Literature DB >> 25819194

Diagnostic accuracy and discrimination of ischemia by fractional flow reserve CT using a clinical use rule: results from the Determination of Fractional Flow Reserve by Anatomic Computed Tomographic Angiography study.

Angus G Thompson1, Rekha Raju2, Philipp Blanke2, Tae-Hyun Yang2, Giovanni Battista John Mancini3, Matthew J Budoff4, Bjarne L Norgaard5, James K Min6, Jonathon A Leipsic2.   

Abstract

BACKGROUND: Fractional flow reserve (FFR) is the gold standard for determining lesion-specific ischemia. Computed FFRCT derived from coronary CT angiography (coronary CTA) correlates well with invasive FFR and accurately differentiates between ischemia-producing and nonischemic lesions. The diagnostic performance of FFRCT when applied in a clinically relevant way to all vessels ≥ 2 mm in diameter stratified by sex and age has not been previously examined.
METHODS: Two hundred fifty-two patients and 407 vessels underwent coronary CTA, FFRCT, invasive coronary angiography, and invasive FFR. FFRCT and FFR ≤ 0.80 were considered ischemic, whereas CT stenosis ≥ 50% was considered obstructive. The diagnostic performance of FFRCT was assessed following a prespecified clinical use rule which included all vessels ≥ 2 mm in diameter, not just those assessed by invasive FFR measurements. Stenoses <30% were assigned an FFR of 0.90, and stenoses >90% were assigned an FFR of 0.50. Diagnostic performance of FFRCT was stratified by vessel diameter, sex, and age.
RESULTS: By FFR, ischemia was identified in 129 of 252 patients (51%) and in 151 of 407 vessels (31%). Mean age (± standard deviation) was 62.9 ± 9 years, and women were older (65.5 vs 61.9 years; P = .003). Per-patient diagnostic accuracy (83% vs 72%; P < .005) and specificity (54% vs 82%, P < .001) improved significantly after application of the clinical use tool. These were significantly improved over standard coronary CTA values before application of the clinical use rule. Discriminatory power of FFRCT also increased compared with baseline (area under the receiver operating characteristics curve [AUC]: 0.93 vs 0.81, P < .001). Diagnostic performance improved in both sexes with no significant differences between the sexes (AUC: 0.93 vs 0.90, P = .43). There were no differences in the discrimination of FFRCT after application of the clinical use rule when stratified by age ≥ 65 or <65 years (AUC: 0.95 vs 0.90, P = .10).
CONCLUSIONS: The diagnostic accuracy and discriminatory power of FFRCT improve significantly after the application of a clinical use rule which includes all clinically relevant vessels >2 mm in diameter. FFRCT has similar diagnostic accuracy and discriminatory power for ischemia detection in men and women irrespective of age using a cut point of 65 years. Crown
Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Computational fluid dynamics; Coronary CT angiography; Fractional flow reserve

Mesh:

Year:  2015        PMID: 25819194     DOI: 10.1016/j.jcct.2015.01.008

Source DB:  PubMed          Journal:  J Cardiovasc Comput Tomogr        ISSN: 1876-861X


  10 in total

Review 1.  Physiome approach for the analysis of vascular flow reserve in the heart and brain.

Authors:  Kyung Eun Lee; Ah-Jin Ryu; Eun-Seok Shin; Eun Bo Shim
Journal:  Pflugers Arch       Date:  2017-03-28       Impact factor: 3.657

2.  Myocardial perfusion with single-photon emission computed tomography, multidetector computed tomography, or neither?

Authors:  Paolo Raggi; G B John Mancini
Journal:  J Nucl Cardiol       Date:  2016-05-17       Impact factor: 5.952

3.  Fractional flow reserve based on computed tomography: an overview.

Authors:  Francesco Secchi; Marco Alì; Elena Faggiano; Paola Maria Cannaò; Marco Fedele; Silvia Tresoldi; Giovanni Di Leo; Ferdinando Auricchio; Francesco Sardanelli
Journal:  Eur Heart J Suppl       Date:  2016-04-29       Impact factor: 1.803

Review 4.  Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?

Authors:  Steven A Niederer; Nic P Smith
Journal:  J Physiol       Date:  2016-07-03       Impact factor: 5.182

5.  The transluminal attenuation gradient in coronary CT angiography for the detection of hemodynamically significant disease: can all arteries be treated equally?

Authors:  Shinichiro Fujimoto; Andreas A Giannopoulos; Kanako K Kumamaru; Rie Matsumori; Anji Tang; Etsuro Kato; Yuko Kawaguchi; Kazuhisa Takamura; Katsumi Miyauchi; Hiroyuki Daida; Frank J Rybicki; Dimitris Mitsouras
Journal:  Br J Radiol       Date:  2018-04-12       Impact factor: 3.039

Review 6.  Challenges in Diagnosis and Functional Assessment of Coronary Artery Disease in Patients With Severe Aortic Stenosis.

Authors:  Srdjan Aleksandric; Marko Banovic; Branko Beleslin
Journal:  Front Cardiovasc Med       Date:  2022-03-11

7.  Measurement of Plaque Characteristics Using Coronary Computed Tomography Angiography: Achieving High Interobserver Performance.

Authors:  G B John Mancini; Craig Kamimura; Eunice Yeoh; Arnold Ryomoto; C David Mazer
Journal:  CJC Open       Date:  2021-09-30

8.  Sex differences in machine learning computed tomography-derived fractional flow reserve.

Authors:  Mahmoud Al Rifai; Ahmed Ibrahim Ahmed; Yushui Han; Jean Michel Saad; Talal Alnabelsi; Faisal Nabi; Su Min Chang; Myra Cocker; Chris Schwemmer; Juan C Ramirez-Giraldo; William A Zoghbi; John J Mahmarian; Mouaz H Al-Mallah
Journal:  Sci Rep       Date:  2022-08-16       Impact factor: 4.996

9.  Simplified Models of Non-Invasive Fractional Flow Reserve Based on CT Images.

Authors:  Jun-Mei Zhang; Liang Zhong; Tong Luo; Aileen Mae Lomarda; Yunlong Huo; Jonathan Yap; Soo Teik Lim; Ru San Tan; Aaron Sung Lung Wong; Jack Wei Chieh Tan; Khung Keong Yeo; Jiang Ming Fam; Felix Yung Jih Keng; Min Wan; Boyang Su; Xiaodan Zhao; John Carson Allen; Ghassan S Kassab; Terrance Siang Jin Chua; Swee Yaw Tan
Journal:  PLoS One       Date:  2016-05-17       Impact factor: 3.240

10.  Validation of the diagnostic performance of 'HeartMedi V.1.0', a novel CT-derived fractional flow reserve measurement, for patients with coronary artery disease: a study protocol.

Authors:  Soo-Hyun Kim; Si-Hyuck Kang; Woo-Young Chung; Chang-Hwan Yoon; Sang-Don Park; Chang-Wook Nam; Ki-Hwan Kwon; Joon-Hyung Doh; Young-Sup Byun; Jang-Whan Bae; Tae-Jin Youn; In-Ho Chae
Journal:  BMJ Open       Date:  2020-07-20       Impact factor: 2.692

  10 in total

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