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Siogkas PK, Lakkas L, Sakellarios AI, Rigas G, Kyriakidis S, Stefanou KA, Anagnostopoulos CD, Clemente A, Rocchiccioli S, Pelosi G, Parodi O, Papafaklis MI, Naka KK, Michalis LK, Neglia D, Fotiadis DI. SmartFFR, a New Functional Index of Coronary Stenosis: Comparison With Invasive FFR Data. Front Cardiovasc Med 2021; 8:714471. [PMID: 34490377 PMCID: PMC8418116 DOI: 10.3389/fcvm.2021.714471] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 07/27/2021] [Indexed: 12/22/2022] Open
Abstract
Aims: In this study, we evaluate the efficacy of SmartFFR, a new functional index of coronary stenosis severity compared with gold standard invasive measurement of fractional flow reserve (FFR). We also assess the influence of the type of simulation employed on smartFFR (i.e. Fluid Structure Interaction vs. rigid wall assumption). Methods and Results: In a dataset of 167 patients undergoing either computed tomography coronary angiography (CTCA) and invasive coronary angiography or only invasive coronary angiography (ICA), as well as invasive FFR measurement, SmartFFR was computed after the 3D reconstruction of the vessels of interest and the subsequent blood flow simulations. 202 vessels were analyzed with a mean total computational time of seven minutes. SmartFFR was used to process all models reconstructed by either method. The mean FFR value of the examined dataset was 0.846 ± 0.089 with 95% CI for the mean of 0.833-0.858, whereas the mean SmartFFR value was 0.853 ± 0.095 with 95% CI for the mean of 0.84-0.866. SmartFFR was significantly correlated with invasive FFR values (RCCTA = 0.86, p CCTA < 0.0001, RICA = 0.84, p ICA < 0.0001, R overall = 0.833, p overall < 0.0001), showing good agreement as depicted by the Bland-Altman method of analysis. The optimal SmartFFR threshold to diagnose ischemia was ≤0.83 for the overall dataset, ≤0.83 for the CTCA-derived dataset and ≤0.81 for the ICA-derived dataset, as defined by a ROC analysis (AUCoverall = 0.956, p < 0.001, AUCICA = 0.975, p < 0.001, AUCCCTA = 0.952, p < 0.001). Conclusion: SmartFFR is a fast and accurate on-site index of hemodynamic significance of coronary stenosis both at single coronary segment and at two or more branches level simultaneously, which can be applied to all CTCA or ICA sequences of acceptable quality.
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Affiliation(s)
- Panagiotis K Siogkas
- Biomedical Research Institute, Foundation for Research and Technology Hellas, Ioannina, Greece.,Materials Science and Engineering, University of Ioannina, Ioannina, Greece
| | - Lampros Lakkas
- Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Antonis I Sakellarios
- Biomedical Research Institute, Foundation for Research and Technology Hellas, Ioannina, Greece
| | - George Rigas
- Biomedical Research Institute, Foundation for Research and Technology Hellas, Ioannina, Greece
| | - Savvas Kyriakidis
- Biomedical Research Institute, Foundation for Research and Technology Hellas, Ioannina, Greece
| | - Kostas A Stefanou
- Biomedical Research Institute, Foundation for Research and Technology Hellas, Ioannina, Greece
| | - Constantinos D Anagnostopoulos
- PET-CT Department & Preclinical Imaging Unit, Center for Experimental Surgery, Clinical & Translational Research, Biomedical Research Foundation Academy of Athens, Athens, Greece
| | - Alberto Clemente
- Fondazione Toscana G. Monasterio and Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Silvia Rocchiccioli
- Fondazione Toscana G. Monasterio and Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Gualtiero Pelosi
- Fondazione Toscana G. Monasterio and Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Oberdan Parodi
- Fondazione Toscana G. Monasterio and Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Pisa, Italy.,Institute of Clinical Physiology, CNR, Pisa, Italy
| | - Michail I Papafaklis
- Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Katerina K Naka
- Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Lampros K Michalis
- Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Danilo Neglia
- Fondazione Toscana G. Monasterio and Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Pisa, Italy
| | - Dimitrios I Fotiadis
- Biomedical Research Institute, Foundation for Research and Technology Hellas, Ioannina, Greece.,Materials Science and Engineering, University of Ioannina, Ioannina, Greece
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