ArticleMovement disorders clinical practice2025
Functional Connectivity and Volumetrics Improve Outcome Prediction for Deep Brain Stimulation in Parkinson's Disease.
Article in Movement disorders clinical practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Predictive Models for Motor Outcomes From Deep Brain Stimulation in Parkinson's Disease: A Systematic Review.The European journal of neuroscience · 2026Pooled it
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Authors and funding
4 authors.
Funding
Abstract
backgroundDeep brain stimulation (DBS) targeting the subthalamic nucleus (STN) can effectively treat motor symptoms of Parkinson's disease (PD). However, optimal patient selection remains challenging due to the inadequacy of outcome predictors. Most clinicians rely on levodopa response to predict DBS motor outcomes, yet previous studies have identified other MRI-based predictors including resting-state functional connectivity (FC) and volumetric measures.
objectivesTo compare the predictive value of functional and volumetric MRI data with levodopa response alone for motor outcomes in STN DBS for PD.
methodsWe analyzed 65 participants who underwent STN DBS for PD at Washington University in St. Louis. We used relaxed LASSO regression to select factors including clinical, volumetric, and FC measures to generate predictive models for relative changes in motor scores post-DBS and assessed cross-validated performance. We then compared the relative influence of the predictive factors with standardized regression coefficients.
resultsAddition of MRI predictors (FC and volumetric) improved model fit and cross-validated model performance over levodopa response alone (levodopa alone: R
conclusionsIncluding MRI-based predictors significantly enhances the prediction of motor outcomes in STN DBS compared to levodopa response alone, with FC predictors demonstrating the greatest influence in the optimized model. External validation studies are necessary to confirm the clinical utility of these predictors in routine practice.
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