Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
102 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Cardiac CT perfusion imaging of pericoronary adipose tissue (PCAT) highlights potential confounds in coronary CTA (2306.15593v1)

Published 27 Jun 2023 in cs.CV

Abstract: Features of pericoronary adipose tissue (PCAT) assessed from coronary computed tomography angiography (CCTA) are associated with inflammation and cardiovascular risk. As PCAT is vascularly connected with coronary vasculature, the presence of iodine is a potential confounding factor on PCAT HU and textures that has not been adequately investigated. Use dynamic cardiac CT perfusion (CCTP) to inform contrast determinants of PCAT assessment. From CCTP, we analyzed HU dynamics of territory-specific PCAT, myocardium, and other adipose depots in patients with coronary artery disease. HU, blood flow, and radiomics were assessed over time. Changes from peak aorta time, Pa, chosen to model the time of CCTA, were obtained. HU in PCAT increased more than in other adipose depots. The estimated blood flow in PCAT was ~23% of that in the contiguous myocardium. Comparing PCAT distal and proximal to a significant stenosis, we found less enhancement and longer time-to-peak distally. Two-second offsets [before, after] Pa resulted in [ 4-HU, 3-HU] differences in PCAT. Due to changes in HU, the apparent PCAT volume reduced ~15% from the first scan (P1) to Pa using a conventional fat window. Comparing radiomic features over time, 78% of features changed >10% relative to P1. CCTP elucidates blood flow in PCAT and enables analysis of PCAT features over time. PCAT assessments (HU, apparent volume, and radiomics) are sensitive to acquisition timing and the presence of obstructive stenosis, which may confound the interpretation of PCAT in CCTA images. Data normalization may be in order.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (13)
  1. Hao Wu (623 papers)
  2. Yingnan Song (6 papers)
  3. Ammar Hoori (11 papers)
  4. Ananya Subramaniam (2 papers)
  5. Juhwan Lee (15 papers)
  6. Justin Kim (7 papers)
  7. Tao Hu (146 papers)
  8. Sadeer Al-Kindi (9 papers)
  9. Wei-Ming Huang (7 papers)
  10. Chun-Ho Yun (3 papers)
  11. Chung-Lieh Hung (3 papers)
  12. Sanjay Rajagopalan (5 papers)
  13. David L. Wilson (13 papers)
Citations (4)