{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T03:48:18Z","timestamp":1772336898885,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,3,16]],"date-time":"2021-03-16T00:00:00Z","timestamp":1615852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Manual segmentation of muscle and adipose compartments from computed tomography (CT) axial images is a potential bottleneck in early rapid detection and quantification of sarcopenia. A prototype deep learning neural network was trained on a multi-center collection of 3413 abdominal cancer surgery subjects to automatically segment truncal muscle, subcutaneous adipose tissue and visceral adipose tissue at the L3 lumbar vertebral level. Segmentations were externally tested on 233 polytrauma subjects. Although after severe trauma abdominal CT scans are quickly and robustly delivered, with often motion or scatter artefacts, incomplete vertebral bodies or arms that influence image quality, the concordance was generally very good for the body composition indices of Skeletal Muscle Radiation Attenuation (SMRA) (Concordance Correlation Coefficient (CCC) = 0.92), Visceral Adipose Tissue index (VATI) (CCC = 0.99) and Subcutaneous Adipose Tissue Index (SATI) (CCC = 0.99). In conclusion, this article showed an automated and accurate segmentation system to segment the cross-sectional muscle and adipose area L3 lumbar spine level on abdominal CT. Future perspectives will include fine-tuning the algorithm and minimizing the outliers.<\/jats:p>","DOI":"10.3390\/s21062083","type":"journal-article","created":{"date-parts":[[2021,3,16]],"date-time":"2021-03-16T21:42:41Z","timestamp":1615930961000},"page":"2083","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients"],"prefix":"10.3390","volume":"21","author":[{"given":"Leanne L. G. C.","family":"Ackermans","sequence":"first","affiliation":[{"name":"Department of Traumatology, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"},{"name":"Department of Surgery, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"}]},{"given":"Leroy","family":"Volmer","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Development Biology, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1612-9055","authenticated-orcid":false,"given":"Leonard","family":"Wee","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Development Biology, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"},{"name":"Clinical Data Science, Faculty of Health Medicine and Lifesciences, Maastricht University, Paul Henri Spaaklaan 1, 6229 GT Maastricht, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9937-2602","authenticated-orcid":false,"given":"Ralph","family":"Brecheisen","sequence":"additional","affiliation":[{"name":"Department of Surgery, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9871-0884","authenticated-orcid":false,"given":"Patricia","family":"S\u00e1nchez-Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Biomedical Engineering and Telemedicine Centre, ETSI Telecomunicaci\u00f3n, Center for Biomedical Technology, Universidad Polit\u00e9cnica de Madrid, 28040 Madrid, Spain"},{"name":"Centro de Investigaci\u00f3n Biom\u00e9dica en Red de Bioingenier\u00eda, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7274-244X","authenticated-orcid":false,"given":"Alexander P.","family":"Seiffert","sequence":"additional","affiliation":[{"name":"Biomedical Engineering and Telemedicine Centre, ETSI Telecomunicaci\u00f3n, Center for Biomedical Technology, Universidad Polit\u00e9cnica de Madrid, 28040 Madrid, Spain"}]},{"given":"Enrique J.","family":"G\u00f3mez","sequence":"additional","affiliation":[{"name":"Biomedical Engineering and Telemedicine Centre, ETSI Telecomunicaci\u00f3n, Center for Biomedical Technology, Universidad Polit\u00e9cnica de Madrid, 28040 Madrid, Spain"},{"name":"Centro de Investigaci\u00f3n Biom\u00e9dica en Red de Bioingenier\u00eda, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0422-7996","authenticated-orcid":false,"given":"Andre","family":"Dekker","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Development Biology, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"},{"name":"Clinical Data Science, Faculty of Health Medicine and Lifesciences, Maastricht University, Paul Henri Spaaklaan 1, 6229 GT Maastricht, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6195-9704","authenticated-orcid":false,"given":"Jan A.","family":"Ten Bosch","sequence":"additional","affiliation":[{"name":"Department of Traumatology, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5202-9345","authenticated-orcid":false,"given":"Steven M. W.","family":"Olde Damink","sequence":"additional","affiliation":[{"name":"Department of Surgery, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"},{"name":"Department of General, Visceral and Transplantation Surgery, RWTH University Hospital Aachen, 52074 Aachen, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3601-3458","authenticated-orcid":false,"given":"Taco J.","family":"Blokhuis","sequence":"additional","affiliation":[{"name":"Department of Traumatology, Maastricht University Medical Centre+, 6229 HX Maastricht, The Netherlands"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1159\/000334879","article-title":"The evaluation of body composition: A useful tool for clinical practice","volume":"60","author":"Thibault","year":"2012","journal-title":"Ann. Nutr. 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