# Quantification of water and lipid composition of perivascular adipose tissue using coronary CT angiography: a simulation study

## TL;DR

This study uses CT scans to measure water and lipid content in perivascular fat, aiming to detect early signs of vascular inflammation.

## Contribution

A novel simulation method to quantify PVAT composition using CT and assess variability due to voltage and patient size.

## Key findings

- PVAT CT numbers increase with higher tube voltages and larger patient sizes.
- Water volumetric fraction measurements have low RMSE when using 120 kV.
- Decomposition method can enable early detection of coronary artery inflammation.

## Abstract

Early detection of vascular inflammation via perivascular adipose tissue (PVAT) compositional changes (e.g., increased water content) could improve cardiovascular risk stratification. However, CT-based measurements face variability due to tube voltage and patient size. This study aims to quantify perivascular adipose tissue (PVAT) composition (water, lipid, protein) using coronary CT angiography and assess impacts of tube voltage, patient size, and positional variability on measurements. A 320-slice CT simulation generated anthropomorphic thorax phantoms (small, medium, large) with fat rings mimicking different patient sizes. Ten randomized water-lipid-protein inserts were placed within the thorax phantom. Three-material decomposition was applied using medium phantoms with different tube voltages and different patient sizes at 120 kV. PVAT CT number (HU) increased with higher tube voltages and larger patient sizes. The root-mean-squared errors (RMSE) for water volumetric fraction measurements were 0.26%, 0.64%, 0.01%, and 0.15% for 80, 100, 120, and 135 kV, respectively, and 0.19%, 0.35%, and 0.61% for small, medium, and large size phantoms at 120 kV, respectively. The root-mean-squared deviations (RMSD) were 3.52%, 2.94%, 4.96%, and 6.00% for 80, 100, 120, and 135 kV, respectively, and 3.82%, 3.74%, and 6.05% for small, medium, and large size phantoms at 120 kV, respectively. Clinically relevant water fractions spanned 17–37%, with inflammation expected to alter values by approximately 5%. The findings of this study indicate that, after accounting for the effects of tube voltage and patient size, perivascular adipose tissue CT number can be quantitatively represented in terms of its water composition. This decomposition method has the potential to enable quantification of water composition and facilitate early detection of coronary artery inflammation.