Atlas-based assessment of hypomyelination: Quantitative MRI in Pelizaeus-Merzbacher disease

Abstract

Pelizaeus-Merzbacher disease (PMD) is a rare childhood hypomyelinating leukodystrophy. Quantification of the pronounced myelin deficit and delineation of subtle myelination processes are of high clinical interest. Quantitative magnetic resonance imaging (qMRI) techniques can provide in vivo insights into myelination status, its spatial distribution, and dynamics during brain maturation. They may serve as potential biomarkers to assess the efficacy of myelin-modulating therapies. However, registration techniques for image quantification and statistical comparison of affected pediatric brains, especially those of low or deviant image tissue contrast, with healthy controls are not yet established. This study aimed first to develop and compare postprocessing pipelines for atlas-based quantification of qMRI data in pediatric patients with PMD and evaluate their registration accuracy. Second, to apply an optimized pipeline to investigate spatial myelin deficiency using myelin water imaging (MWI) data from patients with PMD and healthy controls. This retrospective single-center study included five patients with PMD (mean age, 6 years ± 3.8) who underwent conventional brain MRI and diffusion tensor imaging (DTI), with MWI data available for a subset of patients. Three methods of registering PMD images to a pediatric template were investigated. These were based on (a) T1-weighted (T1w) images, (b) fractional anisotropy (FA) maps, and (c) a combination of T1w, T2-weighted, and FA images in a multimodal approach. Registration accuracy was determined by visual inspection and calculated using the structural similarity index method (SSIM). SSIM values for the registration approaches were compared using a t test. Myelin water fraction (MWF) was quantified from MWI data as an assessment of relative myelination. Mean MWF was obtained from two PMDs (mean age, 3.1 years ± 0.3) within four major white matter (WM) pathways of a pediatric atlas and compared to seven healthy controls (mean age, 3 years ± 0.2) using a Mann-Whitney U test. Our results show that visual registration accuracy estimation and computed SSIM were highest for FA-based registration, followed by multimodal, and T1w-based registration (SSIM_FA = 0.67 ± 0.04 vs. SSIM_multimodal = 0.60 ± 0.03 vs. SSIM_T1 = 0.40 ± 0.14). Mean MWF of patients with PMD within the WM pathways was significantly lower than in healthy controls MWF_PMD = 0.0267 ± 0.021 vs. MWF_controls = 0.1299 ± 0.039. Specifically, MWF was measurable in brain structures known to be myelinated at birth (brainstem) or postnatally (projection fibers) but was scarcely detectable in other brain regions (commissural and association fibers). Taken together, our results indicate that registration accuracy was highest with an FA-based registration pipeline, providing an alternative to conventional T1w-based registration approaches in the case of hypomyelinating leukodystrophies missing normative intrinsic tissue contrasts. The applied atlas-based analysis of MWF data revealed that the extent of spatial myelin deficiency in patients with PMD was most pronounced in commissural and association and to a lesser degree in brainstem and projection pathways.

Keywords: Pelizaeus‐Merzbacher disease; hypomyelinating leukodystrophy; magnetic resonance imaging; medical image registration; neuroimaging; white matter disorder.

FIGURE 1

Schematic of the developed registration workflows; input images: mov: moving image; ref: reference image.

FIGURE 2

Cerebral axial T1w, T2w, and FA images of the registration dataset aligned to JHU18m template. Upper row: JHU18m template from a 1.5‐year‐old healthy participant. Rows 2–6: PMD patients of different ages, reflecting the inhomogeneous range of T1w and T2w tissue contrast, whereas FA‐image contrast was more similar in these hypomyelinated states with widely varying degrees of maturation.

FIGURE 3

Visual scoring of registration accuracy for the three different image registration methods.

FIGURE 4

Transformed FA image of PMD5 in the JHU18m template space and zoomed section with superimposed atlas segmentation contours. The color‐coded SSIM map demonstrates the differing image similarities between the transformed FA images of the PMD patient to JHU18m for the three analyzed registration approaches. Major misaligned regions are indicated with black arrows.

FIGURE 5

Left: Distribution of mean MWF within the ROIs grouped by the WM tracts for a 3‐year‐old control group and two patients with PMD at 2.9 and 3.3 years of age. Right: Corresponding MWF maps for the average image of the nine male controls and PMD 2 with superimposed WM tracts for comparison.