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Aim.To evaluate the diagnostic accuracy of a noninvasive method of fractional flow reserve (FFR) assessment based on a one-dimensional hemodynamic model build on data obtained from the coronary computed tomography angiography (CCTA).Material and methods.The study enrolled 57 patients: 16 of them underwent 64-slice computed tomography — included retrospectively, 34 — prospectively, with a 640-slice CT scan. Specialists from the Laboratory of Mathematical Modeling processed CT images and evaluated noninvasive FFR. Ischemia was confirmed if FFR Results.During data processing, 3 patients of the retrospective and 34 patients of the prospective group were excluded from the study. The sensitivity of our method was 90,91% (95% CI; 58,72-99,77), specificity — 86,67% (95% CI; 59,54-98,34), PConclusion.Our method has quite a high accuracy and can be successfully used in clinical practice in order to enhance the diagnostic efficiency of the CCTA.

Aim. Comparative analysis of the diagnostic effectiveness of onedimensional (1-D) and three-dimensional (3-D) non-invasive methods for coronary fractional flow reserve (FFR) assessment based on the coronary computed tomography angiography (CCTA). Material and methods . We carried out a retrospective analysis of CCTA data for 13 patients (men — 9, mean age — 61,07±9,73). In the original research, coronary FFR of those patients was evaluated using the original 3-D HeartFlow® Analysis followed by a standard invasive FFR assessment. We estimated coronary FFR using the 1-D algorithm of the Laboratory of Mathematical Modeling (Sechenov University) and compared the diagnostic effectiveness of these methods. Results. In per-vessel analysis, the sensitivity and specificity of the 3-D approach were 90,91% (95% confidence interval (CI) 62,26-99,53) and 20% (95% CI 0,01026-62,46, p>0,9999), respectively; in per-patient analysis — 90% (95% CI 59,58-99,49) and 0% (95% CI 0-56,15, p>0,9999), respectively; area under the ROC curve was 93,75% (95% CI 80,26-100), p=2,0431e-10. For the 1-D approach, the same parameters in per-patient analysis were 88,89 % (95% CI 56,50-99,43) and 25% (95% CI 0,01282-69,94, p>0,9999), respectively; in per-vessel analysis — 100% (95% CI 72,25-100) and 33,33% (95% CI 0,05923-70, p=0,1250), respectively; area under the ROC curve was 84,54% (95% CI 63,93-100), p=0,001. Spearman’s rank correlation coefficient between the 3-D and 1-D techniques was 0,7326 (95% CI 0,35810,9041), p=0,0017. Conclusion. Although we have obtained lower values of area under the ROC curve, the sensitivity and specificity of experimental approach, as well as the correlation coefficient between models were rather high. However, further studies with higher statistical power are required.