Evidence map›Paper›PMID 41906046›Full record

ReviewBrain structure & function2026

Did you know? State-of-the-art preprocessing diffusion MRI data can improve tractography.

Kurt G Schilling, Matthew Cieslak, Maxime Descoteaux, Bennett A Landman, Franco Pestilli, Ariel Rokem, Stamatios N Sotiropoulos, Jacques-Donald Tournier, Jelle Veraart

Abstract readReview
In one paragraph

Review in Brain structure & function, 2026. 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. Article
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.

Kurt G SchillingVanderbilt University Medical Center, Nashville, TN, USA. kurt.g.schilling.1@vumc.org.
Matthew CieslakLifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Maxime DescoteauxSherbrooke Connectivity Imaging Lab (SCIL), Department of Computer Science, Universite de Sherbrooke, Sherbrooke, QC, Canada.
Bennett A LandmanDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
Franco PestilliDepartment of Psychology, Department of Neuroscience, Center for Learning and Memory, Center for Perceptual Systems, The University of Texas, Austin, TX, USA.
Ariel RokemDepartment of Psychology, University of Washington, Seattle, WA, USA.
Stamatios N SotiropoulosSir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.
Jacques-Donald TournierDepartment of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, St. Thomas' Hospital, London, UK.
Jelle VeraartCenter for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA. Jelle.Veraart@nyulangone.org.

Funding

Translational pharmacoepidemiology: neuroprotection and neurotoxicity of antihypertensives and strong anticholinergicsU19AG066567 · NIA · KAISER FOUNDATION RESEARCH INSTITUTE · PI Paul K Crane, Andrea Z. LaCroix · 2021 to 2026
$80.4M
Aging eyes and aging brains in studying alzheimer's disease: Modern ophthalmic data collection in the adult changes in thought (ACT) studyR01AG060942 · NIA · WASHINGTON UNIVERSITY · PI Cecilia Sungmin Lee · 2019 to 2026
$39.4M
BRAIN CONNECTS: Center for Mesoscale ConnectomicsUM1NS132207 · NINDS · UNIVERSITY OF MINNESOTA · PI TANER AKKIN, Damien A Fair · 2023 to 2026
$12.5M
Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRIR01EB017230 · NIBIB · VANDERBILT UNIVERSITY · PI LANDMAN, BENNETT A. · 2015 to 2024
$5.1M
CRCNS: Community-supported open-source software for computational neuroanatomyR01EB027585 · NIBIB · TRUSTEES OF INDIANA UNIVERSITY · PI Eleftherios Garyfallidis · 2018 to 2026
$2.6M
CRCNS: Integrating gray and white matter data to understand the organization of human visual cortexR01EY033628 · NEI · UNIVERSITY OF WASHINGTON · PI Noah C Benson, JONATHAN A WINAWER · 2021 to 2026
$1.7M
Microstructure and connectivity modeling from the cortex to the spinal cord in Multiple SclerosisK01EB032898 · NIBIB · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SCHILLING, KURT G · 2022 to 2025
$630k
NEI NIH HHS R01 EY033628NIA NIH HHS R01 AG060942NIA NIH HHS U19 AG066567NIBIB NIH HHS K01 EB032898NIBIB NIH HHS R01 EB017230NIBIB NIH HHS R01 EB027585NINDS NIH HHS UM1 NS132207Wellcome Trust
6 · The paper itself

Abstract

Diffusion MRI fiber tractography is sensitive to noise and artifacts in diffusion-weighted images, and these challenges can propagate into fiber-orientation estimation and the tractography process. In this “Did You Know” communication, we synthesize evidence that state-of-the-art preprocessing improves tractography anatomical fidelity and test-retest reproducibility compared to minimally processed data. We summarize best-practice preprocessing – including denoising, motion and eddy current correction, EPI distortion correction, and Gibbs ringing removal – along with additional and emerging steps, and highlight integrated, publicly available pipelines that implement these methods in standardized, containerized workflows. We also outline practical acquisition and data-handling considerations that maximize the benefits of modern processing, providing a foundation for reliable tractography-based studies of the brain.

Indexed as

BrainDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingImage Processing, Computer-AssistedArtifactsHumansReproducibility of ResultsArtifactsDenoisingDistortion correctionFiber orientation distributionPreprocessingTractography

Identifiers

PMID41906046
PMCPMC13033464

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.