{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T22:37:18Z","timestamp":1774391838395,"version":"3.50.1"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"1153","license":[{"start":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T00:00:00Z","timestamp":1702339200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82071989"],"award-info":[{"award-number":["82071989"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2021A1515012243"],"award-info":[{"award-number":["2021A1515012243"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"name":"2021 SKY Imaging Science and Research Fund of China International Medical Foundation","award":["Z-2014-07-2101-12"],"award-info":[{"award-number":["Z-2014-07-2101-12"]}]},{"name":"Kelin New Star Talent"},{"name":"The First Affiliated Hospital, Sun Yat-sen University","award":["R08028"],"award-info":[{"award-number":["R08028"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objectives<\/jats:title>\n                  <jats:p>To create a MRI-derived radiomics nomogram that combined clinicopathological factors and radiomics signature (Rad-score) for predicting disease-free survival (DFS) in patients with bladder cancer (BCa) following partial resection (PR) or radical cystectomy (RC), including lymphadenectomy (LAE).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>Finally, 80 patients with BCa after PR or RC with LAE were enrolled. Patients were randomly split into training (n\u2009=\u200956) and internal validation (n\u2009=\u200924) cohorts. Radiomic features were extracted from T2-weighted, dynamic contrast-enhanced, diffusion-weighted imaging, and apparent diffusion coefficient sequence. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was applied to choose the valuable features and construct the Rad-score. The DFS prediction model was built using the Cox proportional hazards model. The relationship between the Rad-score and DFS was assessed using Kaplan-Meier analysis. A radiomics nomogram that combined the Rad-score and clinicopathological factors was created for individualized DFS estimation.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In both the training and validation cohorts, the Rad-score was positively correlated with DFS (P\u2009&amp;lt;\u2009.001). In the validation cohort, the radiomics nomogram combining the Rad-score, tumour pathologic stage (pT stage), and lymphovascular invasion (LVI) achieved better performance in DFS prediction (C-index, 0.807; 95% CI, 0.713-0.901) than either the clinicopathological (C-index, 0.654; 95% CI, 0.467-0.841) or Rad-score\u2013only model (C-index, 0.770; 95% CI, 0.702-0.837).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>The Rad-score was an independent predictor of DFS for patients with BCa after PR or RC with LAE, and the radiomics nomogram that combined the Rad-score, pT stage, and LVI achieved better performance in individual DFS prediction.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Advances in knowledge<\/jats:title>\n                  <jats:p>This study provided a non-invasive and simple method for personalized and accurate prediction of DFS in BCa patients after PR or RC.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bjr\/tqad010","type":"journal-article","created":{"date-parts":[[2024,1,10]],"date-time":"2024-01-10T00:13:38Z","timestamp":1704845618000},"page":"201-209","source":"Crossref","is-referenced-by-count":3,"title":["Radiomics nomogram for predicting disease-free survival after partial resection or radical cystectomy in patients with bladder cancer"],"prefix":"10.1093","volume":"97","author":[{"given":"Qian","family":"Cai","sequence":"first","affiliation":[{"name":"Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University , Guangzhou, Guangdong 510080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiping","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University , Guangzhou, Guangdong 510080, 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