Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project

被引：119

作者：

Bastiani, Matteo ^{[1
]}

Andersson, Jesper L. R. ^{[1
]}

Cordero-Grande, Lucilio ^{[2
]}

Murgasova, Maria ^{[2
]}

Hutter, Jana ^{[2
]}

Price, Anthony N. ^{[2
]}

Makropoulos, Antonios ^{[3
]}

Fitzgibbon, Sean P. ^{[1
]}

Hughes, Emer ^{[2
]}

Rueckert, Daniel ^{[3
]}

Victor, Suresh ^{[2
]}

Rutherford, Mary ^{[2
]}

Edwards, A. David ^{[2
]}

Smith, Stephen M. ^{[1
]}

Tournier, Jacques-Donald ^{[2
]}

Hajnal, Joseph V. ^{[2
]}

Jbabdi, Saad ^{[1
]}

Sotiropoulos, Stamatios N. ^{[1
,4
]}

机构：

[1] Univ Oxford, Wellcome Ctr Integrat Neuroimaging, Oxford Ctr Funct Magnet Resonance Imaging Brain F, Oxford, England

[2] Kings Coll London, Ctr Dev Brain, London, England

[3] Imperial Coll London, Dept Comp, London, England

[4] Univ Nottingham, Sir Peter Mansfield Imaging Ctr, Sch Med, Nottingham, England

来源：

NEUROIMAGE | 2019年 / 185卷

基金：

英国惠康基金; 英国工程与自然科学研究理事会; 欧洲研究理事会; 英国医学研究理事会;

关键词：

Diffusion MRI; Tractography; Quality control; Brain; Connectome; Newborn; ASSESSING WHITE-MATTER; ECHO-PLANAR IMAGES; MOTION CORRECTION; HUMAN FETAL; ORIENTATION DISPERSION; DISTORTION CORRECTION; TENSOR MRI; BRAIN; TRACTOGRAPHY; CONNECTIVITY;

D O I：

10.1016/j.neuroimage.2018.05.064

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38-44 weeks post-menstrual age.

引用

页码：750 / 763

页数：14

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