Literature DB >> 34450625

Standardized measurement of coronary inflammation using cardiovascular computed tomography: integration in clinical care as a prognostic medical device.

Evangelos K Oikonomou1,2, Alexios S Antonopoulos1, David Schottlander3, Mohammad Marwan4, Chris Mathers3, Pete Tomlins3, Muhammad Siddique3, Laura V Klüner1, Cheerag Shirodaria3, Michail C Mavrogiannis1, Sheena Thomas5, Agostina Fava6, John Deanfield7, Keith M Channon1,8,9, Stefan Neubauer1,8,9, Milind Y Desai6, Stephan Achenbach4, Charalambos Antoniades1,5,8,9.   

Abstract

AIMS: Coronary computed tomography angiography (CCTA) is a first-line modality in the investigation of suspected coronary artery disease (CAD). Mapping of perivascular fat attenuation index (FAI) on routine CCTA enables the non-invasive detection of coronary artery inflammation by quantifying spatial changes in perivascular fat composition. We now report the performance of a new medical device, CaRi-Heart®, which integrates standardized FAI mapping together with clinical risk factors and plaque metrics to provide individualized cardiovascular risk prediction. METHODS AND
RESULTS: The study included 3912 consecutive patients undergoing CCTA as part of clinical care in the USA (n = 2040) and Europe (n = 1872). These cohorts were used to generate age-specific nomograms and percentile curves as reference maps for the standardized interpretation of FAI. The first output of CaRi-Heart® is the FAI-Score of each coronary artery, which provides a measure of coronary inflammation adjusted for technical, biological, and anatomical characteristics. FAI-Score is then incorporated into a risk prediction algorithm together with clinical risk factors and CCTA-derived coronary plaque metrics to generate the CaRi-Heart® Risk that predicts the likelihood of a fatal cardiac event at 8 years. CaRi-Heart® Risk was trained in the US population and its performance was validated externally in the European population. It improved risk discrimination over a clinical risk factor-based model [Δ(C-statistic) of 0.085, P = 0.01 in the US Cohort and 0.149, P < 0.001 in the European cohort] and had a consistent net clinical benefit on decision curve analysis above a baseline traditional risk factor-based model across the spectrum of cardiac risk.
CONCLUSION: Mapping of perivascular FAI on CCTA enables the non-invasive detection of coronary artery inflammation by quantifying spatial changes in perivascular fat composition. We now report the performance of a new medical device, CaRi-Heart®, which allows standardized measurement of coronary inflammation by calculating the FAI-Score of each coronary artery. The CaRi-Heart® device provides a reliable prediction of the patient's absolute risk for a fatal cardiac event by incorporating traditional cardiovascular risk factors along with comprehensive CCTA coronary plaque and perivascular adipose tissue phenotyping. This integration advances the prognostic utility of CCTA for individual patients and paves the way for its use as a dual diagnostic and prognostic tool among patients referred for CCTA.
© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.

Entities:  

Keywords:  Atherosclerosis; Coronary artery disease; Fat attenuation index; Pericoronary; Perivascular

Mesh:

Year:  2021        PMID: 34450625     DOI: 10.1093/cvr/cvab286

Source DB:  PubMed          Journal:  Cardiovasc Res        ISSN: 0008-6363            Impact factor:   10.787


  10 in total

1.  Clinical applications of cardiac computed tomography: a consensus paper of the European Association of Cardiovascular Imaging-part II.

Authors:  Gianluca Pontone; Alexia Rossi; Marco Guglielmo; Marc R Dweck; Oliver Gaemperli; Koen Nieman; Francesca Pugliese; Pal Maurovich-Horvat; Alessia Gimelli; Bernard Cosyns; Stephan Achenbach
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2022-03-22       Impact factor: 9.130

2.  ESC CVD Prevention Guidelines 2021: improvements, controversies, and opportunities.

Authors:  Charalambos Antoniades; Henry W West
Journal:  Cardiovasc Res       Date:  2022-01-29       Impact factor: 13.081

Review 3.  Non-canonical WNT signalling in cardiovascular disease: mechanisms and therapeutic implications.

Authors:  Ioannis Akoumianakis; Murray Polkinghorne; Charalambos Antoniades
Journal:  Nat Rev Cardiol       Date:  2022-06-13       Impact factor: 49.421

4.  The Predictive Value of the Perivascular Adipose Tissue CT Fat Attenuation Index for Coronary In-stent Restenosis.

Authors:  Bin Qin; Zhengjun Li; Hao Zhou; Yongkang Liu; Huiming Wu; Zhongqiu Wang
Journal:  Front Cardiovasc Med       Date:  2022-04-26

Review 5.  The year in cardiovascular medicine 2021: imaging.

Authors:  Chiara Bucciarelli-Ducci; Nina Ajmone-Marsan; Marcelo Di Carli; Edward Nicol
Journal:  Eur Heart J       Date:  2022-03-31       Impact factor: 29.983

6.  A methylprednisolone-loaded and core-shell nanofiber-covered stent-graft to prevent inflammation and reduce degradation in aortic dissection.

Authors:  Junjun Liu; Hongqiao Zhu; Yifei Pei; Jian Zhou; Zaiping Jing; Heng Zhang
Journal:  Biomater Res       Date:  2022-04-25

Review 7.  Non-Invasive Modalities in the Assessment of Vulnerable Coronary Atherosclerotic Plaques.

Authors:  Panagiotis Theofilis; Marios Sagris; Alexios S Antonopoulos; Evangelos Oikonomou; Konstantinos Tsioufis; Dimitris Tousoulis
Journal:  Tomography       Date:  2022-07-06

8.  The correlation of pericoronary adipose tissue with coronary artery disease and left ventricular function.

Authors:  Deshu You; Haiyang Yu; Zhiwei Wang; Xiaoyu Wei; Xiangxiang Wu; Changjie Pan
Journal:  BMC Cardiovasc Disord       Date:  2022-09-06       Impact factor: 2.174

Review 9.  Cardiovascular computed tomography imaging for coronary artery disease risk: plaque, flow and fat.

Authors:  Keith M Channon; David E Newby; Edward D Nicol; John Deanfield
Journal:  Heart       Date:  2022-09-12       Impact factor: 7.365

Review 10.  Browning Epicardial Adipose Tissue: Friend or Foe?

Authors:  Elisa Doukbi; Astrid Soghomonian; Coralie Sengenès; Shaista Ahmed; Patricia Ancel; Anne Dutour; Bénédicte Gaborit
Journal:  Cells       Date:  2022-03-14       Impact factor: 6.600

  10 in total

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