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Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI

NeuroImage (Orlando, Fla.), 2017-05, Vol.152, p.411-424 [Peer Reviewed Journal]

2017 Elsevier Inc. ;Copyright © 2017 Elsevier Inc. All rights reserved. ;Copyright Elsevier Limited May 15, 2017 ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2017.03.012 ;PMID: 28284800

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Title:
Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI
Author: Rekik, Islem ; Li, Gang ; Yap, Pew-Thian ; Chen, Geng ; Lin, Weili ; Shen, Dinggang
Subjects: Attention deficit hyperactivity disorder ; Babies ; Bifurcations ; Brain ; Brain development ; Brain Mapping - methods ; Cerebral Cortex - anatomy & histology ; Cerebral Cortex - growth & development ; Cortex ; Cortex (temporal) ; Diffusion Magnetic Resonance Imaging ; Diffusion Tensor Imaging ; Evolution ; Fibers ; Growth models ; Heterogeneous-atlas estimation ; Humans ; Image Processing, Computer-Assisted ; Infant ; Innovations ; Longitudinal Studies ; Low-rank tensor completion ; Magnetic resonance imaging ; Multidirectional varifold ; Multishape prediction ; Neonates ; Neural networks ; Prediction models ; Registration ; Substantia alba ; Trajectories ; White Matter - anatomy & histology ; White Matter - growth & development
Is Part Of: NeuroImage (Orlando, Fla.), 2017-05, Vol.152, p.411-424
Description: The human brain can be modeled as multiple interrelated shapes (or a multishape), each for characterizing one aspect of the brain, such as the cortex and white matter pathways. Predicting the developing multishape is a very challenging task due to the contrasting nature of the developmental trajectories of the constituent shapes: smooth for the cortical surface and non-smooth for white matter tracts due to changes such as bifurcation. We recently addressed this problem and proposed an approach for predicting the multishape developmental spatiotemporal trajectories of infant brains based only on neonatal MRI data using a set of geometric, dynamic, and fiber-to-surface connectivity features. In this paper, we propose two key innovations to further improve the prediction of multishape evolution. First, for a more accurate cortical surface prediction, instead of simply relying on one neonatal atlas to guide the prediction of the multishape, we propose to use multiple neonatal atlases to build a spatially heterogeneous atlas using the multidirectional varifold representation. This individualizes the atlas by locally maximizing its similarity to the testing baseline cortical shape for each cortical region, thereby better representing the baseline testing cortical surface, which founds the multishape prediction process. Second, for temporally consistent fiber prediction, we propose to reliably estimate spatiotemporal connectivity features using low-rank tensor completion, thereby capturing the variability and richness of the temporal development of fibers. Experimental results confirm that the proposed variants significantly improve the prediction performance of our original multishape prediction framework for both cortical surfaces and fiber tracts shape at 3, 6, and 9 months of age. Our pioneering model will pave the way for learning how to predict the evolution of anatomical shapes with abnormal changes. Ultimately, devising accurate shape evolution prediction models that can help quantify and predict the severity of a brain disorder as it progresses will be of great aid in individualized treatment planning. •Neonatal multishape (cortical surface and fiber tracts) development prediction.•Spatially-heterogeneous atlas estimation using multidirectional varifolds.•Temporally-consistent prediction of fiber development using tensor completion.
Publisher: United States: Elsevier Inc
Language: English
Identifier: ISSN: 1053-8119
EISSN: 1095-9572
DOI: 10.1016/j.neuroimage.2017.03.012
PMID: 28284800
Source: ProQuest One Psychology
MEDLINE
Alma/SFX Local Collection
ProQuest Central

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Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI

2017 Elsevier Inc. ;Copyright © 2017 Elsevier Inc. All rights reserved. ;Copyright Elsevier Limited May 15, 2017 ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2017.03.012 ;PMID: 28284800

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