{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T02:04:14Z","timestamp":1793325854316,"version":"4.5.0"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>High expression of Ki-67 in meningioma is significantly associated with higher histological grade and worse prognosis. The non-invasive and dynamic assessment of Ki-67 expression levels in meningiomas is of significant clinical importance and is urgently required. This study aimed to develop a predictive model for the Ki-67 index in meningioma based on preoperative magnetic resonance imaging (MRI).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This study included 196 patients from one center (internal cohort) and 92 patients from another center (external validation cohort). Meningioma had to have been pathologically confirmed for inclusion. The Ki-67 index was classified as high (Ki-67\u202f\u2265\u202f5%) and low (Ki-67\u202f&amp;lt;\u202f5%). The internal cohort was randomly assigned to training and validation sets at a 7:3 ratio. Radiomics features were selected from contrast-enhanced T1-weighted MRI using the least-absolute shrinkage and selection operator and random forest methods. Then, we constructed a predictive model based on the identified semantic and radiomics features, aiming to distinguish high and low Ki-67 expression. The model\u2019s performance was evaluated through internal cross-validation and validated in the external cohort.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Among the clinical features, peritumoral edema (<jats:italic>p<\/jats:italic>\u202f=\u202f0.001) and heterogeneous enhancement (<jats:italic>p<\/jats:italic>\u202f=\u202f0.001) were independent predictors of the Ki-67 index in meningiomas. The radiomics model using a combined 8\u202fmm volume of interest demonstrated optimal performance in the training (area under the receiver operating characteristic curve [AUC]\u202f=\u202f0.883) and validation (AUC\u202f=\u202f0.811) sets. A nomogram integrating clinical and radiomic features was constructed, achieving an AUC of 0.904 and enhancing the model\u2019s predictive accuracy for high Ki-67 expression.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study developed clinical-radiomic models to non-invasively predict Ki-67 expression in meningioma and provided a novel preoperative strategy for assessing tumor proliferation.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fneur.2025.1554539","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T05:32:59Z","timestamp":1753335179000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["MRI-based multiregional radiomics for preoperative prediction of Ki-67 expression in meningiomas: a two-center study"],"prefix":"10.3389","volume":"16","author":[{"given":"Ming","family":"Luo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guihan","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duoning","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiyue","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuiwei","family":"Xia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junguo","family":"Hui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengjun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minjiang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wangyang","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiansong","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1136\/jnnp.20.1.22","article-title":"The recurrence of intracranial meningiomas after surgical treatment","volume":"20","author":"Simpson","year":"1957","journal-title":"J Neurol Neurosurg Psychiatry"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"735","DOI":"10.1093\/neuonc\/not325","article-title":"Proposal for a new risk stratification classification for meningioma based on patient age, WHO tumor grade, size, localization, and karyotype","volume":"16","author":"Domingues","year":"2014","journal-title":"Neuro-Oncology"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"v1","DOI":"10.1093\/neuonc\/noac202","article-title":"CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2015-2019","volume":"24","author":"Ostrom","year":"2022","journal-title":"Neuro-Oncology"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"37","DOI":"10.4103\/0028-3886.128276","article-title":"Assessment of expression of epidermal growth factor receptor and p53 in meningiomas","volume":"62","author":"Narla","year":"2014","journal-title":"Neurol India"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1093\/neuonc\/noab106","article-title":"The 2021 WHO classification of tumors of the central nervous system: a summary","volume":"23","author":"Louis","year":"2021","journal-title":"Neuro-Oncology"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1007\/s00401-016-1598-1","article-title":"Brain invasion in otherwise benign meningiomas does not predict tumor recurrence","volume":"132","author":"Baumgarten","year":"2016","journal-title":"Acta Neuropathol"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"Ec15","DOI":"10.7860\/JCDR\/2016\/15661.7117","article-title":"Histopathological and immunohistochemical evaluation of meningiomas with reference to proliferative markers p53 and Ki-67","volume":"10","author":"Telugu","year":"2016","journal-title":"J Clin Diagn Res"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1284","DOI":"10.1002\/acn3.51797","article-title":"A radiomics model enables prediction venous sinus invasion in meningioma","volume":"10","author":"Wang","year":"2023","journal-title":"Ann Clin Transl Neurol"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/s00701-003-0173-4","article-title":"The Ki-67 proliferation antigen in meningiomas. 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