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

• Main Authors: Osamu Manabe, Shigeru Yamaguchi, Kenji Hirata, Kentaro Kobayashi, Hiroyuki Kobayashi, Shunsuke Terasaka, Takuya Toyonaga, Keiichi Magota, Yuji Kuge, Nagara Tamaki, Tohru Shiga, Kohsuke Kudo
• Format: Article
• Language: English
• Published: MDPI AG 2021-01-01
• Series: Diagnostics
• Subjects: methionine; positron emission tomography; glioma; texture analysis; prognosis
• Online Access: https://www.mdpi.com/2075-4418/11/2/189

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, <em>p </em>= 0.0093), tumor grade (HR 3.64, 95% CI 1.63–9.63, <em>p </em>= 0.0010), genetic status (<em>p </em>< 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, <em>p </em>= 0.0096), and correlation (calculated from the gray-level co-occurrence matrix) (HR 5.17, 95% CI 1.07–20.93, <em>p </em>= 0.041). The multivariate analyses revealed OS was independently associated with LGRE and correlation. The survival curves were also significantly different (both log-rank <em>p </em>< 0.05). Conclusion: Textural features obtained using preoperative MET positron emission tomography may compliment the semi-quantitative assessment for prognostication in glioma cases.