Focused ultrasound capsulotomy: predicting the probability of successful lesioning based on skull morphology.
Authors
Affiliations (7)
Affiliations (7)
- 1Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Toronto.
- 2Division of Neurosurgery, Sunnybrook Health Sciences Centre, Toronto.
- 3Institute of Medical Sciences, University of Toronto.
- 7Research Design and Biostatistics, Sunnybrook Research Institute, Toronto, Ontario, Canada.
- 4Physical Sciences Platform, Sunnybrook Research Institute, Toronto.
- 5Department of Medical Biophysics, University of Toronto.
- 6Institute of Biomedical Engineering, University of Toronto; and.
Abstract
MR-guided focused ultrasound anterior capsulotomy (MRgFUS-AC) is an incisionless ablative procedure, which has shown reassuring safety and compelling efficacy in the treatment of refractory obsessive-compulsive disorder and major depressive disorder. However, in some patients lesions cannot be reliably generated due to patient-specific skull morphologies and properties. Despite screening patients for MRgFUS-AC using skull density ratio (SDR), up to 25% of cases experience treatment failure. This variability in technical success limits the real-world applicability of an otherwise highly impactful treatment, and a better predictor of success is needed. This study analyzed data from 60 attempted MRgFUS-AC treatments in 57 patients between 2017 and 2024. Treatments were categorized as success or failure based on lesion volume. Preoperative parameters, including SDR, skull thickness, angle of incidence, CSF volume, brain and head volumes, and lesion side, were recorded. Logistic and machine learning models were evaluated to construct a preoperative model to predict the probability of technical success. A total of 157 lesions were treated, of which 31 experienced treatment failure. Higher SDR, thinner skulls, and lower incident angles were significantly associated with successful outcomes (all p < 0.05). The logistic regression model performed the best among the models tested, with an accuracy of 0.81 ± 0.07 and an F1 score of 0.89 ± 0.04. The model was incorporated into a predictive tool to aid in identifying candidates for MRgFUS-AC. SDR, skull thickness, and angle of incidence significantly influenced the likelihood of successful MRgFUS-AC lesioning. Incorporating these three parameters into a predictive tool can dramatically reduce technical failure rates and may be especially informative in patients with an SDR between 0.35 and 0.55.