Skip to main content
Erschienen in: European Radiology 11/2022

18.04.2022 | Musculoskeletal

Deep learning–based fully automated body composition analysis of thigh CT: comparison with DXA measurement

verfasst von: Hye Jin Yoo, Young Jae Kim, Hyunsook Hong, Sung Hwan Hong, Hee Dong Chae, Ja-Young Choi

Erschienen in: European Radiology | Ausgabe 11/2022

Einloggen, um Zugang zu erhalten

Abstract

Objectives

To compare volumetric CT with DL-based fully automated segmentation and dual-energy X-ray absorptiometry (DXA) in the measurement of thigh tissue composition.

Methods

This prospective study was performed from January 2019 to December 2020. The participants underwent DXA to determine the body composition of the whole body and thigh. CT was performed in the thigh region; the images were automatically segmented into three muscle groups and adipose tissue by custom-developed DL-based automated segmentation software. Subsequently, the program reported the tissue composition of the thigh. The correlation and agreement between variables measured by DXA and CT were assessed. Then, CT thigh tissue volume prediction equations based on DXA-derived thigh tissue mass were developed using a general linear model.

Results

In total, 100 patients (mean age, 44.9 years; 60 women) were evaluated. There was a strong correlation between the CT and DXA measurements (R = 0.813~0.98, p < 0.001). There was no significant difference in total soft tissue mass between DXA and CT measurement (p = 0.183). However, DXA overestimated thigh lean (muscle) mass and underestimated thigh total fat mass (p < 0.001). The DXA-derived lean mass was an average of 10% higher than the CT-derived lean mass and 47% higher than the CT-derived lean muscle mass. The DXA-derived total fat mass was approximately 20% lower than the CT-derived total fat mass. The predicted CT tissue volume using DXA-derived data was highly correlated with actual CT-measured tissue volume in the validation group (R2 = 0.96~0.97, p < 0.001).

Conclusions

Volumetric CT measurements with DL-based fully automated segmentation are a rapid and more accurate method for measuring thigh tissue composition.

Key Points

• There was a positive correlation between CT and DXA measurements in both the whole body and thigh.
• DXA overestimated thigh lean mass by 10%, lean muscle mass by 47%, but underestimated total fat mass by 20% compared to the CT method.
• The equations for predicting CT volume (cm 3 ) were developed using DXA data (g), age, height (cm), and body weight (kg) and good model performance was proven in the validation study.
Literatur
1.
Zurück zum Zitat Wolfe RR (2006) The underappreciated role of muscle in health and disease. Am J Clin Nutr 84:475–482CrossRef Wolfe RR (2006) The underappreciated role of muscle in health and disease. Am J Clin Nutr 84:475–482CrossRef
2.
Zurück zum Zitat Tavoian D, Ampomah K, Amano S, Law TD, Clark BC (2019) Changes in DXA-derived lean mass and MRI-derived cross-sectional area of the thigh are modestly associated. Sci Rep 9:10028CrossRef Tavoian D, Ampomah K, Amano S, Law TD, Clark BC (2019) Changes in DXA-derived lean mass and MRI-derived cross-sectional area of the thigh are modestly associated. Sci Rep 9:10028CrossRef
3.
Zurück zum Zitat Lee K, Shin Y, Huh J et al (2019) Recent issues on body composition imaging for sarcopenia evaluation. Korean J Radiol 20:205–217CrossRef Lee K, Shin Y, Huh J et al (2019) Recent issues on body composition imaging for sarcopenia evaluation. Korean J Radiol 20:205–217CrossRef
4.
Zurück zum Zitat Boutin RD, Yao L, Canter RJ, Lenchik L (2015) Sarcopenia: current concepts and imaging implications. AJR Am J Roentgenol 205:W255–W266CrossRef Boutin RD, Yao L, Canter RJ, Lenchik L (2015) Sarcopenia: current concepts and imaging implications. AJR Am J Roentgenol 205:W255–W266CrossRef
5.
Zurück zum Zitat Ruhdorfer A, Wirth W, Eckstein F (2015) Relationship between isometric thigh muscle strength and minimum clinically important differences in knee function in osteoarthritis: data from the osteoarthritis initiative. Arthritis Care Res 67:509–518CrossRef Ruhdorfer A, Wirth W, Eckstein F (2015) Relationship between isometric thigh muscle strength and minimum clinically important differences in knee function in osteoarthritis: data from the osteoarthritis initiative. Arthritis Care Res 67:509–518CrossRef
6.
Zurück zum Zitat Ruhdorfer A, Wirth W, Eckstein F (2017) Association of knee pain with a reduction in thigh muscle strength – a cross-sectional analysis including 4553 osteoarthritis initiative participants. Osteoarthritis Cartilage 25:658–666 Ruhdorfer A, Wirth W, Eckstein F (2017) Association of knee pain with a reduction in thigh muscle strength – a cross-sectional analysis including 4553 osteoarthritis initiative participants. Osteoarthritis Cartilage 25:658–666
7.
Zurück zum Zitat Segal NA, Torner JC, Felson D et al (2009) Effect of thigh strength on incident radiographic and symptomatic knee osteoarthritis in a longitudinal cohort. Arthritis Rheum 61:1210–1217CrossRef Segal NA, Torner JC, Felson D et al (2009) Effect of thigh strength on incident radiographic and symptomatic knee osteoarthritis in a longitudinal cohort. Arthritis Rheum 61:1210–1217CrossRef
8.
Zurück zum Zitat Segal NA, Glass NA, Torner J et al (2010) Quadriceps weakness predicts risk for knee joint space narrowing in women in the MOST cohort. Osteoarthritis Cartilage 18:769–775 Segal NA, Glass NA, Torner J et al (2010) Quadriceps weakness predicts risk for knee joint space narrowing in women in the MOST cohort. Osteoarthritis Cartilage 18:769–775
9.
Zurück zum Zitat Øiestad BE, Juhl CB, Eitzen I, Thorlund JB (2015) Knee extensor muscle weakness is a risk factor for development of knee osteoarthritis. A systematic review and meta-analysis. Osteoarthritis Cartilage 23:171–177 Øiestad BE, Juhl CB, Eitzen I, Thorlund JB (2015) Knee extensor muscle weakness is a risk factor for development of knee osteoarthritis. A systematic review and meta-analysis. Osteoarthritis Cartilage 23:171–177
10.
Zurück zum Zitat Culvenor AG, Wirth W, Ruhdorfer A, Eckstein F (2016) Thigh muscle strength predicts knee replacement risk independent of radiographic disease and pain in women: data from the osteoarthritis initiative. Arthritis Rheumatol 68:1145-1155 Culvenor AG, Wirth W, Ruhdorfer A, Eckstein F (2016) Thigh muscle strength predicts knee replacement risk independent of radiographic disease and pain in women: data from the osteoarthritis initiative. Arthritis Rheumatol 68:1145-1155
11.
Zurück zum Zitat Levine JA, Abboud L, Barry M, Reed JE, Sheedy PF (1985) Jensen MD (2000) Measuring leg muscle and fat mass in humans: comparison of CT and dual-energy X-ray absorptiometry. J Appl Physiol (1985) 88:452–456 Levine JA, Abboud L, Barry M, Reed JE, Sheedy PF (1985) Jensen MD (2000) Measuring leg muscle and fat mass in humans: comparison of CT and dual-energy X-ray absorptiometry. J Appl Physiol (1985) 88:452–456
12.
Zurück zum Zitat Engelke K, Museyko O, Wang L, Laredo JD (2018) Quantitative analysis of skeletal muscle by computed tomography imaging-State of the art. J Orthop Translat 15:91–103CrossRef Engelke K, Museyko O, Wang L, Laredo JD (2018) Quantitative analysis of skeletal muscle by computed tomography imaging-State of the art. J Orthop Translat 15:91–103CrossRef
13.
Zurück zum Zitat Kim TN, Park MS, Lee EJ et al (2017) Comparisons of three different methods for defining sarcopenia: an aspect of cardiometabolic risk. Sci Rep 7:6491CrossRef Kim TN, Park MS, Lee EJ et al (2017) Comparisons of three different methods for defining sarcopenia: an aspect of cardiometabolic risk. Sci Rep 7:6491CrossRef
14.
Zurück zum Zitat Bredella MA, Ghomi RH, Thomas BJ et al (2010) Comparison of DXA and CT in the assessment of body composition in premenopausal women with obesity and anorexia nervosa. Obesity (Silver Spring) 18:2227–2233CrossRef Bredella MA, Ghomi RH, Thomas BJ et al (2010) Comparison of DXA and CT in the assessment of body composition in premenopausal women with obesity and anorexia nervosa. Obesity (Silver Spring) 18:2227–2233CrossRef
15.
Zurück zum Zitat Visser M, Kritchevsky SB, Goodpaster BH et al (2002) Leg muscle mass and composition in relation to lower extremity performance in men and women aged 70 to 79: the health, aging and body composition study. J Am Geriatr Soc 50:897–904CrossRef Visser M, Kritchevsky SB, Goodpaster BH et al (2002) Leg muscle mass and composition in relation to lower extremity performance in men and women aged 70 to 79: the health, aging and body composition study. J Am Geriatr Soc 50:897–904CrossRef
16.
Zurück zum Zitat Davidson FE, Matsha TE, Erasmus RT, Ismail S, Kengne AP, Goedecke JH (2020) Comparison of single-slice CT and DXA-derived measures of central adiposity in South African women. Eur J Clin Nutr 74:1282–1289CrossRef Davidson FE, Matsha TE, Erasmus RT, Ismail S, Kengne AP, Goedecke JH (2020) Comparison of single-slice CT and DXA-derived measures of central adiposity in South African women. Eur J Clin Nutr 74:1282–1289CrossRef
17.
Zurück zum Zitat Hansen RD, Williamson DA, Finnegan TP et al (2007) Estimation of thigh muscle cross-sectional area by dual-energy X-ray absorptiometry in frail elderly patients. Am J Clin Nutr 86:952–958CrossRef Hansen RD, Williamson DA, Finnegan TP et al (2007) Estimation of thigh muscle cross-sectional area by dual-energy X-ray absorptiometry in frail elderly patients. Am J Clin Nutr 86:952–958CrossRef
18.
Zurück zum Zitat Wang W, Wang Z, Faith MS, Kotler D, Shih R (1985) Heymsfield SB (1999) Regional skeletal muscle measurement: evaluation of new dual-energy X-ray absorptiometry model. J Appl Physiol (1985) 87:1163–1171 Wang W, Wang Z, Faith MS, Kotler D, Shih R (1985) Heymsfield SB (1999) Regional skeletal muscle measurement: evaluation of new dual-energy X-ray absorptiometry model. J Appl Physiol (1985) 87:1163–1171
19.
Zurück zum Zitat Wang ZM, Visser M, Ma R et al (1985) (1996) Skeletal muscle mass: evaluation of neutron activation and dual-energy X-ray absorptiometry methods. J Appl Physiol (1985) 80:824–831 Wang ZM, Visser M, Ma R et al (1985) (1996) Skeletal muscle mass: evaluation of neutron activation and dual-energy X-ray absorptiometry methods. J Appl Physiol (1985) 80:824–831
20.
Zurück zum Zitat Ding J, Cao P, Chang HC, Gao Y, Chan SHS, Vardhanabhuti V (2020) Deep learning-based thigh muscle segmentation for reproducible fat fraction quantification using fat-water decomposition MRI. Insights Imaging 11:128CrossRef Ding J, Cao P, Chang HC, Gao Y, Chan SHS, Vardhanabhuti V (2020) Deep learning-based thigh muscle segmentation for reproducible fat fraction quantification using fat-water decomposition MRI. Insights Imaging 11:128CrossRef
21.
Zurück zum Zitat Hiasa Y, Otake Y, Takao M, Ogawa T, Sugano N, Sato Y (2020) Automated muscle segmentation from clinical CT using Bayesian U-Net for personalized musculoskeletal modeling. IEEE Trans Med Imaging 39:1030–1040CrossRef Hiasa Y, Otake Y, Takao M, Ogawa T, Sugano N, Sato Y (2020) Automated muscle segmentation from clinical CT using Bayesian U-Net for personalized musculoskeletal modeling. IEEE Trans Med Imaging 39:1030–1040CrossRef
22.
Zurück zum Zitat Heymsfield SB, Smith R, Aulet M et al (1990) Appendicular skeletal muscle mass: measurement by dual-photon absorptiometry. Am J Clin Nutr 52:214–218CrossRef Heymsfield SB, Smith R, Aulet M et al (1990) Appendicular skeletal muscle mass: measurement by dual-photon absorptiometry. Am J Clin Nutr 52:214–218CrossRef
23.
Zurück zum Zitat Aubrey J, Esfandiari N, Baracos VE et al (2014) Measurement of skeletal muscle radiation attenuation and basis of its biological variation. Acta Physiol (Oxf) 210:489–497 Aubrey J, Esfandiari N, Baracos VE et al (2014) Measurement of skeletal muscle radiation attenuation and basis of its biological variation. Acta Physiol (Oxf) 210:489–497
24.
Zurück zum Zitat Yoshizumi T, Nakamura T, Yamane M et al (1999) Abdominal fat: standardized technique for measurement at CT. Radiology 211:283–286CrossRef Yoshizumi T, Nakamura T, Yamane M et al (1999) Abdominal fat: standardized technique for measurement at CT. Radiology 211:283–286CrossRef
25.
Zurück zum Zitat Visser M, Fuerst T, Lang T, Salamone L, Harris TB (1985) (1999) Validity of fan-beam dual-energy X-ray absorptiometry for measuring fat-free mass and leg muscle mass. Health, Aging, and Body Composition Study--Dual-Energy X-ray Absorptiometry and Body Composition Working Group. J Appl Physiol (1985) 87:1513–1520 Visser M, Fuerst T, Lang T, Salamone L, Harris TB (1985) (1999) Validity of fan-beam dual-energy X-ray absorptiometry for measuring fat-free mass and leg muscle mass. Health, Aging, and Body Composition Study--Dual-Energy X-ray Absorptiometry and Body Composition Working Group. J Appl Physiol (1985) 87:1513–1520
26.
Zurück zum Zitat Chowdhury B, Sjostrom L, Alpsten M, Kostanty J, Kvist H, Lofgren R (1994) A multicompartment body composition technique based on computerized tomography. Int J Obes Relat Metab Disord 18:219–234 Chowdhury B, Sjostrom L, Alpsten M, Kostanty J, Kvist H, Lofgren R (1994) A multicompartment body composition technique based on computerized tomography. Int J Obes Relat Metab Disord 18:219–234
27.
Zurück zum Zitat (1979) Report of the task group on reference man. Ann ICRP 3:iii. 10.1016/0146-6453(79)90123-4 (1979) Report of the task group on reference man. Ann ICRP 3:iii. 10.1016/0146-6453(79)90123-4
28.
Zurück zum Zitat Kim J, Shen W, Gallagher D et al (2006) Total-body skeletal muscle mass: estimation by dual-energy X-ray absorptiometry in children and adolescents. Am J Clin Nutr 84:1014–1020CrossRef Kim J, Shen W, Gallagher D et al (2006) Total-body skeletal muscle mass: estimation by dual-energy X-ray absorptiometry in children and adolescents. Am J Clin Nutr 84:1014–1020CrossRef
29.
Zurück zum Zitat Bland JM, Altman DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8:135–160CrossRef Bland JM, Altman DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8:135–160CrossRef
30.
Zurück zum Zitat Maden-Wilkinson TM, Degens H, Jones DA, McPhee JS (2013) Comparison of MRI and DXA to measure muscle size and age-related atrophy in thigh muscles. J Musculoskelet Neuronal Interact 13:320–328 Maden-Wilkinson TM, Degens H, Jones DA, McPhee JS (2013) Comparison of MRI and DXA to measure muscle size and age-related atrophy in thigh muscles. J Musculoskelet Neuronal Interact 13:320–328
31.
Zurück zum Zitat Euser AM, Dekker FW, le Cessie S (2008) A practical approach to Bland-Altman plots and variation coefficients for log transformed variables. J Clin Epidemiol 61:978–982CrossRef Euser AM, Dekker FW, le Cessie S (2008) A practical approach to Bland-Altman plots and variation coefficients for log transformed variables. J Clin Epidemiol 61:978–982CrossRef
32.
Zurück zum Zitat Brady SL, Trout AT, Somasundaram E, Anton CG, Li Y, Dillman JR (2021) Improving image quality and reducing radiation dose for pediatric CT by using deep learning reconstruction. Radiology 298:180–188CrossRef Brady SL, Trout AT, Somasundaram E, Anton CG, Li Y, Dillman JR (2021) Improving image quality and reducing radiation dose for pediatric CT by using deep learning reconstruction. Radiology 298:180–188CrossRef
33.
Zurück zum Zitat Mayo-Smith WW, Hara AK, Mahesh M, Sahani DV, Pavlicek W (2014) How I do it: managing radiation dose in CT. Radiology 273:657–672CrossRef Mayo-Smith WW, Hara AK, Mahesh M, Sahani DV, Pavlicek W (2014) How I do it: managing radiation dose in CT. Radiology 273:657–672CrossRef
34.
Zurück zum Zitat Kemnitz J, Baumgartner CF, Eckstein F et al (2020) Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain. MAGMA 33:483–493CrossRef Kemnitz J, Baumgartner CF, Eckstein F et al (2020) Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain. MAGMA 33:483–493CrossRef
Metadaten
Titel
Deep learning–based fully automated body composition analysis of thigh CT: comparison with DXA measurement
verfasst von
Hye Jin Yoo
Young Jae Kim
Hyunsook Hong
Sung Hwan Hong
Hee Dong Chae
Ja-Young Choi
Publikationsdatum
18.04.2022
Verlag
Springer Berlin Heidelberg
Erschienen in
European Radiology / Ausgabe 11/2022
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08770-y

Weitere Artikel der Ausgabe 11/2022

European Radiology 11/2022 Zur Ausgabe

Update Radiologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.