Abstract 35: Vessel Wall Magnetic Resonance Imaging Biomarkers of Symptomatic Intracranial Atherosclerosis: A Meta-Analysis

Abstract

Background: Intracranial vessel wall MR imaging (VWI) may be able to identify imaging biomarkers of symptomatic plaque. A meta-analysis was performed to evaluate the strength of association of imaging features of symptomatic plaque on VWI and downstream ischemia. Methods: PubMed, Scopus, Web of Science, EMBASE and Cochrane databases were searched up to October 2019. Studies evaluating acute/subacute cerebrovascular ischemia using VWI on 1.5 or 3 Tesla MR were included. Studies with insufficient exclusion of other stroke etiologies, insufficient or duplicated data and conference abstracts were excluded. Two independent reviewers extracted data on study design, VWI techniques, imaging endpoints, and conducted a study design risk bias assessment using the QUADAS-2 tool. Per-lesion odds ratios (OR) were calculated and pooled using a bivariate random-effects model. Subgroup analyses and evaluation of publication bias were performed. Results: Twenty-one articles met inclusion criteria (1,750 lesions; 1,542 subjects). Plaque enhancement (OR 7.4, 95% CI 3.4-16.4; Figure), positive remodeling (OR 5.6, 95% CI 2.2-14.0), surface irregularity (OR 4.5, 95% CI 1.4-8.6), and T1 hyperintensity (OR 2.1, 95% CI 1.3-3.3) were significantly associated with downstream ischemia. T2 signal intensity was not significant (p=0.59). Plaque enhancement showed stronger associations when measured in retrospectively designed studies (OR 35.3, 95% CI 7.4-141, p=0.02), by a radiologist as a rater (OR 12.6, 95% CI 5.3-29.7, p<0.001), and on VWI pulse sequences with lower spatial resolution (OR 30.4, 95% CI 7.0-132.4, p=0.02). There was no publication bias (Egger’s test p=0.48). Conclusions: Plaque enhancement, positive remodeling, T1 hyperintensity and surface irregularity emerged as imaging biomarkers of symptomatic plaque. Plaque enhancement had the strongest association and remained significant accounting for sources of bias and variability in both study design and instrument.