Quantitative Analysis of Automatically Segmented Perivascular Space in Subcortical White Matter of Parkinson’s Disease: Its Clinical Relevance

Objective: To examine the relationship between automatically quantified perivascular space (PVS) extent located in the subcortical white matter (WM), baseline motor deficits and cognitive function, as well as longitudinal motor and cognitive outcomes in patients with Parkinson's disease (PD). Methods: This retrospective cohort study included 270 consecutive patients with newly diagnosed PD. Subcortical WM PVS was automatically segmented using high-resolution T2-weighted images, and automated PVS (aPVS) volume and count were calculated. Multivariate linear regression analyses evaluated the association between subcortical WM aPVS and baseline Unified PD Rating Scale Part III, Mini-Mental State Examination, and Montreal Cognitive Assessment scores. Cox regression models assessed the prognostic value of baseline subcortical WM aPVS for the risk of developing freezing of gait (FOG) and dementia. Results: Greater subcortical WM aPVS volume, particularly in the frontal and parietal regions, correlated with milder parkinsonian motor deficits and better global cognitive function at baseline. Higher subcortical WM aPVS volume, especially in the frontal region, was linked to a lower risk of FOG (hazard ratio (HR), 0.5; 95% confidence interval (CI), 0.2-0.9; p=0.028). Additionally, greater subcortical WM aPVS volume, especially in the occipital region, was associated with a reduced risk of dementia conversion (HR, 0.4; 95% CI, 0.1-1.0; p=0.041) in Cox regression models. Higher subcortical WM aPVS count was linked to better baseline motor symptoms, cognitive function, and lower risk of FOG. Conclusions: These findings indicate that larger subcortical WM aPVS volume or higher aPVS count can be an indicator of favorable clinical outcomes in PD.