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Published on: September 25, 2019
Early-Stage White Matter Lesions Detected by Multispectral MRI Segmentation Predict Progressive Cognitive Decline
Hanna Jokinen1, Nicolau Gonçalves2, Ricardo Vigário3
1Clinical Neurosciences, Neurology, University of Helsinki and Helsinki University Hospital Helsinki, Finland.
Abstract:
White matter lesions (WML) are the main brain imaging surrogate of cerebral small-vessel disease. A new MRI tissue segmentation method, based on a discriminative clustering approach without explicit model-based added prior, detects partial WML volumes, likely representing very early-stage changes in normal-appearing brain tissue. This study investigated how the different stages of WML, from a "pre-visible" stage to fully developed lesions, predict future cognitive decline. MRI scans of 78 subjects, aged 65-84 years, from the Leukoaraiosis and Disability (LADIS) study were analyzed using a self-supervised multispectral segmentation algorithm to identify tissue types and partial WML volumes. Each lesion voxel was classified as having a small (33%), intermediate (66%), or high (100%) proportion of lesion tissue. The subjects were evaluated with detailed clinical and neuropsychological assessments at baseline and at three annual follow-up visits. We found that voxels with small partial WML predicted lower executive function compound scores at baseline, and steeper decline of executive scores in follow-up, independently of the demographics and the conventionally estimated hyperintensity volume on fluid-attenuated inversion recovery images. The intermediate and fully developed lesions were related to impairments in multiple cognitive domains including executive functions, processing speed, memory, and global cognitive function. In conclusion, early-stage partial WML, still too faint to be clearly detectable on conventional MRI, already predict executive dysfunction and progressive cognitive decline regardless of the conventionally evaluated WML load. These findings advance early recognition of small vessel disease and incipient vascular cognitive impairment.
Insights
Early-stage white matter lesions (WML), even when faint, predict cognitive decline. Detecting these subtle changes using advanced MRI segmentation can help identify individuals at risk for vascular cognitive impairment.
Area of Science:
- Neurology
- Radiology
- Neuroimaging
Background:
- White matter lesions (WML) are key indicators of cerebral small-vessel disease.
- Conventional MRI may miss very early WML, potentially underestimating disease burden.
- Understanding the predictive value of different WML stages is crucial for early intervention.
Purpose of the Study:
- To investigate the association between early-stage, partially detected WML and future cognitive decline.
- To determine if subtle WML predict cognitive decline independently of conventional WML measures.
- To explore the relationship between different WML severities and various cognitive domains.
Main Methods:
- Utilized a novel self-supervised multispectral segmentation algorithm on MRI scans from 78 elderly subjects (LADIS study).
- Classified WML voxels into partial volumes: small (33%), intermediate (66%), and high (100%) lesion tissue.
- Assessed cognitive function through detailed clinical and neuropsychological evaluations at baseline and annual follow-ups.
Main Results:
- Small partial WML volumes predicted lower baseline executive function scores and a steeper decline in executive function over time.
- These associations remained significant even after accounting for demographics and conventional hyperintensity volumes.
- Intermediate and fully developed WML were linked to impairments in executive function, processing speed, memory, and global cognition.
Conclusions:
- Early-stage, faint partial WML detected by advanced segmentation predict executive dysfunction and progressive cognitive decline.
- These findings suggest that subtle WML are early markers of small vessel disease and incipient vascular cognitive impairment.
- The study highlights the potential of advanced MRI techniques for earlier detection and risk stratification of cognitive decline.
