Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning.

Journal: Nature communications
PMID: 34031407

Abstract

Commonly used for Parkinson's disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.

Authors

  • Alexandre Boutet
    Joint Department of Medical Imaging, University of Toronto, Toronto, Canada.
  • Radhika Madhavan
  • Gavin J B Elias
    Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
  • Suresh E Joel
  • Robert Gramer
    Division of Global Neurosurgery and Neurology, Duke University Medical Center, Durham, North Carolina, USA.
  • Manish Ranjan
    NanoHealth, NanoCare Health Services, Hyderabad, India.
  • Vijayashankar Paramanandam
    Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Division of Neurology, University of Toronto, Toronto, ON, Canada.
  • David Xu
    Department of BioHealth Informatics, Indiana University School of Informatics and Computing , Indianapolis, Indiana 46202, United States.
  • Jurgen Germann
    Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
  • Aaron Loh
    Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
  • Suneil K Kalia
    Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
  • Mojgan Hodaie
    Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
  • Bryan Li
    Joint Department of Medical Imaging, University of Toronto, Toronto, Canada.
  • Sreeram Prasad
    Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Division of Neurology, University of Toronto, Toronto, ON, Canada.
  • Ailish Coblentz
    Joint Department of Medical Imaging, University of Toronto, Toronto, Canada.
  • Renato P Munhoz
    Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Division of Neurology, University of Toronto, Toronto, ON, Canada.
  • Jeffrey Ashe
    GE Global Research Center, Niskayuna, NY, USA.
  • Walter Kucharczyk
    Joint Department of Medical Imaging, University of Toronto, Toronto, Canada.
  • Alfonso Fasano
    Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Division of Neurology, University of Toronto, Toronto, ON, Canada.
  • Andres M Lozano
    Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada. lozano@uhnresearch.ca.

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