Literature DB >> 34527519

Prognostic value of CT-derived myocardial blood flow, CT fractional flow reserve and high-risk plaque features for predicting major adverse cardiac events.

Lihua Yu1, Zhigang Lu2, Xu Dai1, Chengxing Shen2, Lei Zhang3, Jiayin Zhang3.   

Abstract

BACKGROUND: Myocardial blood flow (MBF), CT fractional flow reserve (CT-FFR) and high-risk plaque (HRP) features have been revealed to be associated with patients' prognosis. However, direct intra-individual comparison of these CT-derived parameters has not been explored yet. The aim of this study was to investigate the prognostic value of CT-derived MBF, CT-FFR and HRP features for predicting major adverse cardiac events (MACEs).
METHODS: Consecutive patients with chest pain and intermediate-to-high pre-test probability of coronary artery disease (CAD) were prospectively enrolled. All patients were referred for dynamic CT myocardial perfusion imaging (CT-MPI) + coronary CT angiography (CCTA) and followed up for at least 1 year. MBFischemic (mean MBF of all ischemic segments), MBFratio (MBF of ischemic segments/MBF of reference segments), CT-FFR and HRP features were measured and multivariate analysis was used to evaluate the predictive value of all above parameters for MACEs.
RESULTS: One hundred and forty-two patients were included into final analysis. MBFischemic and MBFratio was significantly lower in patients with MACE compared to patients without MACE (87 vs. 153 mL/100 mL/min and 0.64 vs. 0.95, both P<0.001). Similarly, CT-FFR was also markedly lower in patients with MACE (0.58 vs. 0.88, P<0.001) whereas coronary artery calcium score (CACS) was significantly higher (1,038.9 vs. 34.2, P<0.001). According to ROC curve analysis, MBFischemic, MBFratio and CACS had largest area under curve (AUC =0.872, 0.855 and 0.813 respectively, all P<0.001) for identifying patients with MACE. After adjusted by multivariate analysis, MBFischemic (hazard ratio =23.382, P=0.003) and CACS (hazard ratio =3.759, P=0.029) were revealed to be the independent predictors for MACE where CT-FFR and HRP features failed to have prognostic value.
CONCLUSIONS: MBFischemic derived from dynamic CT-MPI was the strongest predictor for MACE, followed by CACS. MBFischemic outperformed HRP features and CT-FFR for prediction of unfavorable clinical outcome. 2021 Cardiovascular Diagnosis and Therapy. All rights reserved.

Entities:  

Keywords:  Coronary artery disease (CAD); computed tomography (CT); fractional flow reserve (FFR); myocardial perfusion imaging (MPI); plaque

Year:  2021        PMID: 34527519      PMCID: PMC8410497          DOI: 10.21037/cdt-21-219

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


  27 in total

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2.  Computed Tomographic Coronary Angiography-Derived Plaque Characteristics Predict Major Adverse Cardiovascular Events: A Systematic Review and Meta-Analysis.

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Journal:  Circ Cardiovasc Imaging       Date:  2018-01       Impact factor: 7.792

Review 3.  The incremental value of coronary artery calcium scores to myocardial single photon emission computer tomography in risk assessment.

Authors:  Marcus Hacker; Christoph Becker
Journal:  J Nucl Cardiol       Date:  2011-08       Impact factor: 5.952

4.  The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning-based FFRCT, or high-risk plaque features?

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Journal:  Eur Radiol       Date:  2019-03-22       Impact factor: 5.315

5.  Incremental Prognostic Value of Myocardial Blood Flow Quantified With Stress Dynamic Computed Tomography Perfusion Imaging.

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Journal:  JACC Cardiovasc Imaging       Date:  2018-07-18

6.  Quantitative baseline CT plaque characterization of unrevascularized non-culprit intermediate coronary stenosis predicts lesion volume progression and long-term prognosis: A serial CT follow-up study.

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Journal:  JACC Cardiovasc Imaging       Date:  2019-09-18

8.  Coronary calcium as a predictor of coronary events in four racial or ethnic groups.

Authors:  Robert Detrano; Alan D Guerci; J Jeffrey Carr; Diane E Bild; Gregory Burke; Aaron R Folsom; Kiang Liu; Steven Shea; Moyses Szklo; David A Bluemke; Daniel H O'Leary; Russell Tracy; Karol Watson; Nathan D Wong; Richard A Kronmal
Journal:  N Engl J Med       Date:  2008-03-27       Impact factor: 91.245

9.  Intermodel disagreement of myocardial blood flow estimation from dynamic CT perfusion imaging.

Authors:  Marly van Assen; Gert Jan Pelgrim; Carlo N De Cecco; J Marco A Stijnen; Beatrice M Zaki; Matthijs Oudkerk; Rozemarijn Vliegenthart; U Joseph Schoepf
Journal:  Eur J Radiol       Date:  2018-11-24       Impact factor: 3.528

10.  Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome.

Authors:  Sadako Motoyama; Masayoshi Sarai; Hiroto Harigaya; Hirofumi Anno; Kaori Inoue; Tomonori Hara; Hiroyuki Naruse; Junichi Ishii; Hitoshi Hishida; Nathan D Wong; Renu Virmani; Takeshi Kondo; Yukio Ozaki; Jagat Narula
Journal:  J Am Coll Cardiol       Date:  2009-06-30       Impact factor: 24.094

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  2 in total

1.  Distribution of FFRCT in single obstructive coronary stenosis and predictors for major adverse cardiac events: a propensity score matching study.

Authors:  Xianglan Jin; Xiangyu Jin; Xiaoyun Wu; Luguang Chen; Tiegong Wang; Wangfu Zang
Journal:  BMC Med Imaging       Date:  2022-03-31       Impact factor: 1.930

Review 2.  The role of cardiac computed tomography in predicting adverse coronary events.

Authors:  Maria Emfietzoglou; Michail C Mavrogiannis; Athanasios Samaras; Georgios P Rampidis; George Giannakoulas; Polydoros N Kampaktsis
Journal:  Front Cardiovasc Med       Date:  2022-07-15
  2 in total

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