{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T14:40:05Z","timestamp":1781534405748,"version":"3.54.5"},"reference-count":52,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T00:00:00Z","timestamp":1780876800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100021718","name":"University of West Attica","doi-asserted-by":"crossref","award":["80793"],"award-info":[{"award-number":["80793"]}],"id":[{"id":"10.13039\/501100021718","id-type":"DOI","asserted-by":"crossref"}]},{"award":["80793"],"award-info":[{"award-number":["80793"]}],"id":[{"id":"https:\/\/ror.org\/00r2r5k05","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Gliomas constitute the majority of primary brain tumors, and accurate diagnosis through MRI is essential for patient management. Existing computer-aided diagnosis approaches frequently rely on tumor segmentation frameworks. In this study, a segmentation-independent framework for volumetric low-grade versus high-grade glioma (LGG\/HGG) classification is proposed using a Convolutional Neural Network (CNN) designed through task-oriented Neural Architecture Search (NAS). The proposed method was evaluated on a multi-center dataset comprising 1194 patients with pre-operative MRI scans, including T1-CE and FLAIR sequences from four publicly available cohorts. NAS was conducted within a controlled search space to optimize a 3D U-Net\u2013based backbone using Tree-structured Parzen Estimator (TPE) combined with Hyperband pruning. The optimized backbone was enhanced with residual connections and Squeeze-and-Excitation (SE) attention mechanisms to improve feature representation and training stability. Internal validation employed repeated 5-fold cross-validation across all four multi-center datasets. An external experiment used REMBRANDT as a test cohort (49 LGG, 19 HGG). The proposed model achieved 88.25% internal accuracy and 75.51% external accuracy (macro-F1: 87.37% internal, 73.77% external), outperforming benchmark 3D CNNs. Explainable Artificial Intelligence (XAI) analysis based on Grad-CAM revealed robust tumor localization without segmentation supervision, validated against available ground-truth masks. Additional experiments demonstrated the model\u2019s generalization capacity, achieving 89.51% accuracy for IDH mutation prediction and 78.74% for multi-grade classification.<\/jats:p>","DOI":"10.3390\/jimaging12060254","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T16:25:16Z","timestamp":1780935916000},"page":"254","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Segmentation-Free Preoperative 3D MRI Classification of Low-Grade Versus High-Grade Glioma Using Task-Oriented Neural Architecture Search"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-5073-8531","authenticated-orcid":false,"given":"Christos Ch.","family":"Andrianos","sequence":"first","affiliation":[{"name":"Medical Image and Signal Processing Laboratory, Department of Biomedical Engineering, University of West Attica, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0223-2502","authenticated-orcid":false,"given":"Spiros A.","family":"Kostopoulos","sequence":"additional","affiliation":[{"name":"Medical Image and Signal Processing Laboratory, Department of Biomedical Engineering, University of West Attica, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2192-3520","authenticated-orcid":false,"given":"Ioannis K.","family":"Kalatzis","sequence":"additional","affiliation":[{"name":"Medical Image and Signal Processing Laboratory, Department of Biomedical Engineering, University of West Attica, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3252-4055","authenticated-orcid":false,"given":"Dimitris Th.","family":"Glotsos","sequence":"additional","affiliation":[{"name":"Medical Image and Signal Processing Laboratory, Department of Biomedical Engineering, University of West Attica, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0570-0909","authenticated-orcid":false,"given":"Pantelis A.","family":"Asvestas","sequence":"additional","affiliation":[{"name":"Medical Image and Signal Processing Laboratory, Department of Biomedical Engineering, University of West Attica, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6891-5256","authenticated-orcid":false,"given":"Dionisis A.","family":"Cavouras","sequence":"additional","affiliation":[{"name":"Medical Image and Signal Processing Laboratory, Department of Biomedical Engineering, University of West Attica, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2771-5562","authenticated-orcid":false,"given":"Emmanouil I.","family":"Athanasiadis","sequence":"additional","affiliation":[{"name":"Medical Image and Signal Processing Laboratory, Department of Biomedical Engineering, University of West Attica, 12241 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","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 Oncol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1038\/s41572-024-00516-y","article-title":"Glioma","volume":"10","author":"Weller","year":"2024","journal-title":"Nat. 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