{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T13:45:24Z","timestamp":1792071924801,"version":"4.4.0"},"reference-count":37,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T00:00:00Z","timestamp":1788307200000},"content-version":"vor","delay-in-days":1,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Gliomas are the most common primary tumors of the central nervous system. Their treatment remains highly challenging, with high rates of associated disability and mortality. Conventional prognostic indicators no longer adequately satisfy the clinical demands of precision medicine. Therefore, it is essential to further explore novel prognostic biomarkers to enable accurate risk stratification and to provide new reference indicators for personalized precision therapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purposes<\/jats:title>\n                    <jats:p>This study aimed to investigate the prognostic significance of vascular endothelial growth factor A (VEGFA) in patients diag nosed with lower\u2010grade gliomas (LGGs) using an MRI based radiomics model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data regarding VEGFA expression and clinical records of LGG patients were retrieved from The Cancer Genome Atlas (TCGA). Corresponding preoperative MRI data were obtained from The Cancer Imaging Archive (TCIA) for radiomic feature extraction. Patients were stratified into high\u2010 and low\u2010 VEGFA expression groups based on survival information from the current cohort using the survminer package. The overall survival (OS) was assessed using Kaplan\u2013Meier analysis and Cox proportional hazards regression. Predictive models were developed using logistic regression (LR), and model performance was evaluated via receiver operating characteristic (ROC) curve analysis, with area under the curve (AUC) values reported. An optimized model incorporating the Akaike information criterion (AIC) was also constructed (AIC\u2010LR).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      VEGFA expression was significantly associated with OS (\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.002). Multivariate Cox regression confirmed VEGFA as an independent prognostic factor (hazard ratio [HR]\u00a0=\u00a02.545, 95% confidence interval: 1.422\u20134.555). Furthermore, VEGFA expression correlated with immune infiltration levels, particularly of M1 and M2 macrophages and T follicular helper cells, and was associated with enrichment in Wnt signaling and B cell receptor signaling pathways. The LR and AIC\u2010LR models demonstrated acceptable predictive performance, with AUCs of 0.728 (95% CI: 0.612\u20130.843) and 0.725(95% CI: 0.612\u20130.839) in the training cohort, and 0.704 (95% CI: 0.562\u20130.847) and 0.718(95% CI: 0.576\u20130.861) in the validation cohort, respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The MRI based radiomics model showed potential for noninvasive assessment of VEGFA expression and may provide auxiliary information for prognostic evaluation in LGG. Further validation in larger samples and independent external cohorts is required before clinical application.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70615","type":"journal-article","created":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T07:50:56Z","timestamp":1788335456000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MRI\u2010based radiomics model for predicting VEGFA expression and prognosis in lower\u2010grade glioma"],"prefix":"10.1002","volume":"53","author":[{"given":"Kun","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Neurology Affiliated People's Hospital of Jiangsu University  Zhenjiang Jiangsu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Hong","sequence":"additional","affiliation":[{"name":"Institute of Clinical Applied Anatomy School of Basic Medical Science Fujian Medical University  Fuzhou Fujian 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Hospital of Jiangsu University  Zhenjiang Jiangsu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongbing","family":"Gu","sequence":"additional","affiliation":[{"name":"Medical Imaging Department Affiliated People's Hospital of Jiangsu University  Zhenjiang Jiangsu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoqiang","family":"Ren","sequence":"additional","affiliation":[{"name":"Medical Imaging Department Affiliated People's Hospital of Jiangsu University  Zhenjiang Jiangsu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baomin","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery Affiliated People's Hospital of Jiangsu University  Zhenjiang Jiangsu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liping","family":"Zhan","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery Affiliated People's Hospital of Jiangsu University  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