Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts

Abstract

Introduction: The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns.

Methods: Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented.

Results: WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected.

Discussion: Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.

Keywords: Brain MRI; Distribution frequencies; Lesion location; White matter hyperintensities.

Fig. 1

WMH probability map at the voxel level for the whole cohort. This figure shows the spatial probability distribution of WMH overlaid onto the MNI-152 template. Colors indicate the percentage of participants who have a WMH in a given voxel. L = left, R = right.

Fig. 2

WMH probability map at the voxel level stratified by WMH tertile. This figure shows the spatial probability distribution of WMH overlaid onto the MNI-152 template per WMH tertile. Colors indicate the percentage of participants who have a WMH in a voxel in that tertile. L = left, R = right.

Fig. 3

Region-of-interest based WMH probability map. This figure shows the region-of-interest based WMH spatial probability distribution for the whole cohort and per normalized WMH tertile. Regions-of-interest are defined according to twenty major white matter tracts defined in the JHU atlas (probability threshold of 10 %) (Hua et al., 2008). Colors indicate the percentage of participants who have a WMH (partially) overlapping with that region-of-interest. L = left, R = right.

Fig. 4

Results of Rule based Score 2. Clinical characteristics and WMH distribution patterns of the five participants with the highest Score 2 are presented, after exclusion of segmentations errors. Score 2 assigns a high score to lesions (of at least ten voxels in size) at locations where less than five participants had a lesion and this score was calculated by computing the sum of 1 – probability of a lesion in a certain voxel for these locations. The FLAIR sequence and WMH lesion map in native space are shown. L = left, R = right.

Fig. 5

Results of local outlier factor. Clinical characteristics and WMH distribution patterns of the five participants with the lowest local outlier factor (LOF) score are presented, after exclusion of segmentations errors. LOF assigns a low (negative) score to participants whose total 3D WMH distribution deviates substantially with respect to all other participants in the dataset. The FLAIR sequence and WMH lesion map in native space are shown. L = left, R = right.