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 cm. 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/1765/134571
Otology & Neurotology

Langenhuizen, P.P.J.H. (Patrick P J H), Zinger, S. (Svetlana), Leenstra, S, Kunst, H.P.M, Mulder, J.J.S, Hanssens, P, … Verheul, J.B. (Jeroen B.). (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