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The relationship between preoperative CT-ECV and recurrence risk was evaluated using comprehensive imaging and clinicopathological data. The optimal CT-ECV threshold for recurrence prediction was determined using receiver operating characteristic (ROC) curve analysis. Disease-free survival (DFS) was assessed using Kaplan\u2013Meier and Cox regression analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The mean CT-ECV was 56.4\u2009\u00b1\u200916.7%. Patients with recurrence (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200928) had significantly higher CT-ECV values than those without recurrence (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200984) (65.3\u2009\u00b1\u200914.3% vs 53.5\u2009\u00b1\u200916.5%;\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). The optimal CT-ECV cutoff for recurrence prediction was \u2265\u200956.9%, with an area under the curve of 0.71 (sensitivity 82.1%, specificity 61.9%). Multivariate analysis revealed that high CT-ECV was independently associated with worse DFS (HR: 5.93; 95% CI: 1.77\u201319.86;\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.004). Patients with high CT-ECV had significantly lower DFS rates compared to those with low CT-ECV (5-year DFS rate: 49.9% vs 93.7%;\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>High CT-ECV values correlate with increased recurrence risk and shorter DFS in pStage II\u2013III GC, highlighting its potential as a predictive imaging biomarker for preoperative risk stratification.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Question<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Identifying prognostic markers is crucial for improving outcomes in stage II\u2013III GC with high recurrence rates post-treatment<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>High preoperative CT-ECV values are independently associated with increased recurrence risk and reduced DFS in pStage II\u2013III GC<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Clinical relevance<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>CT-ECV can facilitate personalised treatment strategies and potentially improve patient management and outcomes<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-025-11765-0","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T06:00:39Z","timestamp":1750226439000},"page":"656-665","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["CT-derived extracellular volume fraction as a predictive marker for postoperative recurrence in pStage II\u2013III gastric cancer"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4553-3922","authenticated-orcid":false,"given":"Yusuke","family":"Nishimuta","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daisuke","family":"Tsurumaru","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nobuhiro","family":"Fujita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satohiro","family":"Kai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junki","family":"Maehara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasuhiro","family":"Ushijima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eiji","family":"Oki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kousei","family":"Ishigami","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,18]]},"reference":[{"key":"11765_CR1","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3322\/caac.21660","volume":"71","author":"H Sung","year":"2021","unstructured":"Sung H, Ferlay J, Siegel RL et al (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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Furthermore author Nobuhiro Fujita\u2019s name was misspelled as Fujuta Nobuhiro.","order":8,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 October 2025","order":9,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":10,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A Correction to this paper has been published:","order":11,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1007\/s00330-025-12037-7","URL":"https:\/\/doi.org\/10.1007\/s00330-025-12037-7","order":12,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The scientific guarantor of this publication is Dr. Yusuke Nishimuta.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Guarantor"}},{"value":"The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"No complex statistical methods were necessary for this paper.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was waived by the Ethics Committee of the Kyushu University Hospital.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was obtained from the Ethics Committee of the Kyushu University Hospital (approval number: 2020-219).","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Some study subjects or cohorts have been previously reported in Nishimuta et al [\n                      \n                      ].","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}