Objective: Stereotactic radiosurgery (SRS) is one of the treatment modalities for vestibular schwannomas (VSs). However, tumor progression can still occur after treatment. Currently, it remains unknown how to predict long-term SRS treatment outcome. This study investigates possible magnetic resonance imaging (MRI)-based predictors of long-term tumor control following SRS. Study Design: Retrospective cohort study. Setting: Tertiary referral center. Patients: Analysis was performed on a database containing 735 patients with unilateral VS, treated with SRS between June 2002 and December 2014. Using strict volumetric criteria for long-term tumor control and tumor progression, a total of 85 patients were included for tumor texture analysis. Intervention(s): All patients underwent SRS and had at least 2 years of follow-up. Main Outcome Measure(s): Quantitative tumor texture features were extracted from conventional MRI scans. These features were supplied to a machine learning stage to train prediction models. Prediction accuracy, sensitivity, specificity, and area under the receiver operating curve (AUC) are evaluated. Results: Gray-level co-occurrence matrices, which capture statistics from specific MRI tumor texture features, obtained the best prediction scores: 0.77 accuracy, 0.71 sensitivity, 0.83 specificity, and 0.93 AUC. These prediction scores further improved to 0.83, 0.83, 0.82, and 0.99, respectively, for tumors larger than 5 cm3 . Conclusions: Results of this study show the feasibility of predicting the long-term SRS treatment response of VS tumors on an individual basis, using MRI-based tumor texture features. These results can be exploited for further research into creating a clinical decision support system, facilitating physicians, and patients to select a personalized optimal treatment strategy.

Machine, learning—Magnetic resonance imaging—Radiomics— Stereotactic radiosurgery—Treatment prediction—Tumor, texture—Vestibular schwannoma.
dx.doi.org/10.1097/mao.0000000000002886, hdl.handle.net/1765/132007
Otology & Neurotology
Department of Neurosurgery

Langenhuizen, P., Zinger, S, Leenstra, S, Kunst, HPM, Mulder, JJS, Hanssens, P.E., … Verheul, JB. (2020). Radiomics-Based Prediction of Long-Term Treatment Response of Vestibular Schwannomas Following Stereotactic Radiosurgery. Otology & Neurotology, 41(10), E1321–E1327. doi:10.1097/mao.0000000000002886