{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T16:24:12Z","timestamp":1790958252196,"version":"4.1.0"},"reference-count":39,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2024,2,20]],"date-time":"2024-02-20T00:00:00Z","timestamp":1708387200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR201911040452"],"award-info":[{"award-number":["ZR201911040452"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81627901"],"award-info":[{"award-number":["81627901"]}],"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":["81972863"],"award-info":[{"award-number":["81972863"]}],"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":["82030082"],"award-info":[{"award-number":["82030082"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005149","name":"Cancer Institute and Hospital, Chinese Academy of Medical Sciences","doi-asserted-by":"publisher","award":["2019RU071"],"award-info":[{"award-number":["2019RU071"]}],"id":[{"id":"10.13039\/501100005149","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Thoracic Cancer"],"published-print":{"date-parts":[[2024,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Brain metastases (BMs) are common in small cell lung cancer (SCLC), and the efficacy of immune checkpoint inhibitors (ICIs) in these patients is uncertain. In this study we aimed to develop and validate a radiomics nomogram based on magnetic resonance imaging (MRI) for intracranial efficacy prediction of ICIs in patients with BMs from SCLC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The training and validation cohorts consisted of 101 patients from two centers. The interclass correlation coefficient (ICC), logistic univariate regression analysis, and random forest were applied to select the radiomic features, generating the radiomics score (Rad\u2010score) through the formula. Using multivariable logistic regression analysis, a nomogram was created by the combined model. The discrimination, calibration, and clinical utility were used to assess the performance of the nomogram. Kaplan\u2013Meier curves were plotted based on the nomogram scores.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Ten radiomic features were selected for calculating the Rad\u2010score as they could differentiate the intracranial efficacy in the training (area under the curve [AUC], 0.759) and the validation cohort (AUC, 0.667). A nomogram was created by combining Rad\u2010score, treatment lines, and neutrophil\u2010to\u2010lymphocyte ratio (NLR). The training cohort obtained an AUC of 0.878 for the combined model, verified in the validation cohort (AUC\u2009=\u20090.875). Kaplan\u2013Meier analyses showed the nomogram was associated with progression\u2010free survival (PFS) (<jats:italic>p<\/jats:italic>\u2009=\u20090.0152) and intracranial progression\u2010free survival (iPFS) (<jats:italic>p<\/jats:italic>\u2009=\u20090.0052) but not overall survival (OS) (<jats:italic>p<\/jats:italic>\u2009=\u20090.4894).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>A radiomics nomogram model for predicting the intracranial efficacy of ICIs in SCLC patients with BMs can provide suggestions for exploring individual\u2010based treatments for patients.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1759-7714.15259","type":"journal-article","created":{"date-parts":[[2024,2,20]],"date-time":"2024-02-20T16:50:38Z","timestamp":1708447838000},"page":"738-748","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Using <scp>MRI<\/scp> radiomics to predict the efficacy of immunotherapy for brain metastasis in patients with small cell lung cancer"],"prefix":"10.1111","volume":"15","author":[{"given":"Xiaonan","family":"Shi","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences  Jinan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peiliang","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences  Jinan China"},{"name":"Cheeloo College of Medicine Shandong University  Jinan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yikun","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences  Jinan 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