An enriched survival study of epicardial adipose tissues risk on major adverse cardiovascular event in CT calcium score images

Ammar Hoori; Tao Hu; Juhwan Lee; Sadeer Al-Kindi; Sanjay Rajagopalan; David L. Wilson

doi:10.1117/12.2653613

10 April 2023 An enriched survival study of epicardial adipose tissues risk on major adverse cardiovascular event in CT calcium score images

Ammar Hoori, Tao Hu, Juhwan Lee, Sadeer Al-Kindi, Sanjay Rajagopalan, David L. Wilson

Author Affiliations +

Proceedings Volume 12468, Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging; 124680T (2023) https://doi.org/10.1117/12.2653613
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

We extracted features of fat depots from computed tomography calcium score (CTCS) images to predict a future major adverse cardiovascular event (MACE). Our work builds on two observations: 1) Agatston score for coronary calcifications is known to be predictive and 2) studies have shown association of epicardial adipose tissue (EAT) volume with MACE. We extracted many features of fat depots (fat-omics) and used feature assessments in modeling to predict MACE. We used time-to-event Cox model with an elastic net regularization to identify the most compelling fat-omics features, including morphological (e.g., volume and thickness) and intensity statistics (e.g., mean and max HU). We collected and engineered EAT features from a 6-year cohort study of 339 individuals (58.7%MACE) from the University Hospitals Cleveland. The cohort was MACE-enriched to balance data and to enable precise determination of best features. We found that body mass index (BMI) was not a good surrogate for EAT volume, as the correlation was minimal. The 2-year ROC result of fat-omics model was superior to other univariate models (i.e., BMI, EAT volume, and Agatston), with AUC=0.72 compared to (0.56, 0.54, and 0.57), respectively. In addition, high- and low-risk stratification was improved. In a further experiment using 166 zero-Agatston cases with 59%MACE, fat-omics model outperformed BMI or EAT. Fat-omics had AUC=0.66 compared to (0.56,0.49), respectively. Promising results indicate the importance of EAT fat-omics over traditional BMI, EAT volume, and Agatston score. Fat-omics with calcifications analyses may significantly improve MACE prediction from CTCS images.

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Citation Download Citation

Ammar Hoori, Tao Hu, Juhwan Lee, Sadeer Al-Kindi, Sanjay Rajagopalan, and David L. Wilson "An enriched survival study of epicardial adipose tissues risk on major adverse cardiovascular event in CT calcium score images", Proc. SPIE 12468, Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging, 124680T (10 April 2023); https://doi.org/10.1117/12.2653613

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