{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T15:31:29Z","timestamp":1788449489794,"version":"build-2803163510"},"reference-count":42,"publisher":"Wiley","issue":"47","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["825B2054"],"award-info":[{"award-number":["825B2054"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82472058"],"award-info":[{"award-number":["82472058"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82172034"],"award-info":[{"award-number":["82172034"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Science"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    <jats:bold>Background and aims<\/jats:bold>\n                    : Conventional body composition assessment fails to capture its multidimensional complexity in gastric cancer (GC). This study aimed to systematically evaluate multidimensional body composition and its clinical relevance in GC.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Methods<\/jats:bold>\n                    : 1196 GC patients and 983 healthy controls were retrospectively enrolled. Body composition was segmented using nnU\u2010Net. Propensity score matching was used to compare body composition differences between patients and healthy controls. Prognostic value was assessed across treatment cohorts. TCGA pathological and transcriptomic data were integrated for exploratory analyses. Sex\u2010specific prognostic models were developed and externally validated.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Results<\/jats:bold>\n                    : AI\u2010drived body compositions parameters showed sex\u2010specific associations with survival. Higher muscle\/fat area\/index and lower fat density correlated with longer survival in surgical patients (L1 muscle area: HR = 0.438, ad\n                    <jats:italic>p<\/jats:italic>\n                    = 0.001). In ICI\u2010treated females, higher subcutaneous fat area (SFA) improved survival (L2SFA: HR = 0.972, ad\n                    <jats:italic>p<\/jats:italic>\n                    = 0.045). Potential associations were observed between body composition and tumor microenvironmental features, including stromal composition, EMT\u2010related pathways, and immune infiltration. Sex\u2010specific prognostic models achieved C\u2010indices of 0.723 (males) and 0.705 (females) in test cohorts, outperforming conventional predictors.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Conclusion<\/jats:bold>\n                    : Multidimensional body composition is associated with prognosis in GC and may serve as a complementary biomarker for risk stratification.\n                  <\/jats:p>","DOI":"10.1002\/advs.75859","type":"journal-article","created":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T07:43:25Z","timestamp":1780299805000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Artificial Intelligence\u2010Based Body Composition Analysis Reveals Sex\u2010Specific Prognostic Markers and Their Clinical Value in Gastric Cancer: A Multicenter Study"],"prefix":"10.1002","volume":"13","author":[{"given":"Tianxiang","family":"Li","sequence":"first","affiliation":[{"name":"Department of Radiology Union Hospital Tongji Medical College Huazhong University of Science and Technology  Wuhan China"},{"name":"Hubei Provincial Clinical Research Center For Precision Radiology &amp; Interventional Medicine  Wuhan China"},{"name":"Hubei Key Laboratory of Molecular Imaging  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingting","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Radiology Union Hospital Tongji Medical College Huazhong University of Science and Technology  Wuhan China"},{"name":"Hubei Provincial Clinical Research Center For Precision Radiology &amp; Interventional Medicine  Wuhan China"},{"name":"Hubei Key Laboratory of Molecular Imaging  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Radiology Hubei Cancer Hospital Tongji Medical College Huazhong University of Science and Technology  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Radiology Union Hospital Tongji Medical College Huazhong University of Science and Technology  Wuhan China"},{"name":"Hubei Provincial Clinical Research Center For Precision Radiology &amp; Interventional Medicine  Wuhan China"},{"name":"Hubei Key Laboratory of Molecular Imaging  Wuhan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofang","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Radiology Hubei Cancer Hospital Tongji Medical College Huazhong University of Science and Technology  Wuhan 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