Literature DB >> 30654888

Comparison of Coronary Computed Tomography Angiography, Fractional Flow Reserve, and Perfusion Imaging for Ischemia Diagnosis.

Roel S Driessen1, Ibrahim Danad1, Wijnand J Stuijfzand1, Pieter G Raijmakers2, Stefan P Schumacher1, Pepijn A van Diemen1, Jonathon A Leipsic3, Juhani Knuuti4, S Richard Underwood5, Peter M van de Ven6, Albert C van Rossum1, Charles A Taylor7, Paul Knaapen8.   

Abstract

BACKGROUND: Fractional flow reserve (FFR) computation from coronary computed tomography angiography (CTA) datasets (FFRCT) has emerged as a promising noninvasive test to assess hemodynamic severity of coronary artery disease (CAD), but has not yet been compared with traditional functional imaging.
OBJECTIVES: The purpose of this study was to evaluate the diagnostic performance of FFRCT and compare it with coronary CTA, single-photon emission computed tomography (SPECT), and positron emission tomography (PET) for ischemia diagnosis.
METHODS: This subanalysis involved 208 prospectively included patients with suspected stable CAD, who underwent 256-slice coronary CTA, 99mTc-tetrofosmin SPECT, [15O]H2O PET, and routine 3-vessel invasive FFR measurements. FFRCT values were retrospectively derived from the coronary CTA images. Images from each modality were interpreted by core laboratories, and their diagnostic performances were compared using invasively measured FFR ≤0.80 as the reference standard.
RESULTS: In total, 505 of 612 (83%) vessels could be evaluated with FFRCT. FFRCT showed a diagnostic accuracy, sensitivity, and specificity of 87%, 90%, and 86% on a per-vessel basis and 78%, 96%, and 63% on a per-patient basis, respectively. Area under the receiver-operating characteristic curve (AUC) for identification of ischemia-causing lesions was significantly greater for FFRCT (0.94 and 0.92) in comparison with coronary CTA (0.83 and 0.81; p < 0.01 for both) and SPECT (0.70 and 0.75; p < 0.01 for both), on a per-vessel and -patient level, respectively. FFRCT also outperformed PET on a per-vessel basis (AUC 0.87; p < 0.01), but not on a per-patient basis (AUC 0.91; p = 0.56). In the intention-to-diagnose analysis, PET showed the highest per-patient and -vessel AUC followed by FFRCT (0.86 vs. 0.83; p = 0.157; and 0.90 vs. 0.79; p = 0.005, respectively).
CONCLUSIONS: In this study, FFRCT showed higher diagnostic performance than standard coronary CTA, SPECT, and PET for vessel-specific ischemia, provided coronary CTA images were evaluable by FFRCT, whereas PET had a favorable performance in per-patient and intention-to-diagnose analysis. Still, in patients in whom 3-vessel FFRCT could be analyzed, FFRCT holds clinical potential to provide anatomic and hemodynamic significance of coronary lesions.
Copyright © 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  coronary artery disease; coronary computed tomography angiography; fractional flow reserve; myocardial perfusion imaging

Mesh:

Year:  2019        PMID: 30654888     DOI: 10.1016/j.jacc.2018.10.056

Source DB:  PubMed          Journal:  J Am Coll Cardiol        ISSN: 0735-1097            Impact factor:   24.094


  57 in total

1.  Combining anatomy and physiology: New angiography-based and computed tomography coronary angiography-derived fractional flow reserve indices.

Authors:  Mariusz Tomaniak; Patrick W Serruys
Journal:  Cardiol J       Date:  2020       Impact factor: 2.737

2.  Non-invasive fractional flow reserve derived from coronary computed tomography angiography in patients with acute chest pain: Subgroup analysis of the ROMICAT II trial.

Authors:  Maros Ferencik; Michael T Lu; Thomas Mayrhofer; Stefan B Puchner; Ting Liu; Pal Maurovich-Horvat; Khristine Ghemigian; Alexander Ivanov; Elizabeth Adami; John T Nagurney; Pamela K Woodard; Quynh A Truong; James E Udelson; Udo Hoffmann
Journal:  J Cardiovasc Comput Tomogr       Date:  2019-05-15

3.  Machine learning-based advances in coronary computed tomography angiography.

Authors:  Mina M Benjamin; Mark G Rabbat
Journal:  Quant Imaging Med Surg       Date:  2021-06

4.  Exercise electrocardiography and computed tomography coronary angiography: use of combined functional and anatomical testing in stable angina pectoris.

Authors:  Stella Kyung; Mina M Benjamin; Mark Rabbat
Journal:  Quant Imaging Med Surg       Date:  2020-11

Review 5.  Physiological Assessment of Coronary Lesions in 2020.

Authors:  Mohsin Chowdhury; Eric A Osborn
Journal:  Curr Treat Options Cardiovasc Med       Date:  2020-01-15

Review 6.  Artificial Intelligence in Cardiovascular Imaging for Risk Stratification in Coronary Artery Disease.

Authors:  Andrew Lin; Márton Kolossváry; Manish Motwani; Ivana Išgum; Pál Maurovich-Horvat; Piotr J Slomka; Damini Dey
Journal:  Radiol Cardiothorac Imaging       Date:  2021-02-25

Review 7.  Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning.

Authors:  Joyce Peper; Dominika Suchá; Martin Swaans; Tim Leiner
Journal:  Br J Radiol       Date:  2020-08-12       Impact factor: 3.039

Review 8.  Risk stratification of coronary plaques using physiologic characteristics by CCTA: Focus on shear stress.

Authors:  Habib Samady; David S Molony; Ahmet U Coskun; Anubodh S Varshney; Bernard De Bruyne; Peter H Stone
Journal:  J Cardiovasc Comput Tomogr       Date:  2019-12-04

9.  Impaired Coronary Blood Flow in Patients with Psoriasis: Findings from an Observational Cohort Study.

Authors:  Domingo E Uceda; Amit K Dey; Sundus S Lateef; Khaled Abdelrahman; Milena Aksentijevich; Aarthi S Reddy; Harry Choi; Justin A Rodante; Martin P Playford; David A Bluemke; Wunan Zhou; Marcus Y Chen; Joel M Gelfand; Nehal N Mehta
Journal:  J Invest Dermatol       Date:  2020-10-01       Impact factor: 8.551

Review 10.  Coronary Computed Tomography Angiography From Clinical Uses to Emerging Technologies: JACC State-of-the-Art Review.

Authors:  Khaled M Abdelrahman; Marcus Y Chen; Amit K Dey; Renu Virmani; Aloke V Finn; Ramzi Y Khamis; Andrew D Choi; James K Min; Michelle C Williams; Andrew J Buckler; Charles A Taylor; Campbell Rogers; Habib Samady; Charalambos Antoniades; Leslee J Shaw; Matthew J Budoff; Udo Hoffmann; Ron Blankstein; Jagat Narula; Nehal N Mehta
Journal:  J Am Coll Cardiol       Date:  2020-09-08       Impact factor: 24.094

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