1. Radiomics-Based Prediction of Long-Term Treatment Response of Vestibular Schwannomas Following Stereotactic Radiosurgery
- Author
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Langenhuizen, P.P.J.H. (Patrick P J H), Zinger, S. (Svetlana), Leenstra, S. (Sieger), Kunst, H.P.M. (Henricus P.M.), Mulder, J.J.S. (Jef), Hanssens, P. (Patrick), De With, P.H.N., Verheul, J.B. (Jeroen B.), Langenhuizen, P.P.J.H. (Patrick P J H), Zinger, S. (Svetlana), Leenstra, S. (Sieger), Kunst, H.P.M. (Henricus P.M.), Mulder, J.J.S. (Jef), Hanssens, P. (Patrick), De With, P.H.N., and Verheul, J.B. (Jeroen B.)
- Abstract
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.
- Published
- 2020
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