ArticleNature communications2025
Boundary complexity of cortical and subcortical areas predicts deep brain stimulation outcomes in Parkinson's disease.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Matters arising: critical appraisal of device aided therapy outcomes in Parkinson's disease.NPJ Parkinson's disease · 2026Article
- Integrating standard and native spaces for radiomics and brain network analysis in Alzheimer's disease diagnosis and prognosis.Journal of neurology · 2026Article
- Three-Dimensional Point-Cloud Learning for Patient-Specific Deep Brain Stimulation Motor Response Prediction in Parkinson Disease.BME frontiers · 2026Article
- Preoperative Functional Connectivity Predicts Antiparkinson Drug Change after Deep Brain Stimulation.Movement disorders : official journal of the Movement Disorder Society · 2026Article
- A multimodal machine learning model for predicting postoperative worsening of FOGQ in Parkinson's disease following STN-DBS.Frontiers in neurologyArticle
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Authors and funding
10 authors.
Funding
Abstract
While deep brain stimulation (DBS) remains an effective therapy for Parkinson's disease (PD), sources of variance in patient outcomes are still not fully understood, underscoring a need for better prognostic criteria. Here, we leveraged routinely collected T1-weighted (T1-w) magnetic resonance imaging (MRI) data to derive patient-specific measures of brain structure and evaluate their usefulness in predicting changes in PD medications in response to DBS. Preoperative T1-w MRI data from 231 patients with PD were used to extract regional measures of fractal dimension (FD), sensitive to the structural complexities of cortical and subcortical brain. FD was validated as a biomarker of PD progression through comparison of patients with PD and healthy controls (HCs). This analysis revealed significant group differences in FD across nine brain regions, including frontal, occipital, insular, and basal ganglia areas, which supports its utility as a marker of PD. We evaluated the impact of adding imaging features (FD) to a clinical model that included demographics and clinical parameters (age, sex, total number and location of DBS electrodes), and preoperative motor response to levodopa. This model aimed to explain variance and predict changes in medication following DBS. Regression analysis revealed that inclusion of the FD of distributed brain areas correlated with post-DBS reductions in medication burden, explaining an additional 13.6% of outcome variance (R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.