Evidence map›Paper›PMID 41326803›Full record

ArticleActa neurochirurgica2025

How accurate is probabilistic tractography when used to predict the "sweet spot" in deep brain stimulation? Mind the gap!

Daniel Deuter, Tobias Mederer, Katharina Rosengarth, Judith Anthofer, Anes Dada, Michael Knott, Tina Wendl, Nils-Ole Schmidt, Jürgen Schlaier

Abstract read
In one paragraph

Article in Acta neurochirurgica, 2025. 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

9 authors.

Daniel DeuterKlinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany. daniel.deuter@klinik.uni-regensburg.de.
Tobias MedererKlinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Katharina RosengarthKlinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Judith AnthoferKlinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Anes DadaKlinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Michael KnottInstitut für Röntgendiagnostik, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Tina WendlInstitut für Röntgendiagnostik, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Nils-Ole SchmidtKlinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Jürgen SchlaierKlinik und Poliklinik für Neurochirurgie, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTractography has been used in various studies with respect to the improvement of patient-specific DBS targeting. Nevertheless, methodological influences of the chosen parameters and associated errors are often neglected. The aim of this study was to estimate concrete errors associated with specific image processing steps when using measurements of distances to specific subcortical fiber tracts to predict optimal stimulation sites for DBS targeting.

methodProbabilistic tractography of the crossing and non-decussating part of the dentato-rubro-thalamic-tract (c-/ nd-DRTT) was performed using FSL 6.0.3 in 40 PD- and ET-patients having received bilateral DBS surgery. DBS-electrodes were reconstructed using LeadDBS. The influence of (1) the choice of threshold for binarization of fiber tracts, (2) manual measurements compared to measurements using automized distance maps and (3) normalization into the MNI standard space on measured distances were investigated.

resultsDifferent thresholds for binarization resulted in non-linear and unpredictable variations of measured distances up to 1.72 ± 1.49 mm (mean value ± standard deviation). Manual measurements on the axial slice of the electrode contact showed a mean error of 0.91 ± 1.36 mm (maximum 14.9 mm) compared to automated measurements. Regarding normalization, a mean error of 0.82 ± 0.50 mm (maximum 2.34 mm) was found compared to measurements in native space.

conclusionMeasured maximum errors reach up to several millimeters, which might have significant impact on clinical targeting in DBS. Researchers should be aware of these errors and define individual standards for specific studies.

Indexed as

Deep Brain StimulationDiffusion Tensor ImagingEssential TremorParkinson DiseaseAgedFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedDeep Brain StimulationDiffusion Tensor ImagingFiber tractsProbabilistic tractography

Identifiers

PMID41326803
PMCPMC12669367

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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.