Green, Destiny L.

Abstract High-grade gliomas (HGGs) are aggressive, infiltrative brain tumors with poor survival outcomes and limited therapeutic options. Their spatial and molecular heterogeneity necessitates large, well-curated datasets integrating imaging, clinical, and genomic information to enable precision medicine and drive novel treatment development. Using the Medtronic StealthStation neuronavigation system, we collected over 1,000 spatially localized intraoperative biopsy samples from more than 250 patients undergoing resection for glioma at Mayo Clinic and partnering sites. Each biopsy site was recorded with 3D coordinates, labeled in real time, flash-frozen, and annotated with metadata including collection time, anatomical location, and surgical plan. Samples were processed and entered into a secure database along with the corresponding sampling coordinates, frozen pathology, whole-exome and RNA sequencing data, 5-ALA fluorescence status, patient demographics, and T1, T1Gd, T2, and T2-FLAIR MRI. This multimodal dataset supports radiogenomic research by enabling precise mapping of imaging features to molecular characteristics. A subset of this data, including 268 biopsies from 52 patients (25 male, 27 female) with reported intraoperative 5-ALA fluorescence, was used to develop a radiomics model predicting locoregional patterns of 5-ALA positivity based on preoperative MRI. Image features were extracted from the biopsy sample coordinates across multiple MRI sequences and paired with corresponding 5-ALA fluorescence status to train the model for regional fluorescence prediction. The final model achieved 83% accuracy on the training set and 86% on the validation set using a 70-15-15 data split; this included 208 samples for training and 42 for validation, stratified by patient to ensure no overlap of samples from the same individual across sets. These findings demonstrate the feasibility of predicting 5-ALA fluorescence using radiomic features from standard preoperative MRI, offering a promising noninvasive strategy for improving intraoperative decision-making and enabling more precise, personalized resections in patients with high-grade gliomas.

Abstract High grade gliomas (HGGs) are aggressive brain tumors that are difficult to remove completely, leading to poor survival rates. Contrast enhancement on T1Gd magnetic resonance imaging (MRI) has traditionally been used to guide resection, however it often underestimates true tumor burden, adding a layer of uncertainty for surgeons during pre-operative planning. Fluorescence guided surgery using 5-aminolevulinic acid (5-ALA) has emerged as an intraoperative solution and understanding it in conjunction with MRI features can address the limitations of routine T1Gd imaging during surgical planning. Here we investigate sex-specific patterns in HGGs using 5-ALA fluorescence and imaging features. We analyzed a patient dataset of 202 multiregional MRI-localized biopsies from 42 HGG patients (20 male and 22 female). Data included patient demographics, 5-ALA status (positive or negative), MRI annotations (CE = contrast enhancement, NE = non-enhancement, BAT = brain around tumor non-enhancement), and survival outcomes. Statistical analyses included Wilcoxon rank-sum tests, Kruskal-Wallis tests, and chi-squared tests to assess differences in imaging annotations and 5-ALA positive vs negative status among sex cohorts. Among all samples, CE and BAT were associated with higher 5-ALA positivity, while NE was associated with higher 5-ALA negativity (p = 0.02119). Female patients were less likely to have detectable 5-ALA in their multiregional biopsy samples than males (p < 0.0001). CE at the biopsy location was more likely to be indicative of 5-ALA positivity in males than females (p = 0.001927); whereas NE was associated with higher 5-ALA negativity in females than males (p = 0.03426). BAT was associated with higher 5-ALA positivity in males than females (p = 0.03895). Our study reveals sex-specific patterns in 5-ALA fluorescence and image features among HGG patients. These unique features may serve as potential pre-surgical markers for tumor regions that are more likely to benefit from 5-ALA-guided resection.