Evidence map›Paper›PMID 30009208›Full record

ArticleAnnals of clinical and translational neurology2018

Using automated electrode localization to guide stimulation management in DBS.

Mikkel V Petersen, Andreas Husch, Christine E Parsons, Torben E Lund, Niels Sunde, Karen Østergaard

Abstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Toward Electrophysiology-Based Intelligent Adaptive Deep Brain Stimulation for Movement Disorders.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2019
    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

6 authors.

Mikkel V PetersenCenter of Functionally Integrative Neuroscience (CFIN) Department of Clinical Medicine Aarhus University Nørrebrogade 44 8000 Aarhus C Denmark.ORCID 0000-0001-7760-6797
Andreas HuschNational Department of Neurosurgery Centre Hospitalier de Luxembourg 4 Rue Ernest Barble Luxembourg (City) Luxembourg.ORCID 0000-0001-9404-5127
Christine E ParsonsInteracting Minds Centre Department of Clinical Medicine Aarhus University Jens Chr. Skous Vej 7 Aarhus C 8000 Denmark.ORCID 0000-0003-2856-6308
Torben E LundCenter of Functionally Integrative Neuroscience (CFIN) Department of Clinical Medicine Aarhus University Nørrebrogade 44 8000 Aarhus C Denmark.ORCID 0000-0002-9002-4676
Niels SundeDepartment of Neurosurgery Aarhus University Hospital Nørrebrogade 44 Aarhus C 8000 Denmark.
Karen ØstergaardDepartment of Neurology Aarhus University Hospital Nørrebrogade 44 Aarhus C 8000 Denmark.ORCID 0000-0003-4829-9761

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep Brain Stimulation requires extensive postoperative testing of stimulation parameters to achieve optimal outcomes. Testing is typically not guided by neuroanatomical information on electrode contact locations. To address this, we present an automated reconstruction of electrode locations relative to the treatment target, the subthalamic nucleus, comparing different targeting methods: atlas-, manual-, or tractography-based subthalamic nucleus segmentation. We found that most electrode contacts chosen to deliver stimulation were closest or second closest to the atlas-based subthalamic nucleus target. We suggest that information on each electrode contact's location, which can be obtained using atlas-based methods, might guide clinicians during postoperative stimulation testing.

Identifiers

PMID30009208
PMCPMC6043763

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.