Evidence map›Paper›PMID 32002754›Full record

ArticleMedical & biological engineering & computing2020

Stimulation maps: visualization of results of quantitative intraoperative testing for deep brain stimulation surgery.

Ashesh Shah, Dorian Vogel, Fabiola Alonso, Jean-Jacques Lemaire, Daniela Pison, Jérôme Coste, Karin Wårdell, Erik Schkommodau, Simone Hemm

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Medical & biological engineering & computing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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.

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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Advances in Technical Aspects of Deep Brain Stimulation Surgery.Stereotactic and functional neurosurgery · 2023
    Review
  6. Review
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

9 authors.

Ashesh ShahInstitute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Dorian VogelInstitute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Fabiola AlonsoDepartment of Biomedical Engineering, Linköping University, Linköping, Sweden.
Jean-Jacques LemaireCNRS, SIGMA Clermont, Institut Pascal, Université Clermont Auvergne, Clermont-Ferrand, France.
Daniela PisonInstitute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Jérôme CosteCNRS, SIGMA Clermont, Institut Pascal, Université Clermont Auvergne, Clermont-Ferrand, France.
Karin WårdellDepartment of Biomedical Engineering, Linköping University, Linköping, Sweden.
Erik SchkommodauInstitute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Simone HemmInstitute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland. simone.hemm@fhnw.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep brain stimulation (DBS) is an established therapy for movement disorders such as essential tremor (ET). Positioning of the DBS lead in the patient's brain is crucial for effective treatment. Extensive evaluations of improvement and adverse effects of stimulation at different positions for various current amplitudes are performed intraoperatively. However, to choose the optimal position of the lead, the information has to be "mentally" visualized and analyzed. This paper introduces a new technique called "stimulation maps," which summarizes and visualizes the high amount of relevant data with the aim to assist in identifying the optimal DBS lead position. It combines three methods: outlines of the relevant anatomical structures, quantitative symptom evaluation, and patient-specific electric field simulations. Through this combination, each voxel in the stimulation region is assigned one value of symptom improvement, resulting in the division of stimulation region into areas with different improvement levels. This technique was applied retrospectively to five ET patients in the University Hospital in Clermont-Ferrand, France. Apart from identifying the optimal implant position, the resultant nine maps show that the highest improvement region is frequently in the posterior subthalamic area. The results demonstrate the utility of the stimulation maps in identifying the optimal implant position. Graphical abstract.

Indexed as

AccelerometryBrainData VisualizationDeep Brain StimulationHumansImage Processing, Computer-AssistedMicroelectrodesMonitoring, IntraoperativePrecision MedicineSurgery, Computer-AssistedTremorAccelerometryData visualizationDeep brain stimulationElectric field simulationsEssential tremor

Identifiers

PMID32002754
PMCPMC7156362

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.