P15.08.a mri phenotypes of glioblastomas early after treatment are suggestive of overall patient survival

Neuro-oncology(2023)

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Abstract BACKGROUND Distinguishing between true tumor progression (TP) and treatment induced abnormalities (e.g. pseudo-progression (PP) after radiotherapy) early after treatment on conventional MRI scans remains challenging for glioblastomas (GBM). Despite MRI perfusion techniques being promising in differentiating between TP and PP, individual imaging markers have only showed a modest association with tumor progression and overall survival. Therefore, we aimed to establish brain MRI phenotypes of glioblastomas early after treatment by combined analysis of radiological scoring of structural and perfusion tumor characteristics and assessed the relation with recurrence rate and overall-survival time. MATERIAL AND METHODS MR images and clinical data were retrospectively collected from 67 histologically confirmed GBM patients. Non-invasive (arterial spin labeling, ASL) and contrast-based (dynamic susceptibility contrast DSC) perfusion MRI, T2-FLAIR and post-contrast 3D-T1w scans were acquired on a 3T-MR scanner at around 3 months post-radiotherapy. Structural (presence and type of (enhancing) lesion patterns) and perfusion (increase, decrease or iso) MRI markers (MRIm) were visually scored by a neuroradiologist. Additionally, volume and eccentricity of the enhancing and T2-hyperintense areas were calculated.Subsequently, patients were grouped based on their similarity on tumor perfusion and structural brain MRIm by means of hierarchical clustering. These subgroups were then compared using a chi-square test and one way ANOVA. Survival outcome was assessed using a multivariate cox proportional hazard model, both unadjusted and adjusted for age, KPS and extension of resection. Progression at 9 months (when unavailable at 3/6 months) post-radiotherapy and clinical parameters were compared between subgroups using a chi-square test. RESULTS Four subgroups of patients were established with significantly different tumor perfusion and structural radiological markers (p≤0.05) and therefore showed distinct MRI phenotypes of GBM. Subgroup 1 had less aggressive MRIm with mostly nodular enhancing lesions; subgroup 2 had the least aggressive MRIm with mostly patchy enhancing lesions; subgroup 3 showed the most aggressive MRIm and subgroup 4 showed moderately aggressive MRIm. TP and PP did not differ significantly between subgroups (p = 0.775). However, after performing an adjusted and unadjusted cox regression analysis we found that subgroup 1 and 3 were at increased risk of mortality, respectively (subgroup 1 - HR: 2.649 (95% CI: 1.119 - 6.270; subgroup 3 - HR: 2.363 (95% CI: 1.110 - 5.030); p=0.03). CONCLUSION Our study suggests that differences in MRI phenotypes of GBM at 3 months post-radiotherapy can be indicative of overall patient survival. The early prognostic information our method provides might in the future be beneficial for treatment decisions in GBM patients.
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glioblastomas,overall patient survival
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