Evidence map›Paper›PMID 29800386›Full record

ArticleNeurosurgery2019

Microelectrode Recordings Validate the Clinical Visualization of Subthalamic-Nucleus Based on 7T Magnetic Resonance Imaging and Machine Learning for Deep Brain Stimulation Surgery.

Reuben R Shamir, Yuval Duchin, Jinyoung Kim, Remi Patriat, Odeya Marmor, Hagai Bergman, Jerrold L Vitek, Guillermo Sapiro, Atira Bick, Ruth Eliahou and 3 more

Open access · bronzeAbstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Neurosurgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 8% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

  1. Pooled it
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  7. Advances in Technical Aspects of Deep Brain Stimulation Surgery.Stereotactic and functional neurosurgery · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 6 institutions in 2 countries.

Reuben R ShamirSurgical Information Sciences, Minneapolis, Minnesota.
Yuval DuchinSurgical Information Sciences, Minneapolis, Minnesota.
Jinyoung KimDepartment of Electrical and Computer Engineering, Duke University, Durham, North Carolina.
Remi PatriatCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minnesota.
Odeya MarmorDepartment of Neurobiology, Institute of Medical Research-Israel Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel.
Hagai BergmanDepartment of Neurobiology, Institute of Medical Research-Israel Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel.
Jerrold L VitekDepartment of Neurology, University of Minnesota, Minneapolis, Minnesota.
Guillermo SapiroDepartment of Electrical and Computer Engineering, Duke University, Durham, North Carolina.
Atira BickDepartment of Radiology, Hadassah Medical Center, Jerusalem, Israel.
Ruth EliahouDepartment of Radiology, Hadassah Medical Center, Jerusalem, Israel.
Renana EitanDepartment of Neurobiology, Institute of Medical Research-Israel Canada (IMRIC), The Hebrew University-Hadassah Medical School, Jerusalem, Israel.
Zvi IsraelDepartment of Neurosurgery, Hadassah Medical Center, Jerusalem, Israel.
Noam HarelCenter for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minnesota.
Hadassah Medical Center · ILDuke University · USResonance Research (United States) · USUniversity of Minnesota · USHarvard University · USHebrew University of Jerusalem · IL

Funding

Pathophysiology-based approaches to deep brain stimulation for Parkinson's diseaseP50NS098573 · NINDS · UNIVERSITY OF MINNESOTA · PI VITEK, JERROLD L · 2016 to 2020
$9.1M
NMR Imaging and SpectroscopyP41EB015894 · NIBIB · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2012 to 2017
$8.4M
Institutional Center Cores for Advanced NeuroimagingP30NS076408 · NINDS · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2012 to 2020
$4.2M
Pathway targeted deep brain stimulation for Parkinson's diseaseR01NS085188 · NINDS · UNIVERSITY OF MINNESOTA · PI HAREL, NOAM, MCINTYRE, CAMERON · 2013 to 2017
$3.4M
NIBIB NIH HHS P41 EB015894NINDS NIH HHS P30 NS076408NINDS NIH HHS P50 NS098573NINDS NIH HHS R01 NS085188
6 · The paper itself

Abstract

backgroundDeep brain stimulation (DBS) of the subthalamic nucleus (STN) is a proven and effective therapy for the management of the motor symptoms of Parkinson's disease (PD). While accurate positioning of the stimulating electrode is critical for success of this therapy, precise identification of the STN based on imaging can be challenging. We developed a method to accurately visualize the STN on a standard clinical magnetic resonance imaging (MRI). The method incorporates a database of 7-Tesla (T) MRIs of PD patients together with machine-learning methods (hereafter 7 T-ML).

objectiveTo validate the clinical application accuracy of the 7 T-ML method by comparing it with identification of the STN based on intraoperative microelectrode recordings.

methodsSixteen PD patients who underwent microelectrode-recordings guided STN DBS were included in this study (30 implanted leads and electrode trajectories). The length of the STN along the electrode trajectory and the position of its contacts to dorsal, inside, or ventral to the STN were compared using microelectrode-recordings and the 7 T-ML method computed based on the patient's clinical 3T MRI.

resultsAll 30 electrode trajectories that intersected the STN based on microelectrode-recordings, also intersected it when visualized with the 7 T-ML method. STN trajectory average length was 6.2 ± 0.7 mm based on microelectrode recordings and 5.8 ± 0.9 mm for the 7 T-ML method. We observed a 93% agreement regarding contact location between the microelectrode-recordings and the 7 T-ML method.

conclusionThe 7 T-ML method is highly consistent with microelectrode-recordings data. This method provides a reliable and accurate patient-specific prediction for targeting the STN.

Indexed as

Machine LearningAgedDeep Brain StimulationFemaleHumansMagnetic Resonance ImagingMaleMicroelectrodesMiddle AgedNeuroimagingParkinson DiseaseSubthalamic NucleusDeep brain stimulationHigh-field MRIImage-based targetingMachine learningMicroelectrode recordingsSubthalamic nucleusSurgical planningValidation

Identifiers

PMID29800386
PMCPMC6500885
OpenAlexW2804197724

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.