Evidence map›Paper›PMID 29920375›Full record

ArticleNeuroImage2018

An anatomically curated fiber clustering white matter atlas for consistent white matter tract parcellation across the lifespan.

Fan Zhang, Ye Wu, Isaiah Norton, Laura Rigolo, Yogesh Rathi, Nikos Makris, Lauren J O'Donnell

Abstract read
In one paragraph

Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
122citing papers in PubMed, 1 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

122 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. White matter predicts tDCS antidepressant effects in a sham-controlled clinical trial study.European archives of psychiatry and clinical neuroscience · 2023
    Trial
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62 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

7 authors.

Fan ZhangHarvard Medical School, Boston, USA. Electronic address: fzhang@bwh.harvard.edu.
Ye WuHarvard Medical School, Boston, USA.
Isaiah NortonHarvard Medical School, Boston, USA.
Laura RigoloHarvard Medical School, Boston, USA.
Yogesh RathiHarvard Medical School, Boston, USA.
Nikos MakrisHarvard Medical School, Boston, USA.
Lauren J O'DonnellHarvard Medical School, Boston, USA.

Funding

Training and DisseminationP41EB015902 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI PUJOL, SONIA · 2012 to 2022
$20.9M
Image Guided Therapy Center - Ultrasound-based sensor system for the monitoring of COVID-19 patientsP41EB015898 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI TEMPANY, CLARE M · 2012 to 2021
$18.9M
Novel DT-MRI Analyses of White Matter in SchizophreniaR01MH074794 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI WESTIN, CARL-FREDRIK · 2007 to 2021
$9.6M
Neural substrates of diffusion imaging in cognitively aging rhesus monkeysR01AG042512 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI KUBICKI, MAREK, MAKRIS, NIKOLAOS · 2013 to 2023
$6.5M
Mechanisms of myelin damage and cognitive impairment in the aging monkey: Gene Expression, Neurophysiology, Inflammation and Effects of Calorie RestrictionRF1AG043640 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI ROSENE, DOUGLAS L · 2019 to 2019
$3.7M
Histopathology, Neuroimaging and Mechanism of Myelin Damage in Aging Monkey BrainR01AG043640 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI ROSENE, DOUGLAS L · 2013 to 2017
$3.0M
Taking advanced diffusion imaging to the clinic for pediatric patients with ADHDR01MH097979 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI RATHI, YOGESH · 2012 to 2017
$2.4M
Open source diffusion MRI technology for brain cancer researchU01CA199459 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI O'DONNELL, LAUREN JEAN · 2015 to 2017
$1.1M
Novel diffusion MRI analysis for detection of mild traumatic brain injuryR03NS088301 · NINDS · BRIGHAM AND WOMEN'S HOSPITAL · PI O'DONNELL, LAUREN JEAN · 2015 to 2016
$177k
NCI NIH HHS U01 CA199459NIA NIH HHS R01 AG042512NIA NIH HHS R01 AG043640NIA NIH HHS RF1 AG043640NIBIB NIH HHS P41 EB015898NIBIB NIH HHS P41 EB015902NIMH NIH HHS R01 MH074794NIMH NIH HHS R01 MH097979NINDS NIH HHS R03 NS088301
6 · The paper itself

Abstract

This work presents an anatomically curated white matter atlas to enable consistent white matter tract parcellation across different populations. Leveraging a well-established computational pipeline for fiber clustering, we create a tract-based white matter atlas including information from 100 subjects. A novel anatomical annotation method is proposed that leverages population-based brain anatomical information and expert neuroanatomical knowledge to annotate and categorize the fiber clusters. A total of 256 white matter structures are annotated in the proposed atlas, which provides one of the most comprehensive tract-based white matter atlases covering the entire brain to date. These structures are composed of 58 deep white matter tracts including major long range association and projection tracts, commissural tracts, and tracts related to the brainstem and cerebellar connections, plus 198 short and medium range superficial fiber clusters organized into 16 categories according to the brain lobes they connect. Potential false positive connections are annotated in the atlas to enable their exclusion from analysis or visualization. In addition, the proposed atlas allows for a whole brain white matter parcellation into 800 fiber clusters to enable whole brain connectivity analyses. The atlas and related computational tools are open-source and publicly available. We evaluate the proposed atlas using a testing dataset of 584 diffusion MRI scans from multiple independently acquired populations, across genders, the lifespan (1 day-82 years), and different health conditions (healthy control, neuropsychiatric disorders, and brain tumor patients). Experimental results show successful white matter parcellation across subjects from different populations acquired on multiple scanners, irrespective of age, gender or disease indications. Over 99% of the fiber tracts annotated in the atlas were detected in all subjects on average. One advantage in terms of robustness is that the tract-based pipeline does not require any cortical or subcortical segmentations, which can have limited success in young children and patients with brain tumors or other structural lesions. We believe this is the first demonstration of consistent automated white matter tract parcellation across the full lifespan from birth to advanced age.

Indexed as

Atlases as TopicAdolescentAdultAgedAged, 80 and overAlgorithmsBrainChildChild, PreschoolCluster AnalysisDiffusion Tensor ImagingFemaleHumansImage Processing, Computer-AssistedInfantInfant, Newborn

Identifiers

PMID29920375
PMCPMC6080311

What OpenQuestion holds

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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.