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  • Title: Quantitative score of the vessel morphology in middle cerebral artery atherosclerosis.
    Author: Meng Y, Li M, Yu Y, Xu Y, Gao S, Feng F, Xu WH.
    Journal: J Neurol Sci; 2019 Apr 15; 399():111-117. PubMed ID: 30798108.
    Abstract:
    BACKGROUND: We aimed to quantitatively assess the vessel morphology of middle cerebral artery (MCA) atherosclerosis and explore its value in discriminating plaque types. METHODS: Patients were selected from a high-resolution magnetic resonance imaging (HRMRI) study from January 2007 to December 2015. One hundred and three patients with acute cerebral infarcts due to MCA stenosis (>50%) and eighty-nine patients with asymptomatic MCA stenosis (>50%) were included. Quantitative measurements of MCA morphology, including lumen area, outer-wall and wall area at stenotic site and reference site, stenotic degree, plaque length, remodeling index and plaque eccentricity, were performed on HRMRI with observers blinded to clinical presentations. Firth's penalized logistic regression analysis was used to construct a symptomatic plaque score (SPS) model. Then, the HRMRI data of 39 patients prospectively enrolled from January 2016 to January 2017 were used to validate the SPS model. RESULTS: The HRMRI data of 103 patients with symptomatic MCA stenosis and 89 patients with asymptomatic MCA stenosis in the construction cohort were analyzed. Four main factors were found to be associated with symptomatic plaques: stenotic lumen area ≥ 2.28 mm2, stenotic wall area ≥ 8.88 mm2, plaque length and presence of an eccentric plaque. Summation of each logistic regression coefficient multiplying the corresponding score produced the SPS with an area under curve (AUC) of 0.890 on receiver operating characteristics analysis. Validation of the score of 39 plaques (19 symptomatic and 20 asymptomatic) revealed an AUC of 0.862, confirming the continued diagnostic ability. When the data were pooled in all 235 plaques, the optimal cutoff score of discriminating symptomatic and asymptomatic plaques was 2.79 (SPS ≥ 2.79 indicating a symptomatic plaque) with AUC = 0.886, sensitivity 81.1% and specificity 80.5%. CONCLUSIONS: The quantitative analysis of MCA morphology can independently and accurately discriminate plaque types, suggesting its close association with the underlying pathophysiology. Further prospective studies are required to verify whether the SPS model is clinically valuable in monitoring plaque progression and assessing the vulnerability.
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