Spatiotemporal analysis for detection of pre-symptomatic shape changes in neurodegenerative diseases: Initial application to the GENFI cohort.
Clustering
Computational anatomy
Parallel transport
Shape analysis
Spatiotemporal geodesic regression
Thalamus
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
03 2019
03 2019
Historique:
received:
05
08
2018
revised:
15
11
2018
accepted:
30
11
2018
pubmed:
12
12
2018
medline:
22
1
2020
entrez:
12
12
2018
Statut:
ppublish
Résumé
Brain atrophy as measured from structural MR images, is one of the primary imaging biomarkers used to track neurodegenerative disease progression. In diseases such as frontotemporal dementia or Alzheimer's disease, atrophy can be observed in key brain structures years before any clinical symptoms are present. Atrophy is most commonly captured as volume change of key structures and the shape changes of these structures are typically not analysed despite being potentially more sensitive than summary volume statistics over the entire structure. In this paper we propose a spatiotemporal analysis pipeline based on Large Diffeomorphic Deformation Metric Mapping (LDDMM) to detect shape changes from volumetric MRI scans. We applied our framework to a cohort of individuals with genetic variants of frontotemporal dementia and healthy controls from the Genetic FTD Initiative (GENFI) study. Our method, take full advantage of the LDDMM framework, and relies on the creation of a population specific average spatiotemporal trajectory of a relevant brain structure of interest, the thalamus in our case. The residuals from each patient data to the average spatiotemporal trajectory are then clustered and studied to assess when presymptomatic mutation carriers differ from healthy control subjects. We found statistical differences in shape in the anterior region of the thalamus at least five years before the mutation carrier subjects develop any clinical symptoms. This region of the thalamus has been shown to be predominantly connected to the frontal lobe, consistent with the pattern of cortical atrophy seen in the disease.
Identifiants
pubmed: 30529631
pii: S1053-8119(18)32144-X
doi: 10.1016/j.neuroimage.2018.11.063
pmc: PMC6414401
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
282-290Subventions
Organisme : Medical Research Council
ID : MC_UU_00005/12
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/M009041/1
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 103838
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_U105597119
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/M024873/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/J009482/1
Pays : United Kingdom
Investigateurs
Christin Andersson
(C)
Silvana Archetti
(S)
Andrea Arighi
(A)
Luisa Benussi
(L)
Sandra Black
(S)
Maura Cosseddu
(M)
Marie Fallstrm
(M)
Carlos Ferreira
(C)
Chiara Fenoglio
(C)
Nick Fox
(N)
Morris Freedman
(M)
Giorgio Fumagalli
(G)
Stefano Gazzina
(S)
Roberta Ghidoni
(R)
Marina Grisoli
(M)
Vesna Jelic
(V)
Lize Jiskoot
(L)
Ron Keren
(R)
Gemma Lombardi
(G)
Carolina Maruta
(C)
Lieke Meeter
(L)
Rick van Minkelen
(R)
Benedetta Nacmias
(B)
Linn Ijerstedt
(L)
Alessandro Padovani
(A)
Jessica Panman
(J)
Michela Pievani
(M)
Cristina Polito
(C)
Enrico Premi
(E)
Sara Prioni
(S)
Rosa Rademakers
(R)
Veronica Redaelli
(V)
Ekaterina Rogaeva
(E)
Giacomina Rossi
(G)
Martin Rossor
(M)
Elio Scarpini
(E)
David Tang-Wai
(D)
Carmela Tartaglia
(C)
Hakan Thonberg
(H)
Pietro Tiraboschi
(P)
Ana Verdelho
(A)
Jason Warren
(J)
Informations de copyright
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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