Literature DB >> 34295702

Design and rationale of randomized CT-PRECISION study.

Xu Dai1, Yarong Yu2, Lihua Yu1, Lei Zhang2, Jiayin Zhang2.   

Abstract

BACKGROUND: Coronary computed tomography angiography (CCTA) combined with dynamic CT myocardial perfusion imaging (CT-MPI) and CCTA combined with CT fractional flow reserve (CT-FFR) are both expected to be efficient one-stop shop imaging strategies to guide clinical management. The aim of the study is to determine which of these two methods has superiority in terms of guiding treatment in patients with intermediate to high pretest probability of coronary artery disease (CAD).
METHODS: CT-PRECISION (Computed Tomography myocardial PeRfusion imaging vErsus Computed tomography derived fractional flow reServe: impact ON guiding treatment and prognosis in patients with intermediate to high pretest probability of CAD) is a multicenter, prospective, open-label, randomized study to directly compare the clinical value of guiding treatment and prognostic discrimination of CCTA + dynamic CT-MPI strategy and CCTA + CT-FFR strategy in patients with intermediate to high pretest probability of CAD. Four hundred and twelve patients will be enrolled in this study and randomized to CCTA + dynamic CT-MPI arm and CCTA + CT-FFR arm. All patients will be followed up for at least 2 years. The primary endpoint is the rate of unnecessary invasive coronary angiography (ICA) within 90 days, which is defined as ICA without revascularization. The secondary endpoints will include: (I) a composite of major adverse cardiac events (MACE, defined as all-cause mortality, non-fatal myocardial infarction, rehospitalization due to aggravated angina symptoms, and late revascularization); (II) symptom change at 1 year; (III) the rate of late revascularization after CT examination; (IV) reclassification rate of CCTA + dynamic CT-MPI and CCTA + CT-FFR guided strategies compared with CCTA alone; (V) overall radiation dose, contrast media usage and medical cost. DISCUSSION: The study will provide valuable information about the optimal CT-based diagnostic strategy with regard to the clinical management of patients with intermediate to high pretest probability of CAD. TRIAL REGISTRATION: The study is registered at Chinese Clinical Trial Registry (ChiCTR) with the identifier number ChiCTR2000041102. The first enrollment is planned for January 2021. 2021 Cardiovascular Diagnosis and Therapy. All rights reserved.

Entities:  

Keywords:  Coronary artery disease (CAD); computed tomography angiography; fractional flow reserve (FFR); major adverse cardiac events (MACEs); myocardial perfusion imaging (MPI)

Year:  2021        PMID: 34295702      PMCID: PMC8261741          DOI: 10.21037/cdt-21-57

Source DB:  PubMed          Journal:  Cardiovasc Diagn Ther        ISSN: 2223-3652


  17 in total

Review 1.  Stress myocardial perfusion: imaging with multidetector CT.

Authors:  Alexia Rossi; Daphne Merkus; Ernst Klotz; Nico Mollet; Pim J de Feyter; Gabriel P Krestin
Journal:  Radiology       Date:  2014-01       Impact factor: 11.105

2.  1-Year Outcomes of FFRCT-Guided Care in Patients With Suspected Coronary Disease: The PLATFORM Study.

Authors:  Pamela S Douglas; Bernard De Bruyne; Gianluca Pontone; Manesh R Patel; Bjarne L Norgaard; Robert A Byrne; Nick Curzen; Ian Purcell; Matthias Gutberlet; Gilles Rioufol; Ulrich Hink; Herwig Walter Schuchlenz; Gudrun Feuchtner; Martine Gilard; Daniele Andreini; Jesper M Jensen; Martin Hadamitzky; Karen Chiswell; Derek Cyr; Alan Wilk; Furong Wang; Campbell Rogers; Mark A Hlatky
Journal:  J Am Coll Cardiol       Date:  2016-08-02       Impact factor: 24.094

3.  Prognostic Value and Risk Continuum of Noninvasive Fractional Flow Reserve Derived from Coronary CT Angiography.

Authors:  Abdul Rahman Ihdayhid; Bjarne L Norgaard; Sara Gaur; Jonathan Leipsic; Nitesh Nerlekar; Kazuhiro Osawa; Toru Miyoshi; Jesper M Jensen; Takeshi Kimura; Hiroki Shiomi; Andrejs Erglis; Sanda Jegere; Keith G Oldroyd; Hans Erik Botker; Sujith K Seneviratne; Stephan Achenbach; Brian S Ko
Journal:  Radiology       Date:  2019-06-11       Impact factor: 11.105

4.  2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes.

Authors:  Juhani Knuuti; William Wijns; Antti Saraste; Davide Capodanno; Emanuele Barbato; Christian Funck-Brentano; Eva Prescott; Robert F Storey; Christi Deaton; Thomas Cuisset; Stefan Agewall; Kenneth Dickstein; Thor Edvardsen; Javier Escaned; Bernard J Gersh; Pavel Svitil; Martine Gilard; David Hasdai; Robert Hatala; Felix Mahfoud; Josep Masip; Claudio Muneretto; Marco Valgimigli; Stephan Achenbach; Jeroen J Bax
Journal:  Eur Heart J       Date:  2020-01-14       Impact factor: 29.983

5.  Integrating CT Myocardial Perfusion and CT-FFR in the Work-Up of Coronary Artery Disease.

Authors:  Adriaan Coenen; Alexia Rossi; Marisa M Lubbers; Akira Kurata; Atsushi K Kono; Raluca G Chelu; Sabrina Segreto; Marcel L Dijkshoorn; Andrew Wragg; Robert-Jan M van Geuns; Francesca Pugliese; Koen Nieman
Journal:  JACC Cardiovasc Imaging       Date:  2017-01-18

6.  Diagnostic Accuracy of a Machine-Learning Approach to Coronary Computed Tomographic Angiography-Based Fractional Flow Reserve: Result From the MACHINE Consortium.

Authors:  Adriaan Coenen; Young-Hak Kim; Mariusz Kruk; Christian Tesche; Jakob De Geer; Akira Kurata; Marisa L Lubbers; Joost Daemen; Lucian Itu; Saikiran Rapaka; Puneet Sharma; Chris Schwemmer; Anders Persson; U Joseph Schoepf; Cezary Kepka; Dong Hyun Yang; Koen Nieman
Journal:  Circ Cardiovasc Imaging       Date:  2018-06       Impact factor: 7.792

7.  Dynamic myocardial CT perfusion imaging for evaluation of myocardial ischemia as determined by MR imaging.

Authors:  Fabian Bamberg; Roy P Marcus; Alexander Becker; Kristof Hildebrandt; Kerstin Bauner; Florian Schwarz; Martin Greif; Franz von Ziegler; Bernhard Bischoff; Hans-Christoph Becker; Thorsten R Johnson; Maximilian F Reiser; Konstantin Nikolaou; Daniel Theisen
Journal:  JACC Cardiovasc Imaging       Date:  2014-02-13

8.  Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling.

Authors:  Christian Tesche; Carlo N De Cecco; Stefan Baumann; Matthias Renker; Tindal W McLaurin; Taylor M Duguay; Richard R Bayer; Daniel H Steinberg; Katharine L Grant; Christian Canstein; Chris Schwemmer; Max Schoebinger; Lucian M Itu; Saikiran Rapaka; Puneet Sharma; U Joseph Schoepf
Journal:  Radiology       Date:  2018-04-10       Impact factor: 11.105

9.  Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps).

Authors:  Bjarne L Nørgaard; Jonathon Leipsic; Sara Gaur; Sujith Seneviratne; Brian S Ko; Hiroshi Ito; Jesper M Jensen; Laura Mauri; Bernard De Bruyne; Hiram Bezerra; Kazuhiro Osawa; Mohamed Marwan; Christoph Naber; Andrejs Erglis; Seung-Jung Park; Evald H Christiansen; Anne Kaltoft; Jens F Lassen; Hans Erik Bøtker; Stephan Achenbach
Journal:  J Am Coll Cardiol       Date:  2014-01-30       Impact factor: 24.094

10.  Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: the prospective longitudinal trial of FFR(CT): outcome and resource impacts study.

Authors:  Pamela S Douglas; Gianluca Pontone; Mark A Hlatky; Manesh R Patel; Bjarne L Norgaard; Robert A Byrne; Nick Curzen; Ian Purcell; Matthias Gutberlet; Gilles Rioufol; Ulrich Hink; Herwig Walter Schuchlenz; Gudrun Feuchtner; Martine Gilard; Daniele Andreini; Jesper M Jensen; Martin Hadamitzky; Karen Chiswell; Derek Cyr; Alan Wilk; Furong Wang; Campbell Rogers; Bernard De Bruyne
Journal:  Eur Heart J       Date:  2015-09-01       Impact factor: 29.983

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