# Usefulness of fat attenuation index in postmortem CT for identifying responsible vessels in acute coronary syndromes: A case report

## TL;DR

This case report shows how the fat attenuation index in postmortem CT can help identify coronary arteries responsible for sudden cardiac death.

## Contribution

This is the first case to demonstrate the effectiveness of FAI in postmortem CT for diagnosing acute coronary syndromes.

## Key findings

- FAI values were -57 HU in the RCA, -73 HU in the LAD, and -64 HU in the LCX.
- Autopsy confirmed significant stenosis in the RCA and LCX, aligning with elevated FAI in the RCA.
- FAI in PMCT can noninvasively detect coronary artery inflammation and identify responsible vessels.

## Abstract

Postmortem imaging, particularly unenhanced postmortem computed tomography (PMCT), has been increasingly utilized for pathological or judicial examination as a substitute for conventional autopsy, to compensate very low autopsy rates. While unenhanced PMCT has a limitation in diagnosing acute coronary syndromes, the fat attenuation index (FAI) which is a novel imaging biomarker measured by clinical coronary CT angiography (CCTA), has been known to noninvasively detect coronary artery inflammation. We investigated the postmortem diagnostic usefulness of perivascular FAI measured by CCTA in a 61-year-old male who died suddenly after chest pain. PMCT and autopsy were conducted 92 hours after death. FAI measurement results were -57 Hounsfield units (HU) in the right coronary artery (RCA), -73 HU in the left anterior descending artery (LAD), and -64 HU in the left circumflex artery (LCX). Autopsy revealed significant stenosis in the RCA and LCX, but no significant stenosis was found in the LAD. The elevated FAI in the RCA suggested acute inflammation, which agreed with the autopsy findings. This case is the first to demonstrate effectiveness of FAI measured with PMCT for identifying the vessels responsible for acute coronary syndromes, indicating its potential in postmortem diagnosis.

Image, graphical abstract