<scp>Magnetic resonance imaging</scp> ‐based ranking of resection‐related cortical candidates for presurgical localization in epilepsy using a prior‐aware graph attention transformer

Abstract Objective Structural magnetic resonance imaging (MRI) is fundamental to presurgical localization in epilepsy, but subtle epilepsy‐related abnormalities may not always be apparent on routine review. This study aimed to develop and externally validate an MRI‐only graph attention transformer for ranking resection‐related cortical candidates and to evaluate its reader‐level utility. Methods Graph Attention Transformer for Epilepsy‐Related Candidate Zones (GATEZ) was developed using preoperative three‐dimensional T1‐weighted MRI from the publicly released IDEAS (Imaging Database for Epilepsy and Surgery) database. Participants with a 12‐month International League Against Epilepsy class 1 outcome were split into training, validation, and internal test sets ( n = 171/37/37). Each participant was represented as a 1000‐parcel cortical graph with five regional morphometric features and an individualized Morphometric Inverse Divergence network; postoperative resection masks served as the surgical reference standard for model supervision. External validation used 183 consecutive surgical participants with epilepsy who underwent hybrid 18 F‐fluorodeoxyglucose ( 18 F‐FDG) positron emission tomography (PET)/MRI, with MRI only used for model inference. Reader‐level utility was evaluated in a blinded three‐reader study comparing MRI alone, MRI plus 18 F‐FDG PET, and MRI plus GATEZ. Results In the internal test cohort, GATEZ placed at least one resection‐overlapping parcel within the Top‐10 ranked candidates in 92% of participants, with a mean Top‐10 positive predictive value of 62%. Performance remained stable in the independent external cohort, with an 87% Top‐10 hit rate and 59% mean Top‐10 positive predictive value. Node‐level area under the precision–recall curve was .29 internally and .27 externally, indicating stable enrichment of resection‐related regions among the highest ranked candidates. In the blinded reader study, MRI + GATEZ improved detection compared with MRI alone (74%–78% vs. 58%–66% across readers; adjusted p ≤ .001 for all readers) and performed similarly to MRI + FDG (78%–80% across readers; adjusted p ≥ .34 for all readers). Significance GATEZ generates a concise Top‐ K shortlist of resection‐related cortical candidates and may serve as a practical second‐look aid for presurgical localization.