Non-invasive quantitative plaque analysis by coronary CT angiography in predicting coronary hemodynamic significance
2018
Objective
To evaluate the diagnostic performance of the automated quantitative analysis by coronary computed tomography angiography (CCTA) for lesion specific hemodynamic significance assessed by fractional flow reserve (FFR) .
Methods
One hundred and fifteen patients with one hundred and fifty-one vessels,who successively underwent invasive coronary angiography with evaluation of FFR(values≤0.8 were defined as lesion specific hemodynamically significant),were analyzed by coronary CT angiography. FFR≤0.80 was found in 54(35.76%) of the 151 vessels, which was divided into two groups (group of hemodynamically significant and group of hemodynamically non-significant). CCTA images were quantitatively analyzed with automated software to obtain the following index: minimal lumen diameter(MLD), maximum diameter stenosis(MDS%), minimal lumen area(MLA), maximum area stenosis(MAS%), lesion length(LL), total plaque volume(TPV), total plaque burden(TPB),calcified plaque volume(CPV),calcified plaque burden(CPB), non-calcified plaque volume(NCPV),non-calcified plaque burden(NCPB), lipid plaque volume(LPV), lipid plaque burden(LPB), fibrous plaque volume(FPV), fibrous plaque burden(FPB), napkin-ring sign(NRS), remodeling index(RI) and eccentric index(EI). Logistic regression and area under the receiver operating characteristics were used for statistical analysis.
Results
MDS% (65.04%±8.20%), MAS% (73.91%±7.58%), TPB(57.96%±11.17%), CPB[4.32%(0.11%, 5.34%)], LPB[14.89%(9.30%, 19.23%)], CPV[30.68 (0.29, 33.36)mm3], LPV[(81.72(33.92, 94.68)mm3]in the group with hemodynamic significance were larger than those in group with normal hemodynamic status[58.27%±9.50%, 64.83%±8.31%, 53.88%±11.77%, 2.05%(0.00%,3.42%), 11.83%(6.34%,16.8%), 12.53(0.00,13.24)mm3, 60.71(24.1,75.11)mm3, respectively], which was statistically significant(t=4.41,P 0.05).
Conclusion
Compared with diameter stenosis, area stenosis substantially improves the prediction of lesion specific hemodynamic significance.
Key words:
Coronary artery disease; Hemodynamics; Tomography, X-ray computed
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