Coronary CT angiography evaluation with artificial intelligence for individualized medical treatment of atherosclerosis: a Consensus Statement from the QCI Study Group

Kenrick Schulze^#¹, Anne-Marieke Stantien^#¹, Michelle C Williams^#², Vassilios S Vassiliou³, Andreas A Giannopoulos⁴, Koen Nieman⁵, Pál Maurovich-Horvat⁶, Jason M Tarkin⁷, Rozemarijn Vliegenthart⁸, Jonathan Weir-McCall⁹, Mahmoud Mohamed¹, Bernhard Föllmer¹, Federico Biavati¹, Ann-Christine Stahl¹, Jakob Knape¹, Hanna Balogh^{1

6}, Nicola Galea¹⁰, Ivana Išgum^{11

12

13}, Armin Arbab-Zadeh¹⁴, Hatem Alkadhi¹⁵, Robert Manka^{15

16}, David A Wood^{17

18}, Edward D Nicol^{19

20}, Nick S Nurmohamed²¹, Fabrice M A C Martens²¹, Damini Dey^{22

23}, David E Newby², Marc Dewey^{24

25

26

27

28}

Affiliations

¹ Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany.
² British Heart Foundation Centre of Research Excellence, University of Edinburgh, Edinburgh, UK.
³ Department of Cardiac Medicine, Norwich Medical School, University of East Anglia, Norwich, England.
⁴ Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Zurich, Switzerland.
⁵ Department of Medicine/Cardiovascular and Radiology, Stanford University, Stanford, CA, USA.
⁶ Department of Radiology, Medical Imaging Center, Semmelweis University, Budapest, Hungary.
⁷ Section of Cardiorespiratory Medicine, Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK.
⁸ Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
⁹ Department of Cardiovascular Imaging, Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
¹⁰ Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Rome, Italy.
¹¹ Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
¹² Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
¹³ Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands.
¹⁴ Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
¹⁵ Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
¹⁶ Institute for Biomedical Engineering, University and ETH, Zurich, Switzerland.
¹⁷ National Heart and Lung Institute, Imperial College London, London, UK.
¹⁸ National Institute for Prevention and Cardiovascular Health, University of Galway, Galway, Republic of Ireland.
¹⁹ School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
²⁰ Department of Cardiology and Radiology, Royal Brompton Hospital, London, UK.
²¹ Department of Cardiology, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
²² Departments of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
²³ Departments of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
²⁴ Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany. marc.dewey@charite.de.
²⁵ Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany. marc.dewey@charite.de.
²⁶ Berlin University Alliance, Berlin, Germany. marc.dewey@charite.de.
²⁷ DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany. marc.dewey@charite.de.
²⁸ Deutsches Herzzentrum der Charité (DHZC), Berlin, Germany. marc.dewey@charite.de.

^# Contributed equally.

PMID: 40751112
DOI: 10.1038/s41569-025-01191-6

Review

Coronary CT angiography evaluation with artificial intelligence for individualized medical treatment of atherosclerosis: a Consensus Statement from the QCI Study Group

Kenrick Schulze et al. Nat Rev Cardiol. 2025.

. 2025 Aug 1.

doi: 10.1038/s41569-025-01191-6. Online ahead of print.

Authors

Affiliations

¹ Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany.
² British Heart Foundation Centre of Research Excellence, University of Edinburgh, Edinburgh, UK.
³ Department of Cardiac Medicine, Norwich Medical School, University of East Anglia, Norwich, England.
⁴ Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Zurich, Switzerland.
⁵ Department of Medicine/Cardiovascular and Radiology, Stanford University, Stanford, CA, USA.
⁶ Department of Radiology, Medical Imaging Center, Semmelweis University, Budapest, Hungary.
⁷ Section of Cardiorespiratory Medicine, Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK.
⁸ Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
⁹ Department of Cardiovascular Imaging, Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
¹⁰ Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Rome, Italy.
¹¹ Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
¹² Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
¹³ Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands.
¹⁴ Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
¹⁵ Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
¹⁶ Institute for Biomedical Engineering, University and ETH, Zurich, Switzerland.
¹⁷ National Heart and Lung Institute, Imperial College London, London, UK.
¹⁸ National Institute for Prevention and Cardiovascular Health, University of Galway, Galway, Republic of Ireland.
¹⁹ School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
²⁰ Department of Cardiology and Radiology, Royal Brompton Hospital, London, UK.
²¹ Department of Cardiology, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
²² Departments of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
²³ Departments of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
²⁴ Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany. marc.dewey@charite.de.
²⁵ Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany. marc.dewey@charite.de.
²⁶ Berlin University Alliance, Berlin, Germany. marc.dewey@charite.de.
²⁷ DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany. marc.dewey@charite.de.
²⁸ Deutsches Herzzentrum der Charité (DHZC), Berlin, Germany. marc.dewey@charite.de.

^# Contributed equally.

PMID: 40751112
DOI: 10.1038/s41569-025-01191-6

Abstract

Coronary CT angiography is widely implemented, with an estimated 2.2 million procedures in patients with stable chest pain every year in Europe alone. In parallel, artificial intelligence and machine learning are poised to transform coronary atherosclerotic plaque evaluation by improving reliability and speed. However, little is known about how to use coronary atherosclerosis imaging biomarkers to individualize recommendations for medical treatment. This Consensus Statement from the Quantitative Cardiovascular Imaging (QCI) Study Group outlines key recommendations derived from a three-step Delphi process that took place after the third international QCI Study Group meeting in September 2024. Experts from various fields of cardiovascular imaging agreed on the use of age-adjusted and gender-adjusted percentile curves, based on coronary plaque data from the DISCHARGE and SCOT-HEART trials. Two key issues were addressed: the need to harness the reliability and precision of artificial intelligence and machine learning tools and to tailor treatment on the basis of individualized plaque analysis. The QCI Study Group recommends that the presence of any atherosclerotic plaque should lead to a recommendation of pharmacological treatment, whereas the 70th percentile of total plaque volume warrants high-intensity treatment. The aim of these recommendations is to lay the groundwork for future trials and to unlock the potential of coronary CT angiography to improve patient outcomes globally.

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Conflict of interest statement

Competing interests: M.C.W. has given talks for Canon Medical Systems, GE Healthcare, Novartis and Siemens Healthineers and performed consultancy for Canon Medical Systems and FEops. A.A.G. reports research grant support from GE Healthcare, the Iten-Kohaut Foundation and Promedica Stiftung, has given talks for GE Healthcare and has performed consultancy for Artrya Ltd. J.M.T is supported by the Cambridge BHF Centre of Research Excellence (RE/24/130011) and the Wellcome Trust (211100/Z/18/Z) and has received research grants from AstraZeneca, the British Heart Foundation and General Electric Healthcare. R.V. is supported by institutional research grants from Siemens Healthineers and has received honoraria for lectures/moderatorship from Bayer Healthcare and Siemens Healthineers. I.I. receives institutional research grants from the Dutch Research Council with the participation of Abbott Vascular, Philips Healthcare and Pie Medical Imaging, and institutional research grants from Esaote, Health Holland with participation of Braun and Infraredex, Horizon Europe, the EU Innovative Health Initiative with the participation of Philips Healthcare and Pie Medical Imaging. A.A.-Z. receives grant support from Canon Medical Systems. H.A. receives institutional grants from Bayer, Canon, Guerbet and Siemens and receives royalties from Springer Nature for a textbook on cardiac CT. H.A. received speaker honoraria from Siemens. R.M. receives speaker fees from Bayer, Bristol Meyers Squib, Philips and Siemens and research grant support from the Swissheart Foundation and the USZ Foundation. E.D.N. is on the Scientific Advisory Board of Caristo and is the immediate Past President of the Society of Cardiovascular Computed Tomography (SCCT; the opinions expressed in this article are the author’s own and do not represent the view of the SCCT). N.S.N. reports grants from the Dutch Heart Foundation (Dekker 03-007-2023-0068), European Atherosclerosis Society (2023), research funding/speaker fees from Cleerly, Daiichi Sankyo and Novartis and is co-founder of Lipid Tools. M.D. was the publications chair of the European Society of Radiology (ESR) from 2022 to 2025 (the opinions expressed in this article are the author’s own and do not represent the view of the ESR). He is also the editor of Cardiac CT (Springer Nature) and has institutional master research agreements with Canon, General Electric, Philips and Siemens, the arrangements of which are managed by Charité — Universitätsmedizin Berlin. He also holds a joint approved patent on dynamic perfusion analysis using fractal analysis (EPO 2022 EP3350773A1 and USPTO 2021 10,991,109). The other authors declare no competing interests.

References

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Coronary CT angiography evaluation with artificial intelligence for individualized medical treatment of atherosclerosis: a Consensus Statement from the QCI Study Group

Affiliations

Coronary CT angiography evaluation with artificial intelligence for individualized medical treatment of atherosclerosis: a Consensus Statement from the QCI Study Group

Authors

Affiliations

Abstract

Conflict of interest statement

References

Publication types

LinkOut - more resources

Full Text Sources