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PMID: 30324382 Published · ppublish English Journal Article

Noninvasive CT-based hemodynamic assessment of coronary lesions derived from fast computational analysis: a comparison against fractional flow reserve.

European radiology ·Vol. 29 ·No. 4 ·2019-04-00 ·页码 2117-2126

Siogkas PK, Anagnostopoulos CD, Liga R, Exarchos TP, Sakellarios AI, Rigas G, Scholte AJHA, Papafaklis MI, Loggitsi D, Pelosi G, Parodi O, Maaniitty T, Michalis LK, Knuuti J, Neglia D, Fotiadis DI

Abstract

Application of computational fluid dynamics (CFD) to three-dimensional CTCA datasets has been shown to provide accurate assessment of the hemodynamic significance of a coronary lesion. We aim to test the feasibility of calculating a novel CTCA-based virtual functional assessment index (vFAI) of coronary stenoses > 30% and ≤ 90% by using an automated in-house-developed software and to evaluate its efficacy as compared to the invasively measured fractional flow reserve (FFR). In 63 patients with chest pain symptoms and intermediate (20-90%) pre-test likelihood of coronary artery disease undergoing CTCA and invasive coronary angiography with FFR measurement, vFAI calculations were performed after 3D reconstruction of the coronary vessels and flow simulations using the finite element method. A total of 74 vessels were analyzed. Mean CTCA processing time was 25(± 10) min. There was a strong correlation between vFAI and FFR, (R = 0.93, p < 0.001) and a very good agreement between the two parameters by the Bland-Altman method of analysis. The mean difference of measurements from the two methods was 0.03 (SD = 0.033), indicating a small systematic overestimation of the FFR by vFAI. Using a receiver-operating characteristic curve analysis, the optimal vFAI cutoff value for identifying an FFR threshold of ≤ 0.8 was ≤ 0.82 (95% CI 0.81 to 0.88). vFAI can be effectively derived from the application of computational fluid dynamics to three-dimensional CTCA datasets. In patients with coronary stenosis severity > 30% and ≤ 90%, vFAI performs well against FFR and may efficiently distinguish between hemodynamically significant from non-significant lesions. Virtual functional assessment index (vFAI) can be effectively derived from 3D CTCA datasets. In patients with coronary stenoses severity > 30% and ≤ 90%, vFAI performs well against FFR. vFAI may efficiently distinguish between functionally significant from non-significant lesions.

Keywords
Computed tomography angiography Coronary artery disease Myocardial fractional flow reserve
MeSH 主题词
Aged Coronary Angiography/methods Coronary Artery Disease/diagnosis,physiopathology Coronary Vessels/diagnostic imaging,physiopathology Female Fractional Flow Reserve, Myocardial/physiology Hemodynamics/physiology Humans Imaging, Three-Dimensional Male Middle Aged ROC Curve Tomography, X-Ray Computed/methods
作者与单位
共 16 位作者,点击展开单位 / ORCID
Siogkas Panagiotis K
Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece.
Anagnostopoulos Constantinos D
Center for Experimental Surgery, Clinical and Translational Research, Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou St., 115 27, Athens, Greece. [email protected].
Liga Riccardo
Cardio-Thoracic and Vascular Department, University Hospital of Pisa, Pisa, Italy. | Department of Nuclear Medicine, University Hospital Zurich, Zürich, Switzerland.
Exarchos Themis P
Biomedical Research Institute - FORTH, GR 45110 Ioannina, Ioannina, Greece.
Sakellarios Antonis I
Biomedical Research Institute - FORTH, GR 45110 Ioannina, Ioannina, Greece.
Rigas George
Biomedical Research Institute - FORTH, GR 45110 Ioannina, Ioannina, Greece.
Scholte Arthur J H A
Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.
Papafaklis M I
Michaelideion Cardiac Center, Dept. of Cardiology in Medical School, University of Ioannina, 451 10, Ioannina, Greece.
Loggitsi Dimitra
CT & MRI Department Hygeia-Mitera Hospitals, Athens, Greece.
Pelosi Gualtiero
Fondazione Toscana G. Monasterio and CNR Institute of Clinical Physiology, Pisa, Italy.
Parodi Oberdan
Fondazione Toscana G. Monasterio and CNR Institute of Clinical Physiology, Pisa, Italy.
Maaniitty Teemu
Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland.
Michalis Lampros K
Michaelideion Cardiac Center, Dept. of Cardiology in Medical School, University of Ioannina, 451 10, Ioannina, Greece.
Knuuti Juhani
Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland.
Neglia Danilo
Fondazione Toscana G. Monasterio and CNR Institute of Clinical Physiology, Pisa, Italy.
Fotiadis Dimitrios I
Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece. | Biomedical Research Institute - FORTH, GR 45110 Ioannina, Ioannina, Greece. | Michaelideion Cardiac Center, Dept. of Cardiology in Medical School, University of Ioannina, 451 10, Ioannina, Greece.
Article Info
Journal
European radiology
Abbr.
Eur Radiol
ISSN
1432-1084
Corresponding email
Published
2019-04-00
电子出版
2018-00-15
页码
2117-2126
Language
English
Country/Region
Germany
NLM ID
9114774
Analysis Services
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