adipose tissue and high-risk plaque characteristics: a systematic review and meta-analysis. J Am Heart Assoc 2017; 6 (08) 6
- 76 Franssens BT, Nathoe HM, Visseren FLJJ, van der Graaf Y, Leiner T. SMART Study Group. Relation of epicardial adipose tissue radiodensity to coronary artery calcium on cardiac computed tomography in patients at high risk for cardiovascular disease. Am J Cardiol 2017; 119 (09) 1359-1365
- 77 Nakamori S, Nezafat M, Ngo LH, Manning WJ, Nezafat R. Left atrial epicardial fat volume is associated with atrial fibrillation: a prospective cardiovascular magnetic resonance 3D Dixon study. J Am Heart Assoc 2018; 7 (06) 7
- 78 Al-Talabany S, Mordi I, Graeme Houston J. , et al. Epicardial adipose tissue is related to arterial stiffness and inflammation in patients with cardiovascular disease and type 2 diabetes. BMC Cardiovasc Disord 2018; 18 (01) 31
- 79 Iacobellis G, Gao Y-J, Sharma AM. Do cardiac and perivascular adipose tissue play a role in atherosclerosis?. Curr Diab Rep 2008; 8 (01) 20-24
- 80 Shah RV, Anderson A, Ding J. , et al. Pericardial, but not hepatic, fat by CT is associated with CV outcomes and structure: the multi-ethnic study of atherosclerosis. JACC Cardiovasc Imaging 2017; 10 (09) 1016-1027
- 81 Alman AC, Smith SR, Eckel RH. , et al. The ratio of pericardial to subcutaneous adipose tissues is associated with insulin resistance. Obesity (Silver Spring) 2017; 25 (07) 1284-1291
- 82 Todd A, Satriano A, Fenwick K. , et al. Intra-thoracic adiposity is associated with impaired contractile function in patients with coronary artery disease: a cardiovascular magnetic resonance imaging study. Int J Cardiovasc Imaging 2019; 35 (01) 121-131
- 83 Tsaban G, Wolak A, Avni-Hassid H. , et al. Dynamics of intrapericardial and extrapericardial fat tissues during long-term, dietary-induced, moderate weight loss. Am J Clin Nutr 2017; 106 (04) 984-995
- 84 Bak SH, Kwon SO, Han SS, Kim WJ. Computed tomography-derived area and density of pectoralis muscle associated disease severity and longitudinal changes in chronic obstructive pulmonary disease: a case control study. Respir Res 2019; 20 (01) 226
- 85 Cho YH, Do KH, Chae EJ. , et al. Association of chest CT-based quantitative measures of muscle and fat with post-lung transplant survival and morbidity: a single institutional retrospective cohort study in Korean population. Korean J Radiol 2019; 20 (03) 522-530
- 86 Snijder MB, Visser M, Dekker JM. , et al; Health ABC Study. Low subcutaneous thigh fat is a risk factor for unfavourable glucose and lipid levels, independently of high abdominal fat. The Health ABC Study. Diabetologia 2005; 48 (02) 301-308
- 87 Schorr M, Dichtel LE, Gerweck AV. , et al. Sex differences in body composition and association with cardiometabolic risk. Biol Sex Differ 2018; 9 (01) 28
- 88 Manolopoulos KN, Karpe F, Frayn KN. Gluteofemoral body fat as a determinant of metabolic health. Int J Obes 2010; 34 (06) 949-959
- 89 Grimaldi A, Richardson C, Stanton W, Durbridge G, Donnelly W, Hides J. The association between degenerative hip joint pathology and size of the gluteus medius, gluteus minimus and piriformis muscles. Man Ther 2009; 14 (06) 605-610
- 90 Ten Dam L, van der Kooi AJ, Rövekamp F, Linssen WH, de Visser M. Comparing clinical data and muscle imaging of DYSF and ANO5 related muscular dystrophies. Neuromuscul Disord 2014; 24 (12) 1097-1102
- 91 Woodley SJ, Nicholson HD, Livingstone V. , et al. Lateral hip pain: findings from magnetic resonance imaging and clinical examination. J Orthop Sports Phys Ther 2008; 38 (06) 313-328
- 92 Grimby G, Kvist H, Grangård U. Reduction in thigh muscle cross-sectional area and strength in a 4-year follow-up in late polio. Arch Phys Med Rehabil 1996; 77 (10) 1044-1048
- 93 Pfirrmann CWA, Notzli HP, Dora C, Hodler J, Zanetti M. Abductor tendons and muscles assessed at MR imaging after total hip arthroplasty in asymptomatic and symptomatic patients. Radiology 2005; 235 (03) 969-976
- 94 Pedroso MG, de Almeida AC, Aily JB, de Noronha M, Mattiello SM. Fatty infiltration in the thigh muscles in knee osteoarthritis: a systematic review and meta-analysis. Rheumatol Int 2019; 39 (04) 627-635
- 95 Khoja SS, Patterson CG, Goodpaster BH, Delitto A, Piva SR. Skeletal muscle fat in individuals with rheumatoid arthritis compared to healthy adults. Exp Gerontol 2020; 129: 110768
- 96 Slattery MJ, Bredella MA, Thakur H, Torriani M, Misra M. Insulin resistance and impaired mitochondrial function in obese adolescent girls. Metab Syndr Relat Disord 2014; 12 (01) 56-61
- 97 Savage DB, Watson L, Carr K. , et al. Accumulation of saturated intramyocellular lipid is associated with insulin resistance. J Lipid Res 2019; 60 (07) 1323-1332
- 98 Boss A, Kreis R, Jenni S. , et al. Noninvasive assessment of exercise-related intramyocellular acetylcarnitine in euglycemia and hyperglycemia in patients with type 1 diabetes using 1H magnetic resonance spectroscopy: a randomized single-blind crossover study. Diabetes Care 2011; 34 (01) 220-222