Age-specific optimization of T1-weighted brain MRI throughout infancy.

Abstract:

:The infant brain undergoes drastic morphological and functional development during the first year of life. Three-dimensional T1-weighted Magnetic Resonance Imaging (3D T1w-MRI) is a major tool to characterize the brain anatomy, which however, manifests inherently low and rapidly changing contrast between white matter (WM) and gray matter (GM) in the infant brains (0-12 month-old). Despite the prior efforts made to maximize tissue contrast in the neonatal brains (≤1 months), optimization of imaging methods in the rest of the infancy (1-12 months) is not fully addressed, while brains in the latter period exhibit even more challenging contrast. Here, we performed a systematic investigation to improve the contrast between cortical GM and subcortical WM throughout the infancy. We first performed simultaneous T1 and proton density mapping in a normally developing infant cohort at 3T (n = 57). Based on the evolution of T1 relaxation times, we defined three age groups and simulated the relative tissue contrast between WM and GM in each group. Age-specific imaging strategies were proposed according to the Bloch simulation: inversion time (TI) around 800 ms for the 0-3 month-old group, dual TI at 500 ms and 700 ms for the 3-7 month-old group, and TI around 700 ms for 7-12 month-old group, using a centrically encoded 3D-MPRAGE sequence at 3T. Experimental results with varying TIs in each group confirmed improved contrast at the proposed optimal TIs, even in 3-7 month-old infants who had nearly isointense contrast. We further demonstrated the advantage of improved relative contrast in segmenting the neonatal brains using a multi-atlas segmentation method. The proposed age-specific optimization strategies can be easily adapted to routine clinical examinations, and the improved image contrast would facilitate quantitative analysis of the infant brain development.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Zhang H,Lai C,Liu R,Liu T,Niu W,Oishi K,Zhang Y,Wu D

doi

10.1016/j.neuroimage.2019.05.075

subject

Has Abstract

pub_date

2019-10-01 00:00:00

pages

387-395

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(19)30471-9

journal_volume

199

pub_type

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