Nomogram for evaluating coronary revascularisation necessity based on multi-parameter coronary CT angiography

Area of Science:

• Cardiovascular Imaging
• Interventional Cardiology
• Radiology

Background:

• Coronary computed tomography angiography (CCTA) is crucial for diagnosing coronary artery disease.
• Accurate assessment of revascularisation necessity is vital for optimal patient outcomes.
• Current methods may have limitations in precisely determining the need for revascularisation.

Purpose of the Study:

• To develop and validate a nomogram model using multi-parameter CCTA data.
• To enhance the accuracy in evaluating the necessity of coronary revascularisation.
• To identify key predictors for revascularisation decisions.

Main Methods:

• Retrospective analysis of 335 patients requiring revascularisation and 208 not undergoing revascularisation post-CCTA.
• Analysis of CCTA parameters including stenosis, plaque characteristics, and CT-derived fractional flow reserve (CT-FFR).
• Development of multi-parameter models and a nomogram using regression analysis and R programming.

Main Results:

• The multi-parameter CCTA model demonstrated superior performance (AUC 0.894) compared to individual parameters.
• Key predictors identified: CCTA stenosis, positive remodelling, total plaque volume, non-calcified plaque volume proportion, and CT-FFR.
• A nomogram was successfully constructed based on these independent risk factors.

Conclusions:

• The developed multi-parameter CCTA model significantly improves the evaluation of revascularisation necessity.
• The nomogram offers a promising tool for clinical decision-making in patients with coronary artery disease.
• This approach aids in more precise patient selection for revascularisation procedures.