1
|
Wang C, Li Y, Lv J, Jin J, Hu X, Kuang X, Chen W, Wang H. Recommendation for Cardiac Magnetic Resonance Imaging-Based Phenotypic Study: Imaging Part. PHENOMICS 2021; 1:151-170. [PMID: 35233561 PMCID: PMC8318053 DOI: 10.1007/s43657-021-00018-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 05/22/2021] [Accepted: 05/25/2021] [Indexed: 11/26/2022]
Abstract
Cardiac magnetic resonance (CMR) imaging provides important biomarkers for the early diagnosis of many cardiovascular diseases and has been reported to reveal phenome-wide associations of cardiac/aortic structure and functionality in population studies. Nevertheless, due to the complexity of operation and variations among manufactural vendors, magnetic field strengths, coils, sequences, scan parameters, and image analysis approaches, CMR is rarely used in large cohort studies. Existing guidelines mainly focused on the diagnosis of cardiovascular diseases, which did not aim to basic research. The purpose of this study was to propose a recommendation for CMR based phenotype measurements for cohort study. We classify the imaging sequences of CMR into three categories according to the importance and universality of corresponding measurable phenotypes. The acquisition time and repeatability of the phenotypic measurement were also taken into consideration during the categorization. Unlike other guidelines, this recommendation focused on quantitative measurement of large amount of phenotypes from CMR.
Collapse
Affiliation(s)
- Chengyan Wang
- Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong New District, Shanghai, 201203 China
| | - Yan Li
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Lv
- School of Computer and Control Engineering, Yantai University, Yantai, China
| | - Jianhua Jin
- School of Data Science, Fudan University, Shanghai, China
| | - Xumei Hu
- Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong New District, Shanghai, 201203 China
| | - Xutong Kuang
- Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong New District, Shanghai, 201203 China
| | - Weibo Chen
- Philips Healthcare. Co., Shanghai, China
| | - He Wang
- Human Phenome Institute, Fudan University, 825 Zhangheng Road, Pudong New District, Shanghai, 201203 China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 220 Handan Road, Yangpu District, Shanghai, 200433 China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| |
Collapse
|
2
|
Intra- and inter-reader reproducibility of blood flow measurements on the ascending aorta and pulmonary artery using cardiac magnetic resonance. Radiol Med 2016; 122:179-185. [DOI: 10.1007/s11547-016-0706-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 10/31/2016] [Indexed: 11/24/2022]
|