Development and initial evaluation of a semi-automatic approach to assess perivascular spaces on conventional magnetic resonance images

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Abstract

Purpose Perivascular spaces (PVS) are associated with ageing, cerebral small vessel disease, inflammation and increased blood brain barrier permeability. Most studies to date use visual rating scales to assess PVS, but these are prone to observer variation. Methods We developed a semi-automatic computational method that extracts PVS on bilateral ovoid basal ganglia (BG) regions on intensity-normalised T2-weighted magnetic resonance images. It uses Analyse™10.0 and was applied to 100 mild stroke patients’ datasets. We used linear regression to test association between BGPVS count, volume and visual rating scores; and between BGPVS count & volume, white matter hyperintensity (WMH) rating scores (periventricular: PVH; deep: DWMH) & volume, atrophy rating scores and brain volume. Results In the 100 patients WMH ranged from 0.4 to 119 ml, and total brain tissue volume from 0.65 to 1.45 l. BGPVS volume increased with BGPVS count (67.27, 95%CI [57.93–76.60], p < 0.001). BGPVS count was positively associated with WMH visual rating (PVH: 2.20, 95%CI [1.22–3.18], p < 0.001; DWMH: 1.92, 95%CI [0.99–2.85], p < 0.001), WMH volume (0.065, 95%CI [0.034 0.096], p < 0.001), and whole brain atrophy visual rating (1.01, 95%CI [0.49 1.53], p < 0.001). BGPVS count increased as brain volume (as % of ICV) decreased (−0.33, 95%CI [−0.53 to −0.13], p = 0.002). Comparison with existing method BGPVS count and volume increased with the overall increase of BGPVS visual scores (2.11, 95%CI [1.36–2.86] for count and 0.022, 95%CI [0.012–0.031] for volume, p < 0.001). Distributions for PVS count and visual scores were also similar. Conclusions This semi-automatic method is applicable to clinical protocols and offers quantitative surrogates for PVS load. It shows good agreement with a visual rating scale and confirmed that BGPVS are associated with WMH and atrophy measurements.
Original languageEnglish
Pages (from-to)34-44
JournalJournal of Neuroscience Methods
Volume257
Early online date28 Sep 2015
DOIs
Publication statusPublished - 15 Jan 2016

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