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Home / Journal of Medical Imaging and Health Informatics, Volume 10, Number 7

T1 Mapping for Noninvasively Detecting Diffuse Fibrosis in Severe Aortic Stenosis

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Purpose: To evaluate myocardial diffuse fibrosis in severe aortic stenosis (SAS) with cardiac magnetic resonance imaging (MRI) T1 mapping technique. Methods: Twenty-seven SAS patients and 15 controls were enrolled and performed cardiac MRI. Left ventricular (LV) structure, function and T1-derived parameters were measured to compare between SAS group and the controls. Correlation between T1-derived parameters and the extent of histologic fibrosis was performed in 15 patients who underwent aortic valve replacement surgery and myocardial biopsy. Results: The SAS group had LV remodeling with ventricular dilatation, hypertrophy, and contractile dysfunction. The native T1 (1336.2±62.5 ms vs. 1277.6±40.7 ms, p = 0.002) and extracellular volume fraction (ECV%) (26.7±2.2% vs. 24.9±2.2%, p = 0.018) were elevated in the SAS in comparison to the controls. Only ECV and λ correlated with the extent of fibrosis as measured by histology. Conclusion: Cardiac MRI with T1 mapping provides a noninvasive approach to evaluate LV myocardial diffuse fibrosis in SAS.

Keywords: Cardiac Magnetic Resonance Imaging; Extracellular Volume Fraction; Myocardial Diffuse Fibrosis; Severe Aortic Stenosis; T1 Mapping

Document Type: Research Article

Affiliations: 1: Department of Radiology, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510180, China 2: Department of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510030, China 3: Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, 510641, China 4: Medical Research Center, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, 510030, China 5: Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou and Healthy Aging Research Center, Chang Gung University, Taoyuan, 10699, Taiwan 6: Sleep Center, Department of Respiratory and Critical Care Medicine, Guangdong Institute of Geriatrics, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangdong, 510030, China 7: School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, 510030, China 8: Department of Catheterization Lab, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, 510030, China

Publication date: 01 July 2020

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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