{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T19:57:15Z","timestamp":1792180635821,"version":"4.4.0"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"1164","license":[{"start":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T00:00:00Z","timestamp":1726531200000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000289","name":"Cancer Research UK","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000289","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Body composition assessment using CT images at the L3-level is increasingly applied in cancer research and has been shown to be strongly associated with long-term survival. Robust high-throughput automated segmentation is key to assess large patient cohorts and to support implementation of body composition analysis into routine clinical practice. We trained and externally validated a deep learning neural network (DLNN) to automatically segment L3-CT images.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Expert-drawn segmentations of visceral and subcutaneous adipose tissue (VAT\/SAT) and skeletal muscle (SM) of L3-CT-images of 3187 patients undergoing abdominal surgery were used to train a DLNN. The external validation cohort was comprised of 2535 patients with abdominal cancer. DLNN performance was evaluated with (geometric) dice similarity (DS) and Lin\u2019s concordance correlation coefficient.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>There was a strong concordance between automatic and manual segmentations with median DS for SM, VAT, and SAT of 0.97 (IQR: 0.95-0.98), 0.98 (IQR: 0.95-0.98), and 0.95 (IQR: 0.92-0.97), respectively. Concordance correlations were excellent: SM 0.964 (0.959-0.968), VAT 0.998 (0.998-0.998), and SAT 0.992 (0.991-0.993). Bland-Altman metrics indicated only small and clinically insignificant systematic offsets; SM radiodensity: 0.23 Hounsfield units (0.5%), SM: 1.26\u2009cm2.m\u22122 (2.8%), VAT: \u22121.02\u2009cm2.m\u22122 (1.7%), and SAT: 3.24\u2009cm2.m\u22122 (4.6%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>A robustly-performing and independently externally validated DLNN for automated body composition analysis was developed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Advances in knowledge<\/jats:title>\n                    <jats:p>This DLNN was successfully trained and externally validated on several large patient cohorts. The trained algorithm could facilitate large-scale population studies and implementation of body composition analysis into clinical practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bjr\/tqae191","type":"journal-article","created":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T13:32:13Z","timestamp":1726579933000},"page":"2015-2023","source":"Crossref","is-referenced-by-count":25,"title":["External validation of a deep learning model for automatic segmentation of skeletal muscle and adipose tissue on abdominal CT images"],"prefix":"10.1093","volume":"97","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2019-5402","authenticated-orcid":false,"given":"David P J","family":"van Dijk","sequence":"first","affiliation":[{"name":"Department of Surgery, Maastricht University Medical Center , Maastricht, 6200 MD,","place":["The Netherlands"]},{"name":"NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University , Maastricht, 6229 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Pancreatic Unit, Glasgow Royal Infirmary , Glasgow, Glasgow, G12 0YN,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David K","family":"Chang","sequence":"additional","affiliation":[{"name":"Wolfson Wohl Cancer Research Centre, School of Cancer Sciences, University of Glasgow , Glasgow, Glasgow, G61 1BD,","place":["United Kingdom"]},{"name":"West of Scotland Pancreatic Unit, Glasgow Royal Infirmary , Glasgow, Glasgow, G12 0YN,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donald C","family":"McMillan","sequence":"additional","affiliation":[{"name":"Academic Unit of Surgery, School of Medicine, University of Glasgow, Glasgow Royal Infirmary , Glasgow, Glasgow, G31 2ER,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan H M B","family":"Stoot","sequence":"additional","affiliation":[{"name":"Department of Surgery, Zuyderland Medical Centre , Geleen, 6162 BG,","place":["The Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Malcolm A","family":"West","sequence":"additional","affiliation":[{"name":"Academic Unit of Cancer Sciences, Faculty of Medicine, University of Southampton , Southampton, Southampton, SO16 6YD,","place":["United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sander S","family":"Rensen","sequence":"additional","affiliation":[{"name":"Department of Surgery, Maastricht University Medical Center , Maastricht, 6200 MD,","place":["The Netherlands"]},{"name":"NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University , Maastricht, 6229 ER,","place":["The Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andre","family":"Dekker","sequence":"additional","affiliation":[{"name":"Department of Radiotherapy (MAASTRO), Maastricht University , Maastricht, Maastricht, 6229 ET,","place":["The Netherlands"]},{"name":"GROW School for Oncology and Reproduction, Maastricht University , Maastricht, 6229 ER,","place":["The Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1612-9055","authenticated-orcid":false,"given":"Leonard","family":"Wee","sequence":"additional","affiliation":[{"name":"Department of Radiotherapy (MAASTRO), Maastricht University , Maastricht, Maastricht, 6229 ET,","place":["The Netherlands"]},{"name":"GROW School for Oncology and Reproduction, Maastricht University , Maastricht, 6229 ER,","place":["The Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven W M","family":"Olde Damink","sequence":"additional","affiliation":[{"name":"Department of Surgery, Maastricht University Medical Center , Maastricht, 6200 MD,","place":["The Netherlands"]},{"name":"NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University , Maastricht, 6229 ER,","place":["The 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