Registration-free analysis of diffusion MRI tractography data across subjects through the human lifespan.
Diffusion MRI
Hierarchical clustering
Normalized cuts
Tractography
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
01 07 2020
01 07 2020
Historique:
received:
12
10
2019
revised:
21
01
2020
accepted:
02
03
2020
pubmed:
11
3
2020
medline:
16
2
2021
entrez:
11
3
2020
Statut:
ppublish
Résumé
Diffusion MRI tractography produces massive sets of streamlines that need to be clustered into anatomically meaningful white-matter bundles. Conventional clustering techniques group streamlines based on their proximity in Euclidean space. We have developed AnatomiCuts, an unsupervised method for clustering tractography streamlines based on their neighboring anatomical structures, rather than their coordinates in Euclidean space. In this work, we show that the anatomical similarity metric used in AnatomiCuts can be extended to find corresponding clusters across subjects and across hemispheres, without inter-subject or inter-hemispheric registration. Our proposed approach enables group-wise tract cluster analysis, as well as studies of hemispheric asymmetry. We evaluate our approach on data from the pilot MGH-Harvard-USC Lifespan Human Connectome project, showing improved correspondence in tract clusters across 184 subjects aged 8-90. Our method shows up to 38% improvement in the overlap of corresponding clusters when comparing subjects with large age differences. The techniques presented here do not require registration to a template and can thus be applied to populations with large inter-subject variability, e.g., due to brain development, aging, or neurological disorders.
Identifiants
pubmed: 32151759
pii: S1053-8119(20)30190-7
doi: 10.1016/j.neuroimage.2020.116703
pmc: PMC8482444
mid: NIHMS1741543
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
116703Subventions
Organisme : NIMH NIH HHS
ID : U01 MH093765
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB021265
Pays : United States
Organisme : NCRR NIH HHS
ID : S10 RR019307
Pays : United States
Organisme : NIMH NIH HHS
ID : R56 MH121426
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH108168
Pays : United States
Organisme : NIDA NIH HHS
ID : T90 DA022759
Pays : United States
Organisme : NIDA NIH HHS
ID : R90 DA023427
Pays : United States
Organisme : NCRR NIH HHS
ID : S10 RR023043
Pays : United States
Organisme : NCRR NIH HHS
ID : S10 RR023401
Pays : United States
Informations de copyright
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.
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