Pericoronary adipose tissue radiomics features as imaging markers for coronary artery disease risk assessment: insights from gene expression analysis

This study aimed to explore the correlation between radiomics features of pericoronary adipose tissue (PCAT) and gene expression in patients with coronary artery disease (CAD), with the goal of identifying novel imaging biomarkers for evaluating CAD.

Our findings demonstrated a significant correlation between PCAT radiomics features and gene expression patterns in CAD patients. These features effectively reflect the pathological state of tissues and hold potential as innovative imaging biomarkers. By leveraging PCAT radiomics, clinicians may gain valuable insights for advanced evaluation and management of CAD in later stages.

Between November 2021 and May 2022, data were collected from 60 patients diagnosed with CAD who underwent coronary artery bypass grafting (CABG) and coronary computed tomography angiography (CCTA). Samples of PCAT, three additional adipose tissue types, and peripheral venous blood were analysed. Radiomics features of PCAT were extracted. Gene expression in adipose tissues and serum was quantified via RT-qPCR, immunohistochemistry and ELISA. The correlations between the radiomics features and genes were analysed.

Gene expression analysis revealed significantly elevated levels of CD31, MCP-1, and leptin in PCAT compared with other adipose tissues, and the radiomics features of PCAT have a strong correction with the expression of CD31 and MCP-1. At the systemic level, serum analysis revealed increased concentrations of TNF-α, IL-6, CD31, COL1A1, and resistin, with notable decreases in ADP in CAD patients relative to controls. Notably, CD31, ADP, IL-6, and resistin were significantly corrlated with PCAT texture features, whereas TNF-α was correlated with first-order features. Conclusions: Our findings demonstrated a significant correlation between PCAT radiomics features and gene expression patterns in CAD patients. These features effectively reflect the pathological state of tissues and hold potential as innovative imaging biomarkers. By leveraging PCAT radiomics, clinicians may gain valuable insights for advanced evaluation and management of CAD in later stages.