Synergistic prognostic value of coronary distensibility index and fractional flow reserve based cCTA for major adverse cardiac events in patients with Coronary artery disease

Abstract

Background Coronary distensibility index (CDI), as an early predictor of cardiovascular diseases, has the potential to complement coronary computed tomography angiography (cCTA)-derived fractional flow reserve (CT-FFR) for predicting major adverse cardiac events (MACEs). Thus, the prognostic value of CT-FFR combined with CDI for MACEs is worth exploring. Methods Patients with a moderate or severe single left anterior descending coronary artery stenosis were included and underwent FFR and CDI analysis based on cCTA, followed up at least 1 year, and recorded MACEs. Multivariate logistic regression analysis was performed to determine independent predictors of MACEs. The area under of receiver operating characteristic (ROC) curve was used to evaluated evaluate the diagnostic performance of CT-FFR, CDI, and a combination of the two. Results All the vessel-specific data were from LAD. 150 patients were analysed. 55 (37%) patients experienced MACEs during follow-up. Patients with CT-FFR ≤ 0.8 had higher percentage of MACEs compared with CT-FFR > 0.8 (56.3% vs.7.3%, p < 0.05). Patients’ CDI was significantly decreased in MACEs group compared with non-MACEs group (p < 0.05). Multivariate analysis revealed that diabetes (p = 0.025), triglyceride (p = 0.015), CT-FFR ≤ 0.80 (p = 0.038), and CDI (p < 0.001) are independent predictors of MACEs. According to ROC curve analysis, CT-FFR combined CDI showed incremental diagnostic performance over CT-FFR alone for prediction of MACEs (AUC = 0.831 vs. 0.656, p = 0.0002). Conclusion Our study provides initial evidence that combining CDI with CT-FFR shows incremental discriminatory power for MACEs over CT-FFR alone, independent of clinical risk factors. Diabetes and triglyceride are also associated with MACEs.

On-site CT-derived cFFR in patients with suspected coronary artery disease: Feasibility on a 128-row CT scanner in everyday clinical practice

“…Diabetes and hypercholesteremia are known risk factors for the development of CAD and damage to the small vessels in particular. These results are in line with the study by Zhu X. et al in 2022, who showed that the percentage of patients with a history of diabetes is higher in subgroups with major cardiac events (MACE) (70.9 % vs. 66.3 %, p < 0.05) 31 . Xue Y et al showed that diabetes has no negative impact on the diagnostic accuracy of machine learning–based C FFR 32 .…”

Artificial intelligence-assisted measurements of coronary computed tomography angiography parameters such as stenosis, flow reserve, and fat attenuation for predicting major adverse cardiac events in patients with coronary arterial disease

“…The measurement location was manually selected at a point 2-3 cm distal to the narrowest part of the plaque (Figure 3) [31]. When CT-FFR values were ≤ 0.8, the case was considered positive and associated with a high risk for MACE [32]. FAI values and the volume of peri-coronary adipose tissue (PCAT) were quantified using the platform's Shukun-FAI (version 1.3) software [33].…”