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Recurrent glioblastoma (rGBM) remains one of the most challenging conditions in neuro-oncology, with limited treatment options and ongoing difficulty in accurately assessing treatment response on conventional imaging. Bevacizumab is commonly used in the recurrent setting to reduce edema, decrease corticosteroid dependence, and improve progression-free survival; however, its effects on vascular permeability can lead to decreased contrast enhancement on MRI that may not reflect true tumor response and may even mask tumor progression. This makes interpretation of standard imaging findings particularly difficult.

Advanced MRI techniques may provide additional insight into tumor biology in this setting. Diffusion-weighted imaging, including Apparent Diffusion Coefficient (ADC) metrics, may reflect tumor cellularity, while perfusion imaging–derived cerebral blood volume (CBV) may better characterize tumor vascularity and angiogenic activity. The role of these imaging biomarkers in patient-specific therapeutic planning and response assessment following bevacizumab treatment in rGBM remains incompletely defined, particularly when compared with conventional contrast-enhanced imaging.

The objective of this study is to evaluate whether quantitative diffusion and perfusion MRI metrics, prior to bevacizumab treatment, in combination with progression-free survival (PFS) and overall survival (OS) in patients with recurrent glioblastoma, can help establish parameters that may aid clinically in predictive likelihood of positive or negative response to bevacizumab treatment. This retrospective cohort study utilizes an existing database within the Brain Tumor Imaging Laboratory (BTIL) at UCLA. Eligible patients include those with histologically confirmed glioblastoma, radiographic recurrence, treatment with bevacizumab, and available baseline diffusion and perfusion MRI studies prior to treatment initiation.

Primary imaging analysis includes baseline MRI sequences, including T1-weighted imaging with and without contrast, T2, FLAIR, perfusion, and ADC, to derive ADC-L and normalized CBV values from tumor regions of interest. Clinical outcomes include progression-free survival and overall survival. Planned statistical analyses include descriptive analyses, Kaplan–Meier survival curves, and Cox proportional hazards modeling to evaluate whether ADC-L and CBV values are associated with clinically meaningful differences in treatment response and survival outcomes in patients with rGBM prior to bevacizumab initiation.

This study aims to better define the clinical utility of advanced MRI biomarkers in recurrent glioblastoma and strengthen the role of quantitative imaging in treatment assessment and prognostication.