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We assessed multimodal radiomics\u2014positron emission tomography (PET), computed tomography (CT), and clinicopathological (CP) data\u2014for personalized recurrence prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data from 131 NSCLC patients with PET\/CT imaging and CP variables were analysed. Radiomics features were extracted using PyRadiomics (1,316 PET and 1,409 CT features per tumor), with robustness testing and selection yielding 20 CT, 20 PET, and 23 CP variables. Prediction models were trained using Logistic Regression (L1, L2, Elastic Net), Random Forest, Gradient Boosting, XGBoost, and CatBoost. Nested cross-validation with SMOTE addressed class imbalance. Fusion strategies included early (feature concatenation), intermediate (stacked ensembles), and late (weighted averaging) fusion.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among single modalities, CT with Elastic Net achieved the highest cross-validated AUC (0.679, 95% CI: 0.57\u20130.79). Fusion improved performance: PET\u2009+\u2009CT\u2009+\u2009Clinical late fusion with Elastic Net achieved the best cross-validated AUC (0.811, 95% CI: 0.69\u20130.91). Out-of-fold ROC curves confirmed stronger discrimination for the fusion model (AUC\u2009=\u20090.836 vs. 0.741 for CT). Fusion also showed better calibration, higher net clinical benefit (decision-curve analysis), and clearer survival stratification (Kaplan\u2013Meier).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Integrating PET, CT, and CP data\u2014particularly via late fusion with Elastic Net\u2014enhances discrimination beyond single-modality models and supports more consistent risk stratification. These findings suggest practical potential for informing postoperative surveillance and adjuvant therapy decisions, encouraging a shift beyond TNM alone toward interpretable multimodal frameworks. External validation in larger, multicenter cohorts is warranted.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00432-025-06311-w","type":"journal-article","created":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T03:11:15Z","timestamp":1758165075000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Multimodal radiomics fusion for predicting postoperative recurrence in NSCLC patients"],"prefix":"10.1007","volume":"151","author":[{"given":"Ghazal","family":"Mehri-kakavand","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5418-5122","authenticated-orcid":false,"given":"Sibusiso","family":"Mdletshe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mehdi","family":"Amini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1610-2397","authenticated-orcid":false,"given":"Alan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,18]]},"reference":[{"key":"6311_CR1","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1016\/j.crad.2019.02.008","volume":"74","author":"HK Ahn","year":"2019","unstructured":"Ahn HK, Lee H, Kim SG, Hyun SH (2019) Pre-treatment 18F-FDG PET-based radiomics predict survival in resected non-small cell lung cancer. 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Symmetry 15(10):1834. https:\/\/doi.org\/10.3390\/sym15101834","journal-title":"Symmetry"}],"container-title":["Journal of Cancer Research and Clinical Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00432-025-06311-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00432-025-06311-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00432-025-06311-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T11:35:12Z","timestamp":1781609712000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00432-025-06311-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,18]]},"references-count":43,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["6311"],"URL":"https:\/\/doi.org\/10.1007\/s00432-025-06311-w","relation":{},"ISSN":["1432-1335"],"issn-type":[{"value":"1432-1335","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,18]]},"assertion":[{"value":"10 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 September 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 September 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This study used a publicly available secondary dataset (NSCLC-Radiogenomics) obtained from The Cancer Imaging Archive (TCIA). Ethical approval and informed consent were obtained by the original investigators at Stanford University School of Medicine and Palo Alto Veterans Affairs Healthcare System prior to data collection. All data were fully anonymized before being shared via TCIA. The authors of this manuscript did not participate in the original data collection and did not require additional ethical approval.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Obtained by the original investigators as part of the NSCLC-Radiogenomics study. The authors of this manuscript did not collect any new data requiring consent.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Obtained by the original investigators. The data used in this study were fully anonymized and made publicly available via TCIA.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to publication"}}],"article-number":"261"}}