{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T12:20:01Z","timestamp":1787746801146,"version":"build-2784847793"},"reference-count":39,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"vor","delay-in-days":10,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J cachexia sarcopenia muscle"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Oesophageal cancer remains the sixth most lethal malignancy, with 5\u2010year survival rates around 22%. CT\u2010derived 2D body composition analysis has emerged as a promising prognostic tool, but conventional, often manually created single\u2010slice L3 measurements are unsuited for future clinical implementation. We evaluated fully automated AI\u2010derived volumetric body composition indices as prognostic parameters using conventional L3 and BMI measurements as reference.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective cohort study included patients with histologically confirmed oesophageal cancer treated between 2011 and 2024. Automated deep learning segmentation using the nnU\u2010Net\u2010based body and organ analysis pipeline quantified abdominal tissue volumes from staging CTs. Three normalized indices were calculated: sarcopenia index (SI, muscle\/bone volume ratio), myosteatotic fat index (MFI, intramuscular\/total adipose tissue volume ratio) and abdominal fat index (AFI, visceral\/subcutaneous adipose tissue volume ratio). Cox proportional hazards models assessed prognostic value after sequential adjustment for age, sex, metastatic status, ECOG performance status, BMI and L3\u2010derived indices. Kaplan\u2013Meier analysis evaluated survival differences stratified by sex\u2010specific median values.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The cohort comprised 563 patients (19.7% female), median age 65.4\u2009years (IQR: 58.8\u201371.3); 10.1% (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200957) had metastatic disease and 68.7% (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009387) underwent surgery. Males had higher sarcopenia index (2.54\u2009\u00b1\u20090.41 vs. 2.24\u2009\u00b1\u20090.45,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) and abdominal fat index (median 0.72 vs. 0.36,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), whereas MFI showed no difference (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.89). During median follow\u2010up of 22\u2009months, 367 deaths (65.9%) occurred. Median overall survival was 28.6\u2009months (95% CI: 23.7\u201333.3); 1\u2010year survival 70.7% (95% CI: 67.2%\u201374.8%) and 5\u2010year survival 32.8% (95% CI: 29.6%\u201338.3%), with marked differences by metastatic status (M0 vs. M1 1\u2010year survival: 73.4% vs. 46.4%). In the fully adjusted model incorporating all three volumetric indices alongside clinical covariates, BMI and L3\u2010derived parameters (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009532), only sarcopenia index retained independent significance (HR\u2009=\u20090.56, 95% CI: 0.37\u20130.82,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.003); all others showed\n                      <jats:italic>p<\/jats:italic>\n                      \u2009\u2265\u20090.26. Metastatic status (HR\u2009=\u20092.23,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) and ECOG (HR\u2009=\u20091.29,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) remained significant. All L3 indices lost significance alongside volumetric parameters (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&gt;\u20090.14). Male patients with high sarcopenia index showed longer survival compared with patients with low sarcopenia index (33.3 vs. 21.8\u2009months,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001); female patients showed larger descriptive contrasts (68.8 vs. 16.8\u2009months,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) that were formally confirmed by a significant sex\u2010SI Cox interaction (LRT\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.026).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Automatic AI\u2010derived volumetric body composition parameters calculated from routine staging CTs predict overall survival in patients with oesophageal cancer and are associated with sex\u2010related differences of prognostic impact, supporting further evaluation toward future clinical use.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jcsm.70363","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T06:14:33Z","timestamp":1786515273000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction of Overall Survival in Patients With Oesophageal Cancer Using AI\u2010Based 3D CT Body Composition Analysis"],"prefix":"10.1002","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4386-9323","authenticated-orcid":false,"given":"Christian","family":"R\u00f6mer","sequence":"first","affiliation":[{"name":"Clinic for Radiology University Hospital M\u00fcnster and University of M\u00fcnster  M\u00fcnster 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Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4963-0989","authenticated-orcid":false,"given":"Marc\u2010David","family":"K\u00fcnnemann","sequence":"additional","affiliation":[{"name":"Clinic for Radiology University Hospital M\u00fcnster and University of M\u00fcnster  M\u00fcnster Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1760-2342","authenticated-orcid":false,"given":"Ren\u00e9","family":"Hosch","sequence":"additional","affiliation":[{"name":"Institute of Diagnostic and Interventional Radiology and Neuroradiology University Hospital Essen  Essen Germany"},{"name":"Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen  Essen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6987-6041","authenticated-orcid":false,"given":"Katarzyna","family":"Borys","sequence":"additional","affiliation":[{"name":"Institute of Diagnostic and Interventional Radiology and Neuroradiology University Hospital Essen  Essen Germany"},{"name":"Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen  Essen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3994-1495","authenticated-orcid":false,"given":"Gesa Helen","family":"P\u00f6hler","sequence":"additional","affiliation":[{"name":"Clinic for Radiology University Hospital M\u00fcnster and University of M\u00fcnster  M\u00fcnster Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,11]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21834"},{"key":"e_1_2_12_4_1","unstructured":"National Cancer Institute \u201cSEER Cancer Stat Facts: Esophageal Cancer \u201d accessed January 29 2026 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