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Shi Z, Li J, Zhao M, Peng W, Meddings Z, Jiang T, Liu Q, Teng Z, Lu J. Quantitative Histogram Analysis on Intracranial Atherosclerotic Plaques: A High-Resolution Magnetic Resonance Imaging Study. Stroke 2020; 51:2161-2169. [PMID: 32568660 PMCID: PMC7306260 DOI: 10.1161/strokeaha.120.029062] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND AND PURPOSE Intracranial atherosclerosis is one of the main causes of stroke, and high-resolution magnetic resonance imaging provides useful imaging biomarkers related to the risk of ischemic events. This study aims to evaluate differences in histogram features between culprit and nonculprit intracranial atherosclerosis using high-resolution magnetic resonance imaging. METHODS Two hundred forty-seven patients with intracranial atherosclerosis who underwent high-resolution magnetic resonance imaging sequentially between January 2015 and December 2016 were recruited. Quantitative features, including stenosis, plaque burden, minimum luminal area, intraplaque hemorrhage, enhancement ratio, and dispersion of signal intensity (coefficient of variation), were analyzed based on T2-, T1-, and contrast-enhanced T1-weighted images. Step-wise regression analysis was used to identify key determinates differentiating culprit and nonculprit plaques and to calculate the odds ratios (ORs) with 95% CIs. RESULTS In total, 190 plaques were identified, of which 88 plaques (37 culprit and 51 nonculprit) were located in the middle cerebral artery and 102 (57 culprit and 45 nonculprit) in the basilar artery. Nearly 90% of culprit lesions had a degree of luminal stenosis of <70%. Multiple logistic regression analyses showed that intraplaque hemorrhage (OR, 16.294 [95% CI, 1.043-254.632]; P=0.047), minimum luminal area (OR, 1.468 [95% CI, 1.032-2.087]; P=0.033), and coefficient of variation (OR, 13.425 [95% CI, 3.987-45.204]; P<0.001) were 3 significant features in defining culprit plaques in middle cerebral artery. The enhancement ratio (OR, 9.476 [95% CI, 1.256-71.464]; P=0.029), intraplaque hemorrhage (OR, 2.847 [95% CI, 0.971-10.203]; P=0.046), and coefficient of variation (OR, 10.068 [95% CI, 2.820-21.343]; P<0.001) were significantly associated with plaque type in basilar artery. Coefficient of variation was a strong independent predictor in defining plaque type for both middle cerebral artery and basilar artery with sensitivity, specificity, and accuracy being 0.79, 0.80, and 0.80, respectively. CONCLUSIONS Features characterized by high-resolution magnetic resonance imaging provided complementary values over luminal stenosis in defined lesion type for intracranial atherosclerosis; the dispersion of signal intensity in histogram analysis was a particularly effective predictive parameter.
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Affiliation(s)
- Zhang Shi
- Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China
- Department of Radiology, University of Cambridge, United Kingdom (Z.S., Z.M., Z.T.)
| | - Jing Li
- Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China
| | - Ming Zhao
- Department of Neurology (M.Z.), Changhai Hospital, Naval Medical University, Shanghai, China
| | - Wenjia Peng
- Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China
| | - Zakaria Meddings
- Department of Radiology, University of Cambridge, United Kingdom (Z.S., Z.M., Z.T.)
| | - Tao Jiang
- Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China
| | - Qi Liu
- Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China
| | - Zhongzhao Teng
- Department of Radiology, University of Cambridge, United Kingdom (Z.S., Z.M., Z.T.)
- Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, China (Z.T.)
| | - Jianping Lu
- Department of Radiology (Z.S., J. Li, W.P., T.J., Q.L., J. Lu), Changhai Hospital, Naval Medical University, Shanghai, China
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