Connectivity Predicts deep brain stimulation outcome in Parkinson disease
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...
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| Published in | Annals of neurology Vol. 82; no. 1; pp. 67 - 78 |
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| Main Authors | , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Wiley Subscription Services, Inc
01.07.2017
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| Subjects | |
| Online Access | Get full text |
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| 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 |
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| AbstractList | 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 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. 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. 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. 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. 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 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.OBJECTIVEThe 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.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.METHODSA 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.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.RESULTSIn 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.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.INTERPRETATIONEffective 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. |
| Author | Wenzel, Gregor Schmitz‐Hübsch, Tanja Nickl, Robert Kupsch, Andreas Horn, Andreas Fang, Qianqian Reich, Martin Volkmann, Jens Kühn, Andrea A. Fox, Michael D. Li, Ningfei Vorwerk, Johannes |
| AuthorAffiliation | 5 Institute of Software Engineering and Theoretical Computer Science, Neural Information Processing Group, Berlin Technical University, Berlin, Germany 9 Clinic of Neurology and Stereotactic Neurosurgery, Otto von Guericke University, Magdeburg, Germany 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 4 Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah 3 Department of Neurology, Würzburg University Hospital, Würzburg, Germany 8 Department of Neurosurgery, Würzburg University Hospital, Würzburg, Germany 10 Neurology Moves, Berlin, Germany 12 Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 6 Department of Bioengineering, Northeastern University, Boston, MA 7 NeuroCure Clinical Research C |
| AuthorAffiliation_xml | – name: 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 – name: 10 Neurology Moves, Berlin, Germany – name: 8 Department of Neurosurgery, Würzburg University Hospital, Würzburg, Germany – name: 9 Clinic of Neurology and Stereotactic Neurosurgery, Otto von Guericke University, Magdeburg, Germany – name: 11 Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA – name: 3 Department of Neurology, Würzburg University Hospital, Würzburg, Germany – name: 5 Institute of Software Engineering and Theoretical Computer Science, Neural Information Processing Group, Berlin Technical University, Berlin, Germany – name: 4 Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah – name: 6 Department of Bioengineering, Northeastern University, Boston, MA – name: 7 NeuroCure Clinical Research Center, Charité–Universitätsmedizin, Berlin, Germany – name: 2 Department of Neurology, Movement Disorder and Neuromodulation Unit, Charité–Universitätsmedizin, Berlin, Germany – name: 12 Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA |
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The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain... The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but... Objective The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain... |
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| SubjectTerms | Aged Brain Case-Control Studies Computer networks Connectome Cortex (motor) Deep Brain Stimulation Electrical stimuli Female Humans Male Middle Aged Motor Cortex - physiology Motor task performance Movement disorders Neural networks Neurodegenerative diseases Neuroimaging Nuclei Parkinson Disease - therapy Parkinson's disease Patients Predictions Solitary tract nucleus Stimulation Structure-function relationships Subthalamic nucleus Subthalamic Nucleus - physiology Supplementary motor area Training Treatment Outcome |
| Title | Connectivity Predicts deep brain stimulation outcome in Parkinson disease |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fana.24974 https://www.ncbi.nlm.nih.gov/pubmed/28586141 https://www.proquest.com/docview/1922852524 https://www.proquest.com/docview/1906466381 https://pubmed.ncbi.nlm.nih.gov/PMC5880678 |
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