D Yang1,2, Y Liu3, Y Han1,2, D Li1,2, W Wang3, R Li2, C Yuan4, X Zhao5. 1. From the Beijing Institute of Brain Disorders (D.Y., Y.H., D.L.), Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China. 2. Department of Biomedical Engineering (D.Y., Y.H., D.L., R.L., X.Z.), Center for Biomedical Imaging Research, Tsinghua University School of Medicine, Beijing, China. 3. Department of Radiology (Y.L., W.W.), The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China. 4. Department of Radiology (C.Y.), University of Washington, Seattle, Washington. 5. Department of Biomedical Engineering (D.Y., Y.H., D.L., R.L., X.Z.), Center for Biomedical Imaging Research, Tsinghua University School of Medicine, Beijing, China xihaizhao@tsinghua.edu.cn.
Abstract
BACKGROUND AND PURPOSE: Identifying the mere presence of carotid intraplaque hemorrhage would be insufficient to accurately discriminate the presence of acute cerebral infarct. We aimed to investigate the association between signal intensity ratios of carotid intraplaque hemorrhage on T1-weighted MR imaging and acute cerebral infarct in patients with hemorrhagic carotid plaques using MR vessel wall imaging. MATERIALS AND METHODS: Symptomatic patients with carotid intraplaque hemorrhage were included. The signal intensity ratios of carotid intraplaque hemorrhage against muscle on T1-weighted, TOF, and MPRAGE images were measured. The acute cerebral infarct was determined on the hemisphere ipsilateral to the carotid intraplaque hemorrhage. The association between signal intensity ratios of carotid intraplaque hemorrhage and acute cerebral infarct was analyzed. RESULTS: Of 109 included patients (mean, 66.8 ± 9.9 years of age; 96 men), 40 (36.7%) had acute cerebral infarct. Patients with acute cerebral infarct had significantly higher signal intensity ratios of carotid intraplaque hemorrhage on T1-weighted images than those without (Median, 1.44; 25-75 Percentiles, 1.14-1.82 versus Median, 1.27; 25-75 Percentiles, 1.06-1.55, P = .022). Logistic regression analysis revealed that the signal intensity ratio of carotid intraplaque hemorrhage on T1-weighted images was significantly associated with acute cerebral infarct before (OR, 4.08; 95% CI, 1.34-12.40; P = .013) and after (OR, 3.34; 95% CI, 1.08-10.31; P = .036) adjustment for clinical confounding factors. However, this association was not significant when further adjusted for occlusion of the carotid artery (P = .058) and volumes of intraplaque hemorrhage and lipid-rich necrotic core (P = .458). CONCLUSIONS: The signal intensity ratio of carotid intraplaque hemorrhage on T1-weighted images is associated with acute cerebral infarct in symptomatic patients with carotid hemorrhagic plaques. This association is independent of traditional risk factors but not of the size of plaque composition. The possibility of applying T1 signals of carotid intraplaque hemorrhage to predict subsequent cerebrovascular ischemic events needs to be prospectively verified.
BACKGROUND AND PURPOSE: Identifying the mere presence of carotid intraplaque hemorrhage would be insufficient to accurately discriminate the presence of acute cerebral infarct. We aimed to investigate the association between signal intensity ratios of carotid intraplaque hemorrhage on T1-weighted MR imaging and acute cerebral infarct in patients with hemorrhagic carotid plaques using MR vessel wall imaging. MATERIALS AND METHODS: Symptomatic patients with carotid intraplaque hemorrhage were included. The signal intensity ratios of carotid intraplaque hemorrhage against muscle on T1-weighted, TOF, and MPRAGE images were measured. The acute cerebral infarct was determined on the hemisphere ipsilateral to the carotid intraplaque hemorrhage. The association between signal intensity ratios of carotid intraplaque hemorrhage and acute cerebral infarct was analyzed. RESULTS: Of 109 included patients (mean, 66.8 ± 9.9 years of age; 96 men), 40 (36.7%) had acute cerebral infarct. Patients with acute cerebral infarct had significantly higher signal intensity ratios of carotid intraplaque hemorrhage on T1-weighted images than those without (Median, 1.44; 25-75 Percentiles, 1.14-1.82 versus Median, 1.27; 25-75 Percentiles, 1.06-1.55, P = .022). Logistic regression analysis revealed that the signal intensity ratio of carotid intraplaque hemorrhage on T1-weighted images was significantly associated with acute cerebral infarct before (OR, 4.08; 95% CI, 1.34-12.40; P = .013) and after (OR, 3.34; 95% CI, 1.08-10.31; P = .036) adjustment for clinical confounding factors. However, this association was not significant when further adjusted for occlusion of the carotid artery (P = .058) and volumes of intraplaque hemorrhage and lipid-rich necrotic core (P = .458). CONCLUSIONS: The signal intensity ratio of carotid intraplaque hemorrhage on T1-weighted images is associated with acute cerebral infarct in symptomatic patients with carotid hemorrhagic plaques. This association is independent of traditional risk factors but not of the size of plaque composition. The possibility of applying T1 signals of carotid intraplaque hemorrhage to predict subsequent cerebrovascular ischemic events needs to be prospectively verified.
Authors: J Scott McNally; Michael S McLaughlin; Peter J Hinckley; Scott M Treiman; Gregory J Stoddard; Dennis L Parker; Gerald S Treiman Journal: Stroke Date: 2014-11-18 Impact factor: 7.914
Authors: Norihide Takaya; Chun Yuan; Baocheng Chu; Tobias Saam; Nayak L Polissar; Gail P Jarvik; Carol Isaac; Judith McDonough; Cynthia Natiello; Randy Small; Marina S Ferguson; Thomas S Hatsukami Journal: Circulation Date: 2005-05-23 Impact factor: 29.690
Authors: L Dong; H R Underhill; W Yu; H Ota; T S Hatsukami; T L Gao; Z Zhang; M Oikawa; X Zhao; C Yuan Journal: AJNR Am J Neuroradiol Date: 2009-09-24 Impact factor: 3.825
Authors: Navneet Singh; Alan R Moody; David J Gladstone; General Leung; Radhakrishnan Ravikumar; James Zhan; Robert Maggisano Journal: Radiology Date: 2009-06-09 Impact factor: 11.105
Authors: Akram A Hosseini; Neghal Kandiyil; Shane T S Macsweeney; Nishath Altaf; Dorothee P Auer Journal: Ann Neurol Date: 2013-06-04 Impact factor: 10.422
Authors: John C Benson; Heidi Cheek; Marie C Aubry; Giuseppe Lanzino; John Huston Iii; Alejandro Rabinstein; Waleed Brinjikji Journal: Clin Neuroradiol Date: 2021-01-04 Impact factor: 3.649
Authors: Xiaojie He; Guangxiang Liu; Chunying Zou; Rongrui Li; Juan Zhong; Hong Li Journal: Comput Math Methods Med Date: 2022-01-24 Impact factor: 2.238