Automated Measurement of Pericoronary Adipose Tissue Attenuation and
  Volume in CT Angiography
Andrew M. Nguyen Tejas Sudharshan Mathai Liangchen Liu Jianfei Liu Ronald M. Summers
Pericoronary adipose tissue (PCAT) is the deposition of fat in the vicinity
of the coronary arteries. It is an indicator of coronary inflammation and
associated with coronary artery disease. Non-invasive coronary CT angiography
(CCTA) is presently used to obtain measures of the thickness, volume, and
attenuation of fat deposition. However, prior works solely focus on measuring
PCAT using semi-automated approaches at the right coronary artery (RCA) over
the left coronary artery (LCA). In this pilot work, we developed a fully
automated approach for the measurement of PCAT mean attenuation and volume in
the region around both coronary arteries. First, we used a large subset of
patients from the public ImageCAS dataset (n = 735) to train a 3D full
resolution nnUNet to segment LCA and RCA. Then, we automatically measured PCAT
in the surrounding arterial regions. We evaluated our method on a held-out test
set of patients (n = 183) from the same dataset. A mean Dice score of 83% and
PCAT attenuation of -73.81 $\pm$ 12.69 HU was calculated for the RCA, while a
mean Dice score of 81% and PCAT attenuation of -77.51 $\pm$ 7.94 HU was
computed for the LCA. To the best of our knowledge, we are the first to develop
a fully automated method to measure PCAT attenuation and volume at both the RCA
and LCA. Our work underscores how automated PCAT measurement holds promise as a
biomarker for identification of inflammation and cardiac disease.