Timing of Planning Magnetic Resonance Imaging and Patient Selection for Adaptive Radiation Therapy in Newly Diagnosed High-Grade Glioma

Abstract

Purpose: Radiation therapy (RT) planning for high-grade glioma (HGG) typically relies on a single postoperative magnetic resonance image (MRI), assuming stable tumor and brain architecture throughout treatment. Though the gross tumor volume and surrounding tissues can shift after surgery and throughout RT, its rate of change, predictors of the movement magnitude, and impact on different dosing strategies are not well understood. This study uses meta-analysis and prospective MRI data to optimize MRI timing and identify patients who may benefit from adaptive RT (ART).

Methods and materials: We performed a meta-analysis of 12 studies (405 patients) to quantify postresection brain morphology changes. Additionally, we prospectively collected MRIs from 17 newly diagnosed HGG patients who underwent resection and RT. Nonlinear image registration tracked voxel-wise movement from postsurgery through RT and follow-up. We analyzed changes in gross tumor volume, clinical target volume (CTV), and non-CTV influx volume (nCIV) across 8 CTV strategies. Exponential models predicted the magnitude and rate of postresection changes and optimal MRI timing.

Results: Both meta-analysis and prospective data showed that morphological changes followed an exponential decay, with 80% of shifts occurring within ∼30 days of resection. The nCIV was strongly predicted by T2-weighted fluid-attenuated inversion recovery volume and CTV margin strategy (86% accuracy for T1-based and 80% for T2-weighted fluid-attenuated inversion recovery-based CTVs). To minimize nCIV in patients starting RT >3 weeks postsurgery, our model suggests acquiring an additional MRI before RT. Otherwise, RT planning should be adaptive.

Conclusions: Acquiring a delayed planning MRI or performing ART based on recent MRIs may optimize RT delivery for patients with larger tumors and specific CTV strategies. We propose a simple, clinically feasible algorithm for selecting patients and determining optimal MRI timing in prospective clinical trials of HGG ART.