Enlarged perivascular space burden associations with arterial stiffness and cognition

Small vessel disease (SVD) exists in almost 75% of autopsy-confirmed Alzheimer's disease cases (Kapasi et al., 2017) and has clinical implications. However, enlarged perivascular spaces (ePVS), a purported marker of SVD, have not been widely studied due to difficulties in accurate quantification and the common notion that ePVS are a by-product of neurodegeneration (Barkhof, 2004).

In a healthy state, perivascular spaces (PVS) are fluid-filled spaces that encapsulate cerebral blood vessels and aid in fluid transport in the brain (Iliff et al., 2012). PVS allow cerebrospinal fluid (CSF) to flow into the brain while simultaneously allowing clearance of interstitial fluid and metabolic waste from the brain (Iliff et al., 2012; Weller et al., 2009). When PVS are visible on MRI, they are considered ePVS. One potential mechanism underlying ePVS formation is hypertensive arteriopathy (Charidimou et al., 2017), a condition that affects small perforating vessels of the basal ganglia characterized by vessel wall disorganization, arteriosclerosis, and cell death (Pantoni, 2010). Systemic vascular disease may also play a role in ePVS formation. While hypertension has been related to ePVS in the basal ganglia (Yang et al., 2017), studies addressing systemic drivers are sparse. Arterial stiffening is a precursor to hypertension, so a reliable arterial stiffness marker may provide a subtle and earlier marker of vascular damage (Dernellis and Panaretou, 2005; Mitchell, 2014). More specifically, amplified pressure waves that accompany arterial stiffening may damage vascular walls in downstream small vessels, particularly in high-flow organs like the brain, which could concurrently drive enlargement in surrounding PVS. The first aim of this study is to test the hypothesis that increased arterial stiffness as measured by aortic pulse wave velocity (PWV) may be associated with a worse ePVS burden. ePVS have often been considered clinically benign, a conclusion that is supported by the literature (Hilal et al., 2018). For example, a meta-analysis of 3575 participants across 5 studies found no associations between ePVS and cognition (Hilal et al., 2018). However, a growing body of work, including from our own group (Passiak et al., 2019), suggests ePVS may be clinically relevant. Specifically, ePVS have been associated with worse executive function (Passiak et al., 2019), information processing (Passiak et al., 2019), and visuospatial abilities cross-sectionally (Maclullich et al., 2004). Discrepant findings may be due to methodological variability. To better quantify ePVS and understand their clinical relevance, standardized, fully-quantitative methods are needed. Most other studies (Hilal et al., 2018; Maclullich et al., 2004), including our prior work (Passiak et al., 2019), rely on ordinal scores of ePVS burden based on a few (or less) image slices. To overcome past methodological limitations, the current study leverages machine learning to calculate ePVS volume and count for the entire basal ganglia. The ePVS quantification method implemented here is a novel deep-learning algorithm that outputs continuous volume and count measures for the entire basal ganglia with minimal edits required.

We focus on the basal ganglia for 2 reasons. First, ePVS are more prominent in this region, and second, the basal ganglia plays a crucial role in facilitating executive function and information processing, 2 of our cognitive outcomes of interest. We hypothesize that greater ePVS volume and count in the basal ganglia will be associated with worse cognition cross-sectionally and over time. Specifically, we expect the domains of information processing and executive function to be most affected as these functions rely on frontal subcortical circuits which run through the basal ganglia (Bonelli and Cummings, 2007; Cummings, 1993). To our knowledge, this is the first study to analyze associations between continuous measures of ePVS and longitudinal cognition. We additionally hypothesize that associations will be stronger among participants with mild cognitive impairment (MCI). MCI participants are more susceptible than cognitively unimpaired individuals to cognitive decline. The additional burden of SVD pathology, such as ePVS, likely accelerates this decline leading to stronger cognitive associations among MCI participants, both cross-sectionally and longitudinally.

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