Advanced Computed Tomographic Anatomical and Morphometric Plaque Analysis for Prediction of Fractional Flow Reserve in Intermediate Coronary Lesions
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Objective: To determine the application of advanced coronary computed tomography angiography (CCTA) plaque analysis for predicting invasive fractional flow reserve (FFR) in intermediate coronary lesions.
Methods: Sixty-one patients with 71 single intermediate coronary lesions (≥ 50-80% stenosis) on CCTA prospectively underwent coronary angiography and FFR. Advanced anatomical and morphometric plaque analysis was performed based on CCTA data set to determine optimal criteria for significant flow impairment. A significant stenosis was defined as FFR ≤ 0.80.
Results: FFR averaged 0.85 ± 0.09, and 19 lesions (27%) were functionally significant. FFR correlated with minimum lumen area (MLA) (r=0.456, p<0.001), minimum lumen diameter (MLD) (r=0.326, p=0.006), reference lumen diameter (RLD) (r=0.245, p=0.039), plaque burden (r=-0.313, p=0.008), lumen area stenosis (r=-0.305, p=0.01), lesion length (r=-0.692, p<0.001), and plaque volume (r=-0.668, p<0.001). There was no relationship between FFR and CCTA morphometric plaque parameters. By multivariate analysis the independent predictors of FFR were lesion length (beta=-0.581, p<0.001), MLA (beta=0.360, p=0.041), and RLD (beta=-0.255, p=0.036). The optimal cutoffs for lesion length, MLA, MLD, RLD, and lumen area stenosis were >18.5mm, ≤ 3.0mm(2), ≤ 2.1mm, ≤ 3.2mm, and >69%, respectively (max. sensitivity: 100% for MLA, max. specificity: 79% for lumen area stenosis).
Conclusions: CCTA predictors for FFR support the mathematical relationship between stenosis pressure drop and coronary flow. CCTA could prove to be a useful rule-out test for significant hemodynamic effects of intermediate coronary stenoses.
Mergen V, Eberhard M, Manka R, Euler A, Alkadhi H Front Cardiovasc Med. 2022; 9:981012.
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Hamon M, Geindreau D, Guittet L, Bauters C, Hamon M Eur Radiol. 2019; 29(6):3044-3061.
PMID: 30617482 DOI: 10.1007/s00330-018-5919-8.
Pagiatakis C, Tardif J, LAllier P, Mongrain R Med Biol Eng Comput. 2017; 55(12):2079-2095.
PMID: 28500478 DOI: 10.1007/s11517-017-1653-7.
Cui Y, Zeng W, Yu J, Lu J, Hu Y, Diao N PLoS One. 2017; 12(3):e0174352.
PMID: 28346530 PMC: 5367806. DOI: 10.1371/journal.pone.0174352.
Chu M, Dai N, Yang J, Westra J, Tu S Int J Cardiovasc Imaging. 2017; 33(7):975-990.
PMID: 28265791 DOI: 10.1007/s10554-017-1085-3.