Related Experiment Video

Updated: Jan 11, 2026

Assessment of Vascular Tone Responsiveness using Isolated Mesenteric Arteries with a Focus on Modulation by Perivascular Adipose Tissues
08:41

Assessment of Vascular Tone Responsiveness using Isolated Mesenteric Arteries with a Focus on Modulation by Perivascular Adipose Tissues

Published on: June 3, 2019

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Pericoronary Adipose Tissue as a Predictor of Diastolic Dysfunction: A New Paradigm in Coronary Artery Disease

Ritika Agarwal1, Jahnavi Gaduputi1, Karthik R Shetty1

  • 1Department of Radiodiagnosis, Ramaiah Medical College, Bangalore, Karnataka, India.

International Journal of Heart Failure
|November 17, 2025
PubMed

Insights

Pericoronary adipose tissue (PCAT) fat attenuation index (FAI) in the right coronary artery (RCA) strongly correlates with coronary artery disease (CAD) severity and diastolic dysfunction, aiding risk assessment.

Area of Science:

  • Cardiology
  • Radiology
  • Biomedical Engineering

Background:

  • Pericoronary adipose tissue (PCAT) changes are implicated in coronary artery disease (CAD) progression.
  • PCAT's role in vascular biology and adipose homeostasis disruption is under investigation.

Purpose of the Study:

  • To investigate the relationship between PCAT characteristics (volume, fat attenuation index - FAI) and CAD severity.
  • To assess the association of PCAT metrics with left ventricular (LV) function, including diastolic function.

Main Methods:

  • 100 patients with suspected CAD underwent coronary computed tomography angiography (CCTA) and echocardiography.
  • PCAT volume and FAI were measured along major coronary arteries (RCA, LAD, LCX).
  • CAD severity was quantified by Gensini score; LV function was assessed via echocardiography. Spearman's correlation was used for analysis.

Main Results:

  • Right coronary artery (RCA) FAI showed the strongest correlation with CAD severity (Gensini score) and diastolic dysfunction.
  • Left anterior descending (LAD) and left circumflex (LCX) FAI also demonstrated significant associations with CAD.
  • RCA volume correlated with LV mass index and diastolic parameters; hypertension was linked to elevated RCA PCAT metrics.

Conclusions:

  • PCAT FAI, particularly in the RCA, serves as a sensitive indicator of CAD severity and diastolic dysfunction.
  • Integrating PCAT metrics into CCTA analysis can improve cardiovascular risk stratification and personalized treatment planning.
Abstract

Keywords:
Computed tomography angiographyCoronary artery diseaseLeft ventricular dysfunctionPericoronary adipose tissueRisk assessment

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