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Ann Neurol. 2017 Jul;82(1):67-78. doi: 10.1002/ana.24974.

Connectivity Predicts deep brain stimulation outcome in Parkinson disease.

Author information

1
Berenson-Allen Center for Noninvasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
2
Department of Neurology, Movement Disorder and Neuromodulation Unit, Charité-Universitätsmedizin, Berlin, Germany.
3
Department of Neurology, Würzburg University Hospital, Würzburg, Germany.
4
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah.
5
Institute of Software Engineering and Theoretical Computer Science, Neural Information Processing Group, Berlin Technical University, Berlin, Germany.
6
Department of Bioengineering, Northeastern University, Boston, MA.
7
NeuroCure Clinical Research Center, Charité-Universitätsmedizin, Berlin, Germany.
8
Department of Neurosurgery, Würzburg University Hospital, Würzburg, Germany.
9
Clinic of Neurology and Stereotactic Neurosurgery, Otto von Guericke University, Magdeburg, Germany.
10
Neurology Moves, Berlin, Germany.
11
Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA.
12
Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA.

Abstract

OBJECTIVE:

The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort.

METHODS:

A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center.

RESULTS:

In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p < 0.001). This same connectivity profile predicted response in an independent patient cohort (p < 0.01). Structural and functional connectivity were independent predictors of clinical improvement (p < 0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients.

INTERPRETATION:

Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. Ann Neurol 2017;82:67-78.

PMID:
28586141
PMCID:
PMC5880678
DOI:
10.1002/ana.24974
[Indexed for MEDLINE]
Free PMC Article

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