Background: Diffusion magnetic resonance (MR) characteristics are a predictive imaging biomarker for survival benefit in recurrent glioblastoma treated with anti-vascular endothelial growth factor (VEGF) therapy; however, its use in large volume recurrence has not been evaluated.
Objective: To determine if diffusion MR characteristics can predict survival outcomes in patients with large volume recurrent glioblastoma treated with bevacizumab or repeat resection.
Methods: A total of 32 patients with large volume (>20 cc or > 3.4 cm diameter) recurrent glioblastoma treated with bevacizumab and 35 patients treated with repeat surgery were included. Pretreatment tumor volume and apparent diffusion coefficient (ADC) histogram analysis were used to phenotype patients as having high (>1.24 μm2/ms) or low (<1.24 μm2/ms) ADCL, the mean value of the lower peak in a double Gaussian model of the ADC histogram within the contrast enhancing tumor.
Results: In bevacizumab and surgical cohorts, volume was correlated with overall survival (Bevacizumab: P = .009, HR = 1.02; Surgical: P = .006, HR = 0.96). ADCL was an independent predictor of survival in the bevacizumab cohort (P = .049, HR = 0.44), but not the surgical cohort (P = .273, HR = 0.67). There was a survival advantage of surgery over bevacizumab in patients with low ADCL (P = .036, HR = 0.43) but not in patients with high ADCL (P = .284, HR = 0.69).
Conclusion: Pretreatment diffusion MR imaging is an independent predictive biomarker for overall survival in recurrent glioblastoma with a large tumor burden. Large tumors with low ADCL have a survival benefit when treated with surgical resection, whereas large tumors with high ADCL may be best managed with bevacizumab.
Keywords: ADC histogram analysis; Bevacizumab; Diffusion MRI; Recurrent glioblastoma; T1 subtraction.
Copyright © 2020 by the Congress of Neurological Surgeons.