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| Home > Online First > BIOM-82. GLIOBLASTOMA BEYOND THE ENHANCING TUMOR MARGINS: A LONGITUDINAL CASE STUDY COMPARING FET PET WITH MRI-BASED AI INFILTRATION MAPS |
| Home > Online First > BIOM-82. GLIOBLASTOMA BEYOND THE ENHANCING TUMOR MARGINS: A LONGITUDINAL CASE STUDY COMPARING FET PET WITH MRI-BASED AI INFILTRATION MAPS |
| Abstract | FZJ-2026-01597 |
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2025
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Please use a persistent id in citations: doi:10.1093/neuonc/noaf201.0170
Abstract: AbstractBACKGROUNDGlioblastoma is the most common malignant brain tumor, with rapid proliferation, diffuse infiltration, and poor prognosis. Imaging plays a central role in its diagnosis, treatment planning, and disease monitoring. Positron Emission Tomography with O-(2-[18F]fluoroethyl)-L-tyrosine (FET PET) depicts metabolically active tumor irrespective of the blood-brain barrier integrity. Here, we compare FET PET with AI-generated infiltration maps (AI-InfM) derived from multiparametric MRI (mpMRI - T1, T1Gd, T2, T2-FLAIR, DSC) to identify viable tumor beyond the enhancing tumor, potentially corresponding to early recurrence sites.METHODSWe identified a patient with a newly-diagnosed glioblastoma in a non resectable eloquent area. Pre-operative scans were acquired at baseline and two follow-up timepoints, during and post-treatment, at six-month intervals. Each scanning session comprised a 50-minute dynamic FET PET scan and mpMRI performed at Research Center Juelich, Germany. AI-InfM, based on Support Vector Machines, were trained following within-patient, self-normalized measures of heterogeneity across pre-operative mpMRI of treatment-naïve glioblastoma in a subset of the public UPENN-GBM dataset. AI-InfM were then generated for the identified patient and compared with FET PET visually and quantitatively using clinically-established measures, e.g., tumor-to-brain ratios (TBR).RESULTSAlthough FET PET showed no increased tracer uptake at baseline, the AI-InfM identified a region with elevated signal. This region exhibited increased uptake of FET in the first follow-up scan (TBRmax from 1.9 at baseline to 2.2 at follow-up), supporting the AI-InfM’s early prediction. After completion of adjuvant temozolomide therapy, the third scan denoted the predicted high-risk area with reduced tumor activity across FET PET, AI-InfM, and mpMRI.CONCLUSIONSOur findings indicate potential complementary value of FET PET and mpMRI-derived AI-InfM, for early recurrence identification. This case study underscores the potential to enhance early detection of tumor progression, by virtue of the infiltrative spread in glioblastoma, and warrants continued development and evaluation in a larger multi-institutional cohort.
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