Abstract
Imbalance is the most commonly reported side effect following focused ultrasound (FUS) thalamotomy for essential tremor (ET). It remains unknown which patients are more likely to develop imbalance following FUS treatment. To identify preoperative and treatment-related sonication parameters that are predictive of imbalance following FUS treatment. We retrospectively collected demographic data, preoperative Fahn-Tolosa-Marin Clinical Rating Scale for Tremor (FTM) scores and FUS treatment parameters in patients undergoing FUS thalamotomy for treatment of ET. The presence of imbalance was evaluated at several discrete time-points with up to 4 years of follow-up. Multiple machine learning classifiers were built and evaluated, aiming to maximize accuracy while minimizing feature set. Of the 297 patients identified, the presence of imbalance peaked at 1 week following operation at 79%. This declined rapidly with 29% reporting imbalance at 3 months, and only 15% at 4 years. At 1 week, total preoperative FTM scores and Maximum Energy delivered in FUS could predict the presence of imbalance at 92.8% accuracy. At 3 months, the total preoperative FTM scores and maximum power delivered could predict the presence of imbalance with 90.6% accuracy. Post-operative lesion size and extent into thalamic nuclei, internal capsule, and subthalamic regions were identified as likely key underlying drivers of these predictors. A machine learning model based on preoperative tremor scores and maximum energy/power delivered predicted the development of short-term imbalance and long-term imbalance following FUS thalamotomy.
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