{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T05:41:28Z","timestamp":1784698888990,"version":"3.55.0"},"reference-count":57,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Nutr."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Computed Tomography (CT)-derived analysis of Body Composition (BC) provides detailed phenotyping of skeletal muscle and adipose tissue, offering insight into nutritional and metabolic risk in oncology.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To characterize sex- and age-specific muscle and adipose tissue phenotypes in patients with colon cancer and describe their patterns across postoperative outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Multicentric observational cross-sectional study including Colorectal Cancer (CRC) patients undergoing laparoscopic elective surgery. Preoperative CT scans at L3 were analyzed for muscle and adipose tissue quantity and radiodensity. Differences in BC parameters between patient groups (according to presence of complications, hospital stay and disease stage by sex) were assessed using Student\u2019s\n                      <jats:italic>t<\/jats:italic>\n                      -test (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      502 CRC patients, predominantly males (62.5%) with a mean age of 68.08\u202f\u00b1\u202f10.62 were included. Sex-specific differences in muscle quality and adipose tissue distribution were observed across postoperative outcomes. In women, lower Subcutaneous Adipose Tissue (SAT) values were observed in those with longer hospital stay and complications (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001), whereas in men, reduced Skeletal Lean Muscle Radiodensity (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001) and higher Visceral Adipose Tissue (VAT;\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.013) were found in those with adverse outcomes. These differences were independent of BMI and age.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>CT-based body composition phenotyping identifies distinct metabolic profiles linked to postoperative risk. Incorporating tissue quality and distribution into nutritional assessment may enhance early identification of vulnerable patients and guide personalized perioperative strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnut.2025.1728741","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T05:15:46Z","timestamp":1763702146000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Sex-specific CT-derived muscle and fat phenotypes in colon cancer: implications for nutritional and metabolic assessment"],"prefix":"10.3389","volume":"12","author":[{"given":"Fernanda","family":"Mucarzel","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patricia Guirado","family":"Pel\u00e1ez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Virginia Soria","family":"Utrilla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roc\u00edo Fern\u00e1ndez","family":"Jim\u00e9nez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fiorella Palmas","family":"Candia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francisco Jos\u00e9 S\u00e1nchez","family":"Torralvo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rosa Burgos","family":"Pel\u00e1ez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9 Manuel Garc\u00eda","family":"Almeida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabriel","family":"Olveira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"112152","DOI":"10.1016\/j.nut.2023.112152","article-title":"Association of body mass index and weight change with death in patients with advanced cancer","volume":"115","author":"Ishida","year":"2023","journal-title":"Nutrition"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1268","DOI":"10.1016\/j.clnu.2020.08.009","article-title":"Nutritional status and body composition assessment in patients with a new diagnosis of advanced solid tumour: exploratory comparison of computed tomography and bioelectrical impedance analysis","volume":"40","author":"Casirati","year":"2021","journal-title":"Clin Nutr"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1146\/annurev.nutr.17.1.527","article-title":"Human body composition: advances in models and methods","volume":"17","author":"Heymsfield","year":"1997","journal-title":"Annu Rev Nutr"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1002\/jcsm.12379","article-title":"The evolution of body composition in oncology-epidemiology, clinical trials, and the future of patient care: facts and numbers","volume":"9","author":"Brown","year":"2018","journal-title":"J Cachexia Sarcopenia Muscle"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"940","DOI":"10.1177\/0148607114550189","article-title":"Lean tissue imaging: a new era for nutritional assessment and intervention","volume":"38","author":"Prado","year":"2014","journal-title":"JPEN J Parenter Enteral Nutr"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"997","DOI":"10.1139\/H08-075","article-title":"A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care","volume":"33","author":"Mourtzakis","year":"2008","journal-title":"Appl Physiol Nutr Metab"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"1869","DOI":"10.3390\/nu16121869","article-title":"AI-assisted body composition assessment using CT imaging in colorectal Cancer patients: predictive capacity for sarcopenia and malnutrition diagnosis","volume":"16","author":"Soria-Utrilla","year":"2024","journal-title":"Nutrients"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.clnu.2018.08.002","article-title":"GLIM Core leadership committee; GLIM working group. 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