Evidence map›Paper›PMID 34031407›Full record

Observational studyNature communications2021

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

Alexandre Boutet, Radhika Madhavan, Gavin J B Elias, Suresh E Joel, Robert Gramer, Manish Ranjan, Vijayashankar Paramanandam, David Xu, Jurgen Germann, Aaron Loh and 10 more

Registry-linked trialAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03153670 (3T MRI in Patients With Deep Brain Stimulation), which is not on this map. Cited by 152 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
152citing papers in PubMed, 7 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT03153670 narecruitingnot on this map

3T MRI in Patients With Deep Brain Stimulation (DBS)

TypeinterventionalSponsorUniversity Health Network, TorontoRan2017 to 2030Enrolled250ConditionsNeuro-Degenerative DiseaseArmsfMRI
3 · Its place in the literature

Who cites it

152 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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92 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors.

Alexandre Boutet *Joint Department of Medical Imaging, University of Toronto, Toronto, Canada.ORCID 0000-0001-6942-5195
Radhika Madhavan *GE Global Research Center, Niskayuna, NY, USA.
Gavin J B EliasDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
Suresh E JoelGE Healthcare, Bangalore, India.
Robert GramerDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
Manish RanjanDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-3338-8676
Vijayashankar ParamanandamEdmond 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 XuDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
Jurgen GermannDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-0995-8226
Aaron LohDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
Suneil K KaliaDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.
Mojgan HodaieDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada.ORCID 0000-0001-6278-4929
Bryan LiJoint Department of Medical Imaging, University of Toronto, Toronto, Canada.
Sreeram PrasadEdmond 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 CoblentzJoint Department of Medical Imaging, University of Toronto, Toronto, Canada.
Renato P MunhozEdmond 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 AsheGE Global Research Center, Niskayuna, NY, USA.
Walter KucharczykJoint Department of Medical Imaging, University of Toronto, Toronto, Canada.
Alfonso FasanoEdmond 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.ORCID 0000-0001-5346-0180
Andres M LozanoDivision of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, ON, Canada. lozano@uhnresearch.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Machine LearningAgedBrainBrain MappingDeep Brain StimulationFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMovement DisordersParkinson Disease

Identifiers

PMID34031407
PMCPMC8144408

What OpenQuestion holds

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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.