Quantitative plaque analysis with A.I.-augmented CCTA in end-stage renal disease and complex CAD

Area of Science:

• Cardiovascular Imaging
• Artificial Intelligence in Medicine
• Nephrology

Background:

• Adverse cardiovascular events are a major cause of mortality in end-stage renal disease (ESRD) patients.
• Atherosclerotic plaque characteristics (APC) may significantly contribute to cardiovascular risk in ESRD.
• Atherosclerotic phenotypes in dialysis patients have not been well-described.

Purpose of the Study:

• To define atherosclerotic plaque characteristics (APC) in dialysis patients.
• To utilize artificial-intelligence augmented coronary computed tomography angiography (CCTA) for this characterization.
• To investigate the feasibility of AI-CCTA in ESRD patients with potentially severe coronary calcification.

Main Methods:

• Retrospective analysis of ESRD patients undergoing CCTA.
• Utilized an FDA-approved artificial-intelligence augmented-CCTA program (Cleerly).
• Evaluated coronary lesions for APCs including percent atheroma volume (PAV), low-density non-calcified plaque (LD-NCP), non-calcified plaque (NCP), calcified plaque (CP), and high-risk plaque (HRP).

Main Results:

• 81.0% of 79 ESRD patients exhibited high-risk plaque (HRP).
• Elevated plaque burden (TPV, LD-NCP, NCP, CP) was observed in patients with obstructive lesions.
• Older patients (>65 years) showed more calcified plaque (CP) and higher PAV; men had more 2-feature plaques and higher plaque volumes.

Conclusions:

• AI-augmented CCTA is feasible for characterizing coronary artery disease (CAD) in ESRD patients, even with severe calcification.
• ESRD patients demonstrate elevated plaque burden and stenosis, primarily due to non-calcified plaque.
• AI-augmented CCTA analysis of APCs shows promise for cardiac risk stratification in ESRD patients.