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This study sought to evaluate a novel approach for automatic coregistration of optical coherence tomography (OCT) and coronary angiography. Lumen diameters and side branches from both coronary angiography and OCT were used to create 2 feature sets. Subsequently, a 2-step coregistration approach was performed on the feature sets for matching of each OCT cross section on the angiographic centerline. For validation, all side branches with ≥1.0 mm diameter were identified and used as paired fiduciary landmarks. Geographical error was defined as the distance between the automatically coregistered and the true-paired landmarks. Altogether 212 vessels from 181 patients were analyzed. Mismatch of coronary angiography and OCT occurred in 64 of 1,530 reference landmarks. Median geographical error was 0.32 (interquartile range: 0.00-0.56) mm. The mean time for coregistration was 20.69 ± 1.07 seconds. In conclusion, fast and automatic coregistration of OCT and angiography using a single standard angiographic loop is feasible and accurate.

Background: The prognostic value of whole vessel plaque quantification has not been fully understood. Objectives: We aimed to investigate the clinical relevance of whole vessel plaque quantification on coronary computed tomography angiography. Methods: In a total of 1,013 vessels with fractional flow reserve (FFR) measurement and available coronary computed tomography angiography, high-risk plaque characteristics (HRPC) included minimum lumen area 0.80, the number of HRVC was significantly associated with the risk of VOCO (HR: 2.54; 95% CI: 1.77-3.64) and enhanced the predictability for VOCO of % diameter stenosis and the number of HRPC (P < 0.001). In a landmark analysis at 2 years, the number of HRVC showed sustained prognostic implications beyond 2 years, but the number of HRPC did not. Conclusions: Whole vessel plaque quantification can provide incremental predictability for low FFR and additive prognostic value in deferred vessels with high FFR over anatomical severity and lesion plaque characteristics. (CCTA-FFR Registry for Risk Prediction; NCT04037163)