Relevance of anatomical, plaque, and hemodynamic characteristics of non-obstructive coronary lesions in the prediction of risk for acute coronary syndrome.

Published

Journal Article

OBJECTIVES: We explored the anatomical, plaque, and hemodynamic characteristics of high-risk non-obstructive coronary lesions that caused acute coronary syndrome (ACS). METHODS: From the EMERALD study which included ACS patients with available coronary CT angiography (CCTA) before the ACS, non-obstructive lesions (percent diameter stenosis < 50%) were selected. CCTA images were analyzed for lesion characteristics by independent CCTA and computational fluid dynamics core laboratories. The relative importance of each characteristic was assessed by information gain. RESULTS: Of the 132 lesions, 24 were the culprit for ACS. The culprit lesions showed a larger change in FFRCT across the lesion (ΔFFRCT) than non-culprit lesions (0.08 ± 0.07 vs 0.05 ± 0.05, p = 0.012). ΔFFRCT showed the highest information gain (0.051, 95% confidence interval [CI] 0.050-0.052), followed by low-attenuation plaque (0.028, 95% CI 0.027-0.029) and plaque volume (0.023, 95% CI 0.022-0.024). Lesions with higher ΔFFRCT or low-attenuation plaque showed an increased risk of ACS (hazard ratio [HR] 3.25, 95% CI 1.31-8.04, p = 0.010 for ΔFFRCT; HR 2.60, 95% CI 1.36-4.95, p = 0.004 for low-attenuation plaque). The prediction model including ΔFFRCT, low-attenuation plaque and plaque volume showed the highest ability in ACS prediction (AUC 0.725, 95% CI 0.724-0.727). CONCLUSION: Non-obstructive lesions with higher ΔFFRCT or low-attenuation plaque showed a higher risk of ACS. The integration of anatomical, plaque, and hemodynamic characteristics can improve the noninvasive prediction of ACS risk in non-obstructive lesions. KEY POINTS: • Change in FFR CT across the lesion (ΔFFR CT ) was the most important predictor of ACS risk in non-obstructive lesions. • Non-obstructive lesions with higher ΔFFR CT or low-attenuation plaque were associated with a higher risk of ACS. • The integration of anatomical, plaque, and hemodynamic characteristics can improve the noninvasive prediction of ACS risk.

Full Text

Duke Authors

Cited Authors

  • Park, J; Lee, JM; Koo, B-K; Choi, G; Hwang, D; Rhee, T-M; Yang, S; Park, J; Zhang, J; Kim, K-J; Tong, Y; Doh, J-H; Nam, C-W; Shin, E-S; Cho, Y-S; Chun, EJ; Choi, J-H; Norgaard, BL; Christiansen, EH; Niemen, K; Otake, H; Penicka, M; de Bruyne, B; Kubo, T; Akasaka, T; Narula, J; Douglas, PS; Taylor, CA

Published Date

  • November 2019

Published In

Volume / Issue

  • 29 / 11

Start / End Page

  • 6119 - 6128

PubMed ID

  • 31025066

Pubmed Central ID

  • 31025066

Electronic International Standard Serial Number (EISSN)

  • 1432-1084

Digital Object Identifier (DOI)

  • 10.1007/s00330-019-06221-9

Language

  • eng

Conference Location

  • Germany