Comparison of pre-surgical mri findings from long-term ( 3 yrs) versus short-term (< 3 yrs) glioblastoma survivors: a blinded, case-control review

Abstract BACKGROUND The median overall survival of patients with glioblastoma (GBM) is 10-12 months and the five-year survival ranges from 5-10%. Favorable clinical and molecular prognostic markers have been described in the literature, although an individual patient’s prognosis cannot easily be predetermined on these features as shown in the NOB-LTS project by Briceno et al. (SNO 2021). Until now, no radiologic characteristics have been correlated with better patient outcomes. We reviewed eighteen MRI features to determine if these could aid the identification of long-term survivors (LTS). METHODS From the NOB-LTS cohort of our Natural History Study, 16 long-term survivals (LTS; ≥ 3 years survival post-diagnosis) were matched based on sex, age, and extent of resection to 32 control (STS, < 3 years survival post-diagnosis) patients with NGS-confirmed IDH-wt glioblastoma. Pre-surgical MRIs (T1, T1 post-contrast, T2, T2/FLAIR, DWI, ADC) were reviewed by three blinded reviewers and analyzed based on pre-set criteria. RESULTS T1 hypointensity occurred commonly in the LTS (71%) vs STS (29%) while central heterogeneous signal occurred commonly in the STS (73%) vs LTS (50%) patients. Restricted diffusion was seen in 82% of STS and 70% of LTS cases. No difference was seen in irregular enhancement, peripheral and grey matter enhancement on T1 post-contrast images. Evaluation of T2/FLAIR images showed no difference in the number of lobes involved, presence of mass effect, heterogeneity of the signal or the perilesional signal abnormality or involvement of grey matter. CONCLUSION Our results suggest that pre-surgical MRI might be a useful prognostic tool as T1 hypointensity more frequently, and T1 central heterogeneity less commonly seen in the LTS group. These imaging findings may provide additional insights regarding the differences in tumor biology between LTS and STS. Further validation and correlation with histological/molecular characteristics are planned to better predict patient outcomes with newly diagnosed glioblastoma.