Computational quantification of brain perivascular space morphologies: Associations with vascular risk factors and white matter hyperintensities. A study in the Lothian Birth Cohort 1936.

ABSTRACT:

Background and purpose

Perivascular Spaces (PVS), also known as Virchow-Robin spaces, seen on structural brain MRI, are important fluid drainage conduits and are associated with small vessel disease (SVD). Computational quantification of visible PVS may enable efficient analyses in large datasets and increase sensitivity to detect associations with brain disorders. We assessed the associations of computationally-derived PVS parameters with vascular factors and white matter hyperintensities (WMH), a marker of SVD.

Participants

Community dwelling individuals (n = 700) from the Lothian Birth Cohort 1936 who had multimodal brain MRI at age 72.6 years (SD = 0.7).

Methods

We assessed PVS computationally in the centrum semiovale and deep corona radiata on T2-weighted images.

SUBMITTER: Ballerini L 

PROVIDER: S-EPMC6939098 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature