Preoperative Texture Analysis Using 11C-Methionine Positron Emission Tomography Predicts Survival after Surgery for Glioma

Abstract

Background: Positron emission tomography with 11C-methionine (MET) is well established in the diagnostic work-up of malignant brain tumors. Texture analysis is a novel technique for extracting information regarding relationships among surrounding voxels, in order to quantify their inhomogeneity. This study evaluated whether the texture analysis of MET uptake has prognostic value for patients with glioma. Methods: We retrospectively analyzed adults with glioma who had undergone preoperative metabolic imaging at a single center. Tumors were delineated using a threshold of 1.3-fold of the mean standardized uptake value for the contralateral cortex, and then processed to calculate the texture features in glioma. Results: The study included 42 patients (median age: 56 years). The World Health Organization classifications were grade II (7 patients), grade III (17 patients), and grade IV (18 patients). Sixteen (16.1%) all-cause deaths were recorded during the median follow-up of 18.8 months. The univariate analyses revealed that overall survival (OS) was associated with age (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.01–1.08, p = 0.0093), tumor grade (HR 3.64, 95% CI 1.63–9.63, p = 0.0010), genetic status (p < 0.0001), low gray-level run emphasis (LGRE, calculated from the gray-level run-length matrix) (HR 2.30 × 1011, 95% CI 737.11–4.23 × 1019, p = 0.0096), and correlation (calculated from the gray-level co-occurrence matrix) (HR 5.17, 95% CI 1.07–20.93, p = 0.041). The multivariate analyses revealed OS was independently associated with LGRE and correlation. The survival curves were also significantly different (both log-rank p < 0.05). Conclusion: Textural features obtained using preoperative MET positron emission tomography may compliment the semi-quantitative assessment for prognostication in glioma cases.

Radiomics in Oncological PET Imaging: A Systematic Review—Part 1, Supradiaphragmatic Cancers

“…A total of 23 of the 220 studies focused on oligodendrogliomas, gliomas, and glioblastomas [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 ] employing several PET tracers: 11C-Metionine (n = 7), 18F-FET (n = 7), 18F-FDG (n = 4), 18F-FDOPA (n = 3), 18F-FLT (n = 1), 18F-FMISO (n = 1). These studies included an average of 78.4 patients (range: 32–160), 6/23 (26.1%) including more than 100 patients, 3/23 (13.0%) with prospective data and 8/23 (34.8%) with validation sets.…”

Radiomics for residual tumour detection and prognosis in newly diagnosed glioblastoma based on postoperative [11C] methionine PET and T1c-w MRI

“…Li et al 58 , Kickingereder et al, 59 and Chaddad et al 60 showed that a prognostic model built with second order texture features extracted from pre-treatment mpMRI are significantly associated to OS in GBM (C-index 0.70 58 , C-index 0.65 59 , log-rank test p -value < 0.01 60 ). Carles et al 33 and Manabe et al 61 observed that second-order texture features extracted from [18F]-FDG PET and MET-PET can predict OS (p 0.038 33 and p < 0.05 61 , respectively). Verma et al 62 found higher order pre-treatment MRI features as a prognostic marker for PFS in GBM (C-index 0.80).…”

“…In our review of relevant studies, as summarized in Table S13 , numerous pre-treatment MRI-based radiomics investigations focus on the patient prognosis in GBM 58 – 60 , 62 , 64 – 67 . However, only a limited number of studies incorporate pre-treatment MET-PET with small sample sizes (N = 42 61 , N = 52 63 ). Considering the significance of residual tumour burden as a prognostic imaging biomarker in GBM 18 , 19 , understanding the residual tumour status post-surgery may aid in refining treatment planning and tailoring therapies to the specific tumour burden, potentially improving treatment efficacy.…”