Evidence map›Paper›PMID 34979249›Full record

ReviewNeuroImage2022

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review.

Fan Zhang, Alessandro Daducci, Yong He, Simona Schiavi, Caio Seguin, Robert E Smith, Chun-Hung Yeh, Tengda Zhao, Lauren J O'Donnell

Abstract readReview
In one paragraph

Review in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 152 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
152citing papers in PubMed, 2 pooled it
–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

152 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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92 more citing papers are in PubMed but not listed here.

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.

Fan ZhangBrigham and Women's Hospital, Harvard Medical School, Boston, USA. Electronic address: fzhang@bwh.harvard.edu.
Alessandro DaducciDepartment of Computer Science, University of Verona, Verona, Italy.
Yong HeState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China.
Simona SchiaviDepartment of Computer Science, University of Verona, Verona, Italy.
Caio SeguinMelbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia.
Robert E SmithThe Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia.
Chun-Hung YehInstitute for Radiological Research, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
Tengda ZhaoState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Lauren J O'DonnellBrigham and Women's Hospital, Harvard Medical School, Boston, USA. Electronic address: odonnell@bwh.harvard.edu.

Funding

Training and DisseminationP41EB015902 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI WESTIN, CARL-FREDRIK · 2012 to 2022
$20.9M
Novel DT-MRI Analyses of White Matter in SchizophreniaR01MH074794 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI WESTIN, CARL-FREDRIK · 2007 to 2021
$9.6M
Mapping the superficial white matter connectome of the human brain using ultra high resolution multi-contrast diffusion MRIR01MH125860 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI MAKRIS, NIKOLAOS, O'DONNELL, LAUREN JEAN · 2021 to 2025
$4.1M
Harmonizing multi-site diffusion MRI acquisitions for neuroscientific analysis across ages and brain disordersR01MH119222 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI O'DONNELL, LAUREN JEAN, RATHI, YOGESH · 2019 to 2023
$4.0M
NIBIB NIH HHS P41 EB015902NIMH NIH HHS R01 MH074794NIMH NIH HHS R01 MH119222NIMH NIH HHS R01 MH125860
6 · The paper itself

Abstract

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

Indexed as

BrainDiffusion Tensor ImagingHumansNerve Net

Identifiers

PMID34979249
PMCPMC9257891

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.