{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,6]],"date-time":"2026-11-06T19:22:37Z","timestamp":1793992957998,"version":"4.8.0"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T00:00:00Z","timestamp":1776643200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100004587","name":"Instituto de Salud Carlos III","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004587","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Proyectos I\u2009+\u2009D+i, Acci\u00f3n Estrat\u00e9gica en Salud 2022","award":["PI22\/01680"],"award-info":[{"award-number":["PI22\/01680"]}]},{"name":"European Union\u2019s Recovery and Resilience Facility"},{"DOI":"10.13039\/100031478","name":"NextGenerationEU","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100031478","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Spanish Government\u2019s"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Glioblastoma recurrence is driven by diffuse microscopic infiltration beyond the contrast-enhancing tumor margin. GlioMap is an open-access AI model predicting voxelwise infiltration and recurrence risk from multiparametric MRI. This prospective study aimed to validate GlioMap\u2019s biological accuracy and prognostic relevance through histopathological assessment, transcriptomic profiling, and survival analysis within the SupraGlio trial (NCT05735171).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Patients with newly diagnosed glioblastoma underwent neuronavigated biopsies targeting AI-predicted high-risk (HRoR) and low-risk of recurrence (LRoR) regions beyond the contrast-enhancing tumor. Histopathological infiltration served as the ground truth, and transcriptomic profiling characterised each region\u2019s molecular phenotype. Model performance was evaluated using accuracy and area under the receiver operating characteristic curve (AUC). Survival analyses assessed the prognostic value of postoperative HRoR volume.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Fifty-eight biopsies from 27 patients were analyzed. GlioMap achieved 0.81 accuracy (95% confidence interval [CI], 0.71-0.91) and 0.84 AUC (95% CI, 0.73-0.93) for histologically confirmed infiltration. Transcriptomic analysis of 48 samples from 16 patients revealed progressive upregulation of invasion- and angiogenesis-related genes (CD44, CHI3L1, STAT3, VEGFA) and downregulation of neuronal markers (MBP, GABRA1) from LRoR to HRoR regions and the tumor core, confirming a neural-to-mesenchymal gradient. Postoperative HRoR volume &amp;gt;1.6 cm\u00b3 predicted shorter overall survival (P\u2009=\u2009.04) and progression-free survival (P\u2009\u2009=\u2009\u2009.008).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>To our knowledge, this study provides the first prospective, biopsy-controlled, molecular validation of an AI model for mapping glioblastoma infiltration. By accurately identifying histologically and transcriptionally infiltrated regions, GlioMap offers a biologically grounded imaging biomarker that could guide extended resection and personalized radiotherapy planning, potentially improving tumor control and patient outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/neuonc\/noag088","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T11:38:17Z","timestamp":1776339497000},"page":"1999-2013","source":"Crossref","is-referenced-by-count":6,"title":["Prospective biopsy-controlled validation of an AI model for predicting glioblastoma infiltration: Results from the SupraGlio trial"],"prefix":"10.1093","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1667-8548","authenticated-orcid":false,"given":"Santiago","family":"Cepeda","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, R\u00edo Hortega University Hospital , 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