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• Clinical Article •
Histogram texture analysis on vulnerability of symptomatic plaques in intracranial atherosclerosis
SHI Zhang  CHEN Hai-hu  LI Jing  TIAN Xia  ZHANG Xue-feng  PENG Wen-jia  CHEN Lu-guang  LU Jian-ping  WANG Li  LIU Qi 

Co-first Author: CHEN Hai-hu DOI:10.12015/issn.1674-8034.2018.03.005.


[Abstract] Objective: The aim of the present study is to evaluate differences in histogram features between symptomatic and asymptomatic plaques in intracranial atherosclerotic disease on HR-MRI.Materials and Methods: This study population was retrospectively selected from patients with intracranial stenosis who underwent intracranial HR-MRI between January 2016 and January 2017, from whom all of the plaque features were extracted using CMR Tools and Image J software. Statistical analysis was performed using a logistic regression model.Results: A total of 133 plaques were identified in the 133 patients (mean age 58.5±11.4 years), of which 75 patients were considered with acute ischemic stroke and 58 patients were asymptomatic. T1 images would have a higher sensitivity to predict the vulnerability of atherosclerotic plaques by the quantitative histogram analysis compared with T2 and T1-enhancement images. Multiple logistic regression analysis showed that MLA (OR=1.301, 95% CI, 1.036—1.633), IPH (OR=12.440, 95% CI, 1.551—99.780) and CV (OR=3.476, 95% CI, 1.513—7.985) were important predictors to define symptomatic plaques. Both the morphological and histogram features had been combined to classify the intracranial atherosclerotic plaques was better than the method on the single way, where the area under the curve (AUC) of ROC curve was 0.801.Conclusions: This study demonstrated that quantitative histogram analysis based on T1WI without enhancement could help distinguish acute symptomatic from asymptomatic plaques in intracranial atherosclerosis, and it is better than traditional method to differentiate acute symptomatic and asymptomatic intracranial atherosclerotic plaques.
[Keywords] Intracranial arteriosclerosis；MRI；stroke

SHI Zhang Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

CHEN Hai-hu Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

LI Jing Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

TIAN Xia Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

ZHANG Xue-feng Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

PENG Wen-jia Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

CHEN Lu-guang Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

LU Jian-ping Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

WANG Li Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

LIU Qi* Department of Radiology, Changhai Hospital, Second Military Medical University, Shanghai 200433, China

*Corresponding to: Liu Q, Email: liuqimd@126.com Wang L, E-mail: wangli-changhai@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was supported in part by the National Natural Science Foundation of China No. 81670396, 31470910 The Emerging Frontier Technology Joint Research Program of Shanghai Municipal Hospital of China No. SHDC12013110 The "Twelfth Five-Year" Plan of the Medical Research of the Chinese People's Liberation Army No.BWS12J026
Received  2017-10-11
Accepted  2017-11-18
DOI: 10.12015/issn.1674-8034.2018.03.005
Co-first Author: CHEN Hai-hu DOI:10.12015/issn.1674-8034.2018.03.005.

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