Keywords: Myocardium, Radiomics
Motivation: Right ventricular (RV) dilation and exercise intolerance are important prognostic indicators in repaired Tetralogy of Fallot (rTOF) patients. The conventional native T1 value may ignore subtle changes of myocardial fibrosis patterns in rTOF patients. Radiomics uncovers concealed insights regarding cardiomyopathy.
Goal(s): To establish a radiomics model using native T1 mapping for identifying rTOF patients with severe RV dilation and exercise intolerance.
Approach: We extracted 623 radiomic features from native T1 mapping and employed machine learning for feature selection and classification that enhance diagnostic accuracy in identifying cardiac involvements.
Results: Optimal performance was achieved in the segmental mid-slice T1 mapping model.
Impact: The radiomic analysis of myocardial native T1 can reveal the different myocardial T1 distribution patterns between different severity of RV dilation and exercise intolerance before substantial changes of conventional native T1 values.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords