Noninvasive Assessment of the Fractional Flow Reserve with the CT FFRc 1D Method: Final Results of a Pilot Study
Daria Gognieva,
Yulia Mitina,
Timur Gamilov,
Roman Pryamonosov,
Yuriy Vasilevskii,
Sergey Simakov,
Fuyou Liang,
Sergey Ternovoy,
Natalya Serova,
Ekaterina Tebenkova,
Valentin Sinitsyn,
Ekaterina Pershina,
Sergey Abugov,
Gaik Mardanian,
Narek Zakarian,
Vardan Kirakosian,
Vladimir Betelin,
Dmitry Shchekochikhin,
Abram Syrkin,
Philippe Kopylov
Affiliations
Daria Gognieva
Department of Cardiology, Functional and Ultrasound Diagnostics of N.V. Sklifosovsky Institute for Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Yulia Mitina
Department of Physiology, School of Biomedical Sciences; University of Melbourne, Melbourne
Timur Gamilov
Laboratory of Mathematical Modeling in Biomedicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Roman Pryamonosov
Laboratory of Mathematical Modeling in Biomedicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Yuriy Vasilevskii
Laboratory of Mathematical Modeling in Biomedicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Sergey Simakov
Laboratory of Mathematical Modeling in Biomedicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Fuyou Liang
Laboratory of Mathematical Modeling in Biomedicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, RU; Shanghai Jiao Tong University, Shanghai
Sergey Ternovoy
Department of Radiology and Radiotherapy of N.V. Sklifosovsky Institute for Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Natalya Serova
Department of Radiology and Radiotherapy of N.V. Sklifosovsky Institute for Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Ekaterina Tebenkova
Department of Radiology and Radiotherapy of N.V. Sklifosovsky Institute for Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Valentin Sinitsyn
Department of Radiation Diagnostics and Therapy, Faculty of Fundamental Medicine, M.V. Lomonosov Moscow State University, Moscow
Ekaterina Pershina
N.I. Pirogov City Clinical Hospital № 1, Moscow
Sergey Abugov
Department of endovascular diagnostic and treatment, Russian Medical Academy of Continuous Professional Education, Moscow
Gaik Mardanian
B.V. Petrovsky Russian Research Center of Surgery, Moscow
Narek Zakarian
Clinical hospital № 1, Moscow
Vardan Kirakosian
Clinical hospital № 1, Moscow
Vladimir Betelin
Scientific Research Institute of Systematic Research, RAS, Moscow
Dmitry Shchekochikhin
Department of Cardiology, Functional and Ultrasound Diagnostics of N.V. Sklifosovsky Institute for Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Abram Syrkin
Department of Cardiology, Functional and Ultrasound Diagnostics of N.V. Sklifosovsky Institute for Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Philippe Kopylov
Department of Cardiology, Functional and Ultrasound Diagnostics of N.V. Sklifosovsky Institute for Clinical Medicine, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow
Background:Until recently, Russia did not utilize noninvasive fractional flow reserve (FFR) assessment. We developed an automated algorithm for noninvasive assessment of FFR based on a one-dimensional (1D) mathematical modeling. Objective:The research aims to evaluate the diagnostic accuracy of this algorithm. Methods:The study enrolled 80 patients: 16 of them underwent 64-slice computed tomography – included retrospectively, 64 – prospectively, with a 640-slice CT scan. Specialists processed CT images and evaluated noninvasive FFR. Ischemia was confirmed if FFR < 0.80 and disproved if FFR ≥ 0.80. The prospective group of patients was hospitalized for invasive FFR assessment as a reference standard. If ischemic, patients underwent stent implantation. In the retrospective group, patients already had invasive FFR values. Statistical analysis was performed using GraphPad Prism 8. We compared two methods using a Bland–Altman plot and per-vessel ROC curve analysis. Considering the abnormality of distribution by the Kolmogorov-Smirnov test, we have used Spearman’s rank correlation coefficient. Results:During data processing, three patients of the retrospective and 46 patients of the prospective group were excluded. The sensitivity of our method was 66.67% (95% CI: 46.71–82.03); the specificity was 78.95% (95% CI: 56.67–91.49), p = 0.0052, in the per-vessel analysis. In per-patient analysis, the sensitivity was 69.57% (95% CI: 49.13–84.40); the specificity was 87.50% (95% CI: 52.91–99.36), p = 0.0109. The area under the ROC curve in the per-vessel analysis was 77.52% (95% CI: 66.97–88.08), p < 0.0001. Conclusion:The obtained indices of sensitivity, specificity, PPV, and NPV are, in general, comparable to those in other studies. Moreover, the noninvasive values of FFR yielded a high correlation coefficient with the invasive values. However, the AUC was not high enough, 77.52 (95% CI: 66.97–88.08), p < 0.0001. The discrepancy is probably attributed to the initial data heterogeneity and low statistical power.
