Introduction: Transcranial MR guided focused ultrasound (MRgFUS) thalamotomy has been proposed as a new treatment for essential tremor and Parkinson’s disease. The optimal parameters and technique used during the sonication process is currently under investigation for this new technology. We reviewed the procedural data from three clinical trials of thalamotomy to correlate patient outcomes with acoustic parameters, thermal dose, MRI and probabilistic DTI.
Methods: Patient outcomes were assessed using CRST scores and UPDRS scores. Acoustic parameters included the number of elements, energy, time, and number of sonications. Thermal dose was estimated using 240 cumulative effective minutes at 43C (240CEM43) and achievement of a minimum of 54C for at least 3s as indicated by MR thermography. DTI was used to identify the areas of maximum thalamocortical connections to the pre-central gyrus. Overlap of lesions with DTI maps was performed with Matlab.
Results: A linear relationship exists between the predicted lesion diameter and the actual. POD1 lesion sizes were 40% and 28% of predicted based on MR thermography maps of temperature thresholds and 240CEM43 thresholds respectively. 1 month actual vs. predicted was 26% independent of the predicted model. Errors in the predicted size is driven by 2D thermometry scanning error which can be as high as 1mm. Lesion volume and patient outcomes did not correlate owing to variability of lesion overlap with the DTI maps. ET Patients had improved tremor scores following treatment at 1 year vs. PD patients (75% improvement vs. 41%).
Conclusions: Transcranial MRgFUS thalamotomy has demonstrated tremor improvement in ET and PD; but there is variability in the outcomes and durability. Optimal acoustic parameters, position, and thermal dose are critical. Intra-procedural modeling can improve and predict the lesioning process with less error. Application of DTI for Vim targeting could refine lesion placement and improve patient outcomes.
Patient Care: This research will improve outcomes by improving the predictability of MRgFUS lesion procedures based on intra-procedural data and DTI imaging.
Learning Objectives: To highlight the results of work being performed to improve the predictability of MRgFUS intra-procedural data in accurately predicting outcomes during lesioning procedures.