Using Perfusion Contrast for Spatial Normalization of ASL MRI Images in a Pediatric Craniosynostosis Population.

Catherine A De Planque,Henk J M M Mutsaerts,Jan Petr,Vera C Keil,Marjolein H G Dremmen,Irene M J Mathijssen,Nicole S Erler

doi:10.3389/fnins.2021.698007

Abstract

Spatial normalization is an important step for group image processing and evaluation of mean brain perfusion in anatomical regions using arterial spin labeling (ASL) MRI and is typically performed via high-resolution structural brain scans. However, structural segmentation and/or spatial normalization to standard space is complicated when gray-white matter contrast in structural images is low due to ongoing myelination in newborns and infants. This problem is of particularly clinical relevance for imaging infants with inborn or acquired disorders that impair normal brain development. We investigated whether the ASL MRI perfusion contrast is a viable alternative for spatial normalization, using a pseudo-continuous ASL acquired using a 1.5 T MRI unit (GE Healthcare). Four approaches have been compared: (1) using the structural image contrast, or perfusion contrast with (2) rigid, (3) affine, and (4) nonlinear transformations – in 16 healthy controls [median age 0.83 years, inter-quartile range (IQR) ± 0.56] and 36 trigonocephaly patients (median age 0.50 years, IQR ± 0.30) – a non-syndromic type of craniosynostosis. Performance was compared quantitatively using the real-valued Tanimoto coefficient (TC), visually by three blinded readers, and eventually by the impact on regional cerebral blood flow (CBF) values. For both patients and controls, nonlinear registration using perfusion contrast showed the highest TC, at 17.51 (CI 6.66–49.38) times more likely to have a higher rating and 17.45–18.88 ml/100 g/min higher CBF compared with the standard normalization. Using perfusion-based contrast improved spatial normalization compared with the use of structural images, significantly affected the regional CBF, and may open up new possibilities for future large pediatric ASL brain studies.

Highlights

Spatial normalization is an important step for brain image processing; it enables group analyses but is required for automatic segmentation of tissue type and brain regions
We have shown that direct normalization of arterial spin labeling (ASL) images to MNI space using ASL cerebral blood flow (CBF) as image contrast outperforms spatial normalization based on T1w segmentation in MRI brain studies of both patients and controls who are less than 2 years of age
While better results in Tanimoto coefficient (TC) of the regASLdct were shown for the control group, the difference between regT1 and regASLdct was even higher in patients in both qualitative analysis and CBF analysis

Summary

Introduction

Spatial normalization is an important step for brain image processing; it enables group analyses but is required for automatic segmentation of tissue type and brain regions. Mutsaerts et al (2018) used cerebral blood flow (CBF) and pseudo-CBF, created from a gray matter (GM) map from segmented T1w image to register individual ASL and T1w volumes instead of using the morphological images for the registration, for example, the ASL control images or M0 scans registered to T1w images in elderly subjects This approach was especially important in cases where the image contrast difference between GM and white matter (WM) was low in ASL control images or in M0 scans, due to, for example, use of strong background suppression or short TR, respectively. This approach can be potentially extended to direct spatial normalization of ASL to standard space in the pediatric population as ASL studies of the brain show sufficient CBF contrast between GM and WM already in early age despite the potential lack of GM/WM contrast in T1w images (Yoshida et al, 2013)

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