Evidence map›Paper›PMID 39523281›Full record

ReviewAdvances in experimental medicine and biology2024

Computational Neurosurgery in Deep Brain Stimulation.

Jürgen Germann, Flavia Venetucci Gouveia, Michelle E Beyn, Gavin J B Elias, Andres M Lozano

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Jürgen GermannDivision of Neurosurgery, Department of Surgery, University Health Network, University of Toronto, Toronto, ON, Canada.
Flavia Venetucci GouveiaNeuroscience and Mental Health, The Hospital for Sick Children, Toronto, ON, Canada.
Michelle E BeynDivision of Neurosurgery, Department of Surgery, University Health Network, University of Toronto, Toronto, ON, Canada.
Gavin J B EliasDivision of Neurosurgery, Department of Surgery, University Health Network, University of Toronto, Toronto, ON, Canada.
Andres M LozanoDivision of Neurosurgery, Department of Surgery, University Health Network, University of Toronto, Toronto, ON, Canada. lozano@uhnresearch.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computational methods and technologies are critical for neurosurgery in general and in deep brain stimulation (DBS) in particular. They increasingly inform every aspect of clinical DBS therapy, from presurgical planning and hardware implantation to postoperative adjustment of stimulation parameters. Computational methods also occupy a prominent position within the DBS research sphere, where they facilitate efforts to better understand DBS' underlying mechanisms and optimize and individualize its delivery. This chapter provides a high-level overview of the various computational tools and methods that have been applied to DBS. First, we discuss the invaluable contribution of computational neuroimaging (primarily magnetic resonance imaging) to DBS, targeting and the role of postoperative methods of image analysis-specifically, electrode localization, volume of activated tissue modeling, and sweet-spot mapping-in precisely localizing DBS' targets in the brain and discerning optimal treatment loci. We then address the growing field of connectomics, which leverages specific magnetic resonance imaging (MRI) sequences and post-acquisition processing algorithms to explore how DBS operates at the level of brain-wide networks. Next, the search for electrophysiological and imaging-based biomarkers of optimal DBS therapy is explored. We lastly touch on the incipient field of spatial characterization analysis and discuss the ongoing development of adaptive, closed-loop DBS systems.

Indexed as

BrainDeep Brain StimulationMagnetic Resonance ImagingComputational BiologyConnectomeHumansNeuroimagingNeurosurgical ProceduresComputational biomarkerConnectomeNeuromodulationQuantitative neuroimagingStimulation modeling

Identifiers

PMID39523281

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.