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Updated: Jan 7, 2026

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Published on: January 14, 2014
Pericardial Fat Radiomics to Predict Left Ventricular Involvement and Provide Incremental Prognostic Value in ARVC.
Mengqi Guo1, Jinyu Zheng1, Weihui Xie1
1Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
Pericardial fat tissue (PFT) radiomics can predict left ventricular (LV) involvement and major adverse cardiac events (MACE) in arrhythmogenic right ventricular cardiomyopathy (ARVC) patients, aiding in risk stratification.
Area of Science:
- Cardiology
- Medical Imaging
- Radiology
Background:
- Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a heritable heart muscle disease.
- Left ventricular (LV) involvement and major adverse cardiac events (MACE) are critical indicators of ARVC prognosis.
- Non-invasive imaging biomarkers for predicting ARVC outcomes are needed.
Purpose of the Study:
- To investigate the predictive capability of pericardial fat tissue (PFT) radiomics for LV involvement in ARVC.
- To assess the association between PFT radiomics and MACE in ARVC patients.
- To develop a risk stratification tool combining PFT radiomics and right ventricular ejection fraction (RVEF).
Main Methods:
- Retrospective multicenter study analyzing 122 ARVC patients.
- Cardiac magnetic resonance (CMR) used for LV involvement assessment.
- A radiomic score (RS) from PFT was developed and validated to predict LV involvement and MACE.
Main Results:
- The PFT radiomic score (RS) effectively predicted LV involvement in both development and test sets (AUCs 0.771 and 0.785).
- A high RS was independently associated with increased MACE risk over 5 years (HR 3.452, p < 0.001).
- A simplified risk score integrating RVEF and RS categorized patients into low, intermediate, and high-risk groups.
Conclusions:
- PFT radiomics serves as a valuable tool for predicting LV involvement in ARVC.
- PFT radiomics is significantly associated with MACE, offering prognostic information.
- The combined risk score aids in stratifying ARVC patient risk for improved management.
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