Probabilistic mapping of gait changes after STN-DBS for Parkinson's disease

Abstract

Introduction

Gait disturbances causing impaired mobility are common in Parkinson's disease after bilateral deep brain stimulation of the subthalamic nucleus. We describe subthalamic subregions where neurostimulation had a positive effect on gait or provoked gait disturbances.

Methods

98 patients were classified according to changes in MDS-UPDRS III gait items: gait improvement (≥1-point improvement in items 3.10 and/or 3.11), gait deterioration (≥1-point worsening, confirmed by repeated clinical documentation), or no change. We performed a segregation analysis for (1) and (3) by simulating volumes of tissue activated and comparing aggregated spatial data and calculated probability maps to forecast gait performance and the parkinsonism control.

Results

42 patients experienced improvement of presurgical gait problems after stimulation. Seven patients showed gait deteriorations one-year post-implantation. Active contacts were more ventrally located for gait deterioration versus gait improvement. Voxel-wise probabilistic mapping of gait changes in the subthalamic area were able to forecast patient specific gait performance based on individual stimulation volume (LOOCV R² = 0.45; p < 0.01) but was not associated with long-term parkinsonism control. Whereas a probabilistic map trained on MDS-UPDRS-III changes was predictive for clinical improvement in parkinsonism (R² = 0.18; p < 0.01).

Discussion

Probabilistic mapping showed a strong correlation with therapy outcomes, especially gait improvement, and provided predictive value at the individual level. While the concept of sweet- or sourspots was insufficient to explain individual variability, the heatmap-based approach allowed symptom-specific topographies to be identified. Our findings support the use of probabilistic mapping as a valuable tool to guide individualized reprogramming strategies for improving mobility in Parkinson's disease.