Objective: This study aimed to establish a new scoring system that includes histological quantitative features derived from coronary computed tomographic angiography (CCTA) to predict the efficiency of chronic total occlusion percutaneous coronary intervention (CTO-PCI).
Methods: This study analyzed clinical, morphological, and histological characteristics of 207 CTO lesions in 201 patients (mean age 60.0 [52.0-65.0] years, 85% male), which were recruited from two centers. The primary endpoint was a guidewire successfully crossing the lesions within 30 m. The new predictive model was generated by factors that were determined by multivariate analysis. The CCTA plaque (CTAP) score that included a quantitative plaque characteristic was developed by assigning an appropriate integer score to each independent predictor, then summing all points. In addition, the CTAP score was compared with other predictive scores based on CCTA.
Results: The endpoint was achieved in 63% of the lesions. The independent predictors included previous CTO-PCI failure, the proximal blunt stump, proximal side branch, distal side branch, occluded segment bending > 45°, and high-density plaque volume (fibrous volume + calcified volume) ≥ 19.9 mm3. As the score increased from 0 to 5, the success rate of the guidewire crossing within 30 m decreased from 96 to 0%. Comparing the CTAP score with other predictive scores, the CTAP score showed the highest discriminant power (c-statistic = 0.81 versus 0.73-0.77, p value 0.02-0.07). The CTAP score showed similar results for procedural success.
Conclusion: The CTAP score efficiently predicted the guidewire crossing efficiency and procedural success.
Key points: • An increase in high-density plaque volume (fibrous + dense calcium) was more probable to reduce the efficiency of crossing and lead to procedural failure. • The new prediction scoring system with the addition of the quantitative characteristics of plaques had an improved predictive ability compared with the traditional prediction scoring system.
Keywords: Chronic total occlusion; Coronary computed tomographic angiography; Plaque quantitative analysis; Predicting.
© 2022. The Author(s).