Voxel-based 18 F-FET PET segmentation and automatic clustering of tumor voxels: A significant association with IDH1 mutation status and survival in patients with gliomas

Abstract

Introduction Aim was to develop a full automatic clustering approach of the time-activity curves (TAC) from dynamic 18 F-FET PET and evaluate its association with IDH1 mutation status and survival in patients with gliomas. Methods Thirty-seven patients (mean age: 45±13 y) with newly diagnosed gliomas and dynamic 18 F-FET PET before any histopathologic investigation or treatment were retrospectively included. Each dynamic 18 F-FET PET was realigned to the first image and spatially normalized in the Montreal Neurological Institute template. A tumor mask was semi-automatically generated from Z-score maps. Each brain tumor voxel was clustered in one of the 3 following centroids using dynamic time warping and k-means clustering (centroid #1: slowly increasing slope; centroid #2: rapidly increasing followed by slowly decreasing slope; and centroid #3: rapidly increasing followed by rapidly decreasing slope). The percentage of each dynamic 18 F-FET TAC within tumors and other conventional 18 F-FET PET parameters (maximum and mean tumor-to-brain ratios [TBR max and TBR mean ], time-to-peak [TTP] and slope) was compared between wild-type and IDH1 mutant tumors. Their prognostic value was assessed in terms of progression free-survival (PFS) and overall survival (OS) by Kaplan-Meier estimates. Results Twenty patients were IDH1 wild-type and 17 IDH1 mutant. Higher percentage of centroid #1 and centroid #3 within tumors were positively (P = 0.016) and negatively (P = 0.01) correlated with IDH1 mutated status. Also, TBR max , TBR mean , TTP, and slope discriminated significantly between tumors with and without IDH1 mutation (P range 0.01 to 0.04). Progression occurred in 22 patients (59%) at a median of 13.1 months (7.6–37.6 months) and 13 patients (35%) died from tumor progression. Patients with a percentage of centroid #1 > 90% had a longer survival compared with those with a percentage of centroid #1 < 90% (P = 0.003 for PFS and P = 0.028 for OS). This remained significant after stratification on IDH1 mutation status (P = 0.029 for PFS and P = 0.034 for OS). Compared to other conventional 18 F-FET PET parameters, TTP and slope were associated with PFS and OS (P range 0.009 to 0.04). Conclusions Based on dynamic 18 F-FET PET acquisition, we developed a full automatic clustering approach of TAC which appears to be a valuable noninvasive diagnostic and prognostic marker in patients with gliomas.