{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T11:15:09Z","timestamp":1780398909919,"version":"3.54.1"},"reference-count":30,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:00:00Z","timestamp":1780358400000},"content-version":"vor","delay-in-days":152,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BioMed Research International"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study is aimed at exploring the value of a high\u2010resolution vessel wall imaging (HR\u2010VWI)\u2013based radiomics approach for identifying symptomatic basilar atherosclerotic plaques.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>This retrospective study included 154 patients, hospitalized at Shanxi Cardiovascular Hospital for cerebrovascular disease, who had basilar artery stenosis and underwent HR\u2010VWI examinations between July 2020 and December 2023. The patients were randomly divided into training and validation sets in a 7:3 ratio and further classified into symptomatic and asymptomatic groups based on the presence or absence of acute infarction lesions in the basilar artery supply area, respectively. Clinical and traditional imaging features were collected for all patients. Manual plaque segmentation and radiomics feature extraction were performed on the layers of basilar artery plaques identified in the plain\u2010scanning and enhanced HR\u2010VWI images. Feature denoising was performed using minimum redundancy maximum correlation, and the least absolute shrinkage and selection operator (LASSO) algorithm was applied to reduce feature variables. The most suitable features were selected through univariate and multivariate logistic regression analyses. The plain\u2010scanning, enhanced, and plain \u2212 scanning + enhanced\u2009models were established. Finally, a combined model was constructed by integrating selected clinical and traditional imaging features (intraplaque hemorrhage [IPH], enhanced plaque signal) with the plain \u2212 scanning + enhanced\u2009HR \u2212 VWI\u2009radiomics\u2009features. The recognition efficiency of each model for symptomatic basilar atherosclerotic plaques was evaluated using the receiver operating characteristic (ROC) curve and the area under the receiver operating characteristic curve (AUC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A statistically significant difference in age was observed between symptomatic and asymptomatic groups (\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.05). Conventional imaging features, including IPH, vessel diameter at stenosis, lumen area at stenosis, enhanced plaque signal, stenosis rate, and plaque load, also demonstrated statistically significant differences between the two groups (\n                      <jats:italic>p<\/jats:italic>\n                      &lt; 0.05). Firth\u2010penalized logistic regression analysis identified IPH and enhanced plaque signal as risk factors for symptomatic basilar artery plaques. In the training set, the AUC values for detecting symptomatic plaques were 0.813, 0.853, and 0.898 for plain\u2010scanning, enhanced, and plain \u2212 scanning + enhanced\u2009models, respectively. In the validation set, the AUC values were 0.786, 0.848, and 0.880, respectively. The efficacy of models was in the order of plain \u2212 scanning + enhanced\u2009model &gt; enhanced\u2009model &gt; plain \u2212 scanning\u2009model. The combined model, integrating IPH and enhanced plaque signal with the\u2009plain \u2212 scanning + enhanced\u2009HR \u2212 VWI\u2009radiomics\u2009features, achieved an AUC of 0.916 in the training set, with sensitivity, specificity, and accuracy of 0.821, 0.941, and 0.879, respectively, for predicting symptomatic basilar artery plaques. In the validation set, the AUC value was 0.891, with sensitivity, specificity, and accuracy of 0.792, 0.870, and 0.830, respectively. The combined model demonstrated superior performance compared with the plain \u2212 scanning + enhanced\u2009model.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our HR\u2010VWI\u2013based radiomics models can accurately distinguish symptomatic from asymptomatic basilar atherosclerotic plaques. It is superior to the traditional model in the identification of high\u2010risk plaques.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1155\/bmri\/7319324","type":"journal-article","created":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T10:29:39Z","timestamp":1780396179000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multimodal Radiomics Model Combining HR\u2010VWI and Clinical Features for Identifying Symptomatic Basilar Atherosclerotic 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