Predictive Value of DEEPVESSEL-Fractional Flow Reserve and Quantitative Plaque Analysis based on Coronary CT Angiography for Major Adverse Cardiac Events

Aim To investigate the predictive value of the combination of DEEPVESSEL-fractional flow reserve (DVFFR) and quantitative plaque analysis using coronary computed tomographic angiography (CCTA) for major adverse cardiac events (MACE). Method In this retrospective study, data from 69 vessels from 58 consecutive patients were collected. These patients who underwent coronary angiography (CAG) with DVFFR were divided into MACE-positive and MACE-negative groups. DVFFR measurements were obtained from CCTA images acquired before CAG, and an FFR or DVFFR value ≤ 0.80 was considered haemodynamically significant. CCTA images were analysed quantitatively using automated software to obtain the following indices: total plaque volume (TPV) and burden (TPB), calcified plaque volume (CPV) and burden (CPB), non-calcified plaque volume (NCPV) and burden (NCPB), low-attenuation plaque (LAP), minimum lumen area (MLA), stenosis grade (SG) and lesion length (LL). Univariate and multivariate logistic regression, correlation, and receiver operating characteristic (ROC) analyses were used for statistical analysis. Results DVFFR was highly correlated with invasive FFR (R=0.728), and the Bland–Altman plot showed good agreement between DVFFR and FFR (95% CI: –0.109–0.087) on a per-vessel level. DVFFR showed a high diagnostic performance in identifying abnormal haemodynamic vessels, with an area under the ROC curve (AUC) of 0.984. In multivariate analysis, the following biomarkers were predictors of MACE: DVFFR ≤ 0.8, SG, TPB, NCPB, and LL values. The combination of the above independent risk factors yielded the most valuable prediction for MACE (AUC:0.888). Conclusions DVFFR was highly correlated with FFR with satisfactory diagnostic accuracy. DVFFR, together with plaque analysis indices, yielded valuable predictions for MACE.