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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

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Distinct spatiotemporal patterns of white matter hyperintensity progression.

Jinyong Chung^1,2, Gilsoon Park³, Wi-Sun Ryu⁴

¹Medical Science Research Center, Dongguk University, Goyang, South Korea.

Nature Communications

|October 24, 2025

Summary

This summary is machine-generated.

Researchers identified three white matter hyperintensity progression subtypes in stroke patients. These subtypes, linked to different risk factors and stroke types, improve outcome prediction and may aid in future stroke risk assessment.

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Area of Science:

Neuroimaging
Neurology
Cardiovascular Disease

Background:

White matter hyperintensity (WMH) is a crucial neuroimaging biomarker reflecting brain health and predicting stroke outcomes.
Understanding WMH progression patterns is essential for refining stroke risk stratification and management strategies.

Purpose of the Study:

To identify and characterize distinct subtypes of white matter hyperintensity progression using advanced modeling.
To investigate the associations between WMH subtypes, demographic factors, vascular risks, and stroke outcomes.
To evaluate the utility of WMH subtyping for improving post-stroke outcome prediction and potentially for stroke prediction.

Main Methods:

Utilized a large, multicenter MRI dataset comprising 9179 stroke patients and 36,210 controls from the UK Biobank.
Employed Subtype and Stage Inference (SuStaIn) modeling to classify WMH progression into distinct subtypes.
Performed longitudinal validation to confirm the stability and reliability of the identified WMH subtypes.

Main Results:

Identified three distinct WMH progression subtypes: fronto-parietal, radial, and temporo-occipital.
Fronto-parietal subtype associated with delayed onset, hypertension, small vessel stroke, and higher ischemic stroke recurrence.
Temporo-occipital subtype linked to atrial fibrillation, coronary heart disease, cardioembolism, early neurological deterioration, and worse outcomes.

Conclusions:

The developed subtyping-staging model effectively captures WMH progression, associated demographics, and vascular risks.
WMH subtyping significantly enhances the prediction of post-stroke outcomes, including recurrence and early deterioration.
This novel subtyping approach holds promise for improving both post-stroke outcome prediction and future stroke risk assessment.