We assessed the benefit of combining stress cardiac CT perfusion (CCTP) myocardial blood flow (MBF) with coronary CT angiography (CCTA) using our innovative CCTP software. By combining CCTA and CCTP, one can uniquely identify a flow limiting stenosis (obstructive-lesion + low-MBF) versus MVD (no-obstructive-lesion + low-MBF. We retrospectively evaluated 104 patients with suspected CAD, including 18 with diabetes, who underwent CCTA+CCTP. Whole heart and territorial MBF was assessed using our automated pipeline for CCTP analysis that included beam hardening correction; temporal scan registration; automated segmentation; fast, accurate, robust MBF estimation; and visualization. Stenosis severity was scored using the CCTA coronary-artery-disease-reporting-and-data-system (CAD-RADS), with obstructive stenosis deemed as CAD-RADS>=3. We established a threshold MBF (MBF=199-mL/min-100g) for normal perfusion. In patients with CAD-RADS>=3, 28/37(76%) patients showed ischemia in the corresponding territory. Two patients with obstructive disease had normal perfusion, suggesting collaterals and/or a hemodynamically insignificant stenosis. Among diabetics, 10 of 18 (56%) demonstrated diffuse ischemia consistent with MVD. Among non-diabetics, only 6% had MVD. Sex-specific prevalence of MVD was 21%/24% (M/F). On a per-vessel basis (n=256), MBF showed a significant difference between territories with and without obstructive stenosis (165 +/- 61 mL/min-100g vs. 274 +/- 62 mL/min-100g, p <0.05). A significant and negative rank correlation (rho=-0.53, p<0.05) between territory MBF and CAD-RADS was seen. CCTA in conjunction with a new automated quantitative CCTP approach can augment the interpretation of CAD, enabling the distinction of ischemia due to obstructive lesions and MVD.
@article{arxiv.2401.17433,
title = {Coronary CTA and Quantitative Cardiac CT Perfusion (CCTP) in Coronary Artery Disease},
author = {Hao Wu and Yingnan Song and Ammar Hoori and Ananya Subramaniam and Juhwan Lee and Justin Kim and Tao Hu and Sadeer Al-Kindi and Wei-Ming Huang and Chun-Ho Yun and Chung-Lieh Hung and Sanjay Rajagopalan and David L. Wilson},
journal= {arXiv preprint arXiv:2401.17433},
year = {2024}
}