Background And Purpose: Intracranial atherosclerotic disease is a common cause of stroke worldwide. Intracranial vessel wall magnetic resonance imaging may be able to identify imaging biomarkers of symptomatic plaque. We performed a meta-analysis to evaluate the strength of association of imaging features of symptomatic plaque leading to downstream ischemic events. Effects on the strength of association were also assessed accounting for possible sources of bias and variability related to study design and magnetic resonance parameters.
Methods: PubMed, Scopus, Web of Science, EMBASE, and Cochrane databases were searched up to October 2019. Two independent reviewers extracted data on study design, vessel wall magnetic resonance imaging techniques, and imaging end points. Per-lesion odds ratios (OR) were calculated and pooled using a bivariate random-effects model. Subgroup analyses, sensitivity analysis, and evaluation of publication bias were also performed.
Results: Twenty-one articles met inclusion criteria (1750 lesions; 1542 subjects). Plaque enhancement (OR, 7.42 [95% CI, 3.35-16.43]), positive remodeling (OR, 5.60 [95% CI, 2.23-14.03]), T1 hyperintensity (OR, 2.05 [95% CI, 1.27-3.32]), and surface irregularity (OR, 4.50 [95% CI, 1.39-8.57]) were significantly associated with downstream ischemic events. T2 signal intensity was not significant (=0.59). Plaque enhancement was significantly associated with downstream ischemic events in all subgroup analyses and showed stronger associations when measured in retrospectively designed studies (=0.02), by a radiologist as a rater (<0.001), and on lower vessel wall magnetic resonance imaging spatial resolution sequences (=0.02).
Conclusions: Plaque enhancement, positive remodeling, T1 hyperintensity, and surface irregularity emerged as strong imaging biomarkers of symptomatic plaque in patients with ischemic events. Plaque enhancement remained significant accounting for sources of bias and variability in both study design and instrument. Future studies evaluating plaque enhancement as a predictive marker for stroke recurrence with larger sample sizes would be valuable.
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http://dx.doi.org/10.1161/STROKEAHA.120.031480 | DOI Listing |
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