The basis for personalized anti-atherosclerotic cardiovascular medical therapy: role of atherosclerosis imaging with cardiac computed tomography

The basis for personalized anti-atherosclerotic cardiovascular medical therapy: role of... This editorial refers to ‘Impact of statin therapy on coronary plaque burden and composition assessed by coronary computed tomographic angiography—a systematic review and meta-analysis’ by L. Andelius et al. doi: 10.1093/ehjci/jey012. Introduction Current evidence is robust about the primary role of cardiac computed tomography (CCT) as diagnostic tool for the detection of suspected obstructive coronary artery disease (CAD). Updated 2017 guidelines of the National Institute for Health and Care Excellence (NICE) from the UK NHS regarding the approach in the detection of suspected obstructive CAD put computed tomography (CT) as the first imaging tool in these settings.1 Evidence is building also on the fact that stable obstructive CAD should not mandatorily be approached with revascularization. In fact, obstructive CAD is not a disease but rather a complication of atherosclerosis. Previous studies already showed that medical therapy could deliver results comparable with percutaneous coronary intervention (PCI) in stable patients.2 The ORBITA trial demonstrated also the relevant placebo effect of PCI in the context of stable CAD.3 The landscape of CAD is changing and there is a demand for, or an ‘evolution towards’ if you will, a more clinical (rather than mechanical) and personalised approach to CAD. Cardiac computed tomography showed its potential in the visualization and quantification of atherosclerotic plaques since the very beginning of its development.4,5 The SCOT-HEART study showed that the diagnostic advantage of CCT translates into a better prognosis6; the explanation is that CCT can always show and diagnose sub-clinical/non-obstructive atherosclerosis (regardless the degree of stenosis), thereby inducing a more aggressive medical therapy and more motivation for adherence to therapeutic schemes. Hence, anti-atherosclerotic medical therapy is the key and should be optimized and individualized as much as possible also accounting for non-obstructive atherosclerotic phenotypes that can be identified using CCT. In this issue of the Journal Andelius et al.7 performed a meta-analysis on the impact of statin therapy on coronary plaque burden using CCT. Morphological computed tomography-based methods to quantify and characterize atherosclerosis plaque burden—Caveats Currently, there is no methodology and/or software platform that is widely recognized or accepted to quantify and characterize atherosclerotic plaque burden and its features with CCT. Surely, there was no unique methodology when the studies of the meta-analysis from Andelius et al.7 were performed. Several technical and physiological factors can affect the measurements in terms of quantification of plaque burden using CCT, thereby affecting reproducibility and comparability of results.8,9 For instance, reconstruction algorithms are different between different CT vendors and also, within the same vendor, between different software releases. Also, there is a consistent impact of intravascular attenuation, related mostly to the volume and rate of intravenous contrast material administration, on the measured attenuation of non-calcified plaque components of the coronary trees. More recently more factors have to be considered, like kilovoltage modulation and iterative reconstructions algorithms. Given all these considerations, there has been an important and constant development of software application with semi-automated segmentation capabilities that allow the extraction of coronary artery walls with reasonable reliability. These softwares are more reliable today as compared to some years ago (Figure 1).10 Figure 1 View largeDownload slide Quantitative assessment of a high-risk plaque with cardiac CT. Example of quantitative assessment of a culprit lesion on a right coronary artery in a patient with Myocardial Infarction with Non-Obstructive Coronary Arteries (STEMI-MINOCA). The image shows visually a non-calcified non-obstructive eccentric plaque in the longitudinal plane (A, arrowheads) and in the axial plane (B, arrowheads) with colour-coded overlay for plaque characteristics; with quantification software it is possible to quantify, besides total plaque volume, also the volume of fibrous, fibro-fatty, and necrotic core components within the plaque (C, D). Figure 1 View largeDownload slide Quantitative assessment of a high-risk plaque with cardiac CT. Example of quantitative assessment of a culprit lesion on a right coronary artery in a patient with Myocardial Infarction with Non-Obstructive Coronary Arteries (STEMI-MINOCA). The image shows visually a non-calcified non-obstructive eccentric plaque in the longitudinal plane (A, arrowheads) and in the axial plane (B, arrowheads) with colour-coded overlay for plaque characteristics; with quantification software it is possible to quantify, besides total plaque volume, also the volume of fibrous, fibro-fatty, and necrotic core components within the plaque (C, D). The patient with non-obstructive coronary artery disease Although, we see all the many current limitations of CCT for the quantification and characterization of coronary plaque burden, we should also look ahead because this is the beginning of a new possible approach to an imaging-guided personalised anti-atherosclerotic therapy. The new PARADIGM (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging) registry is focused on this aspect, which is actually the next step towards this goal.11 Enrolling ≥2000 patients who underwent at least two CCT scans and with a follow-up for adverse cardiovascular events, the PARADIGM aims at observation of the natural course of atherosclerosis and at the identification of the clinical determinants of plaque progression or regression, thereby giving tools for attenuating disease progression and improving clinical outcomes.11 Conclusions Despite all the limitations that CCT still has for the characterization and quantification of plaque burden, there is already consistent evidence that in the near future we will be able to the assess coronary atherosclerosis and adapt our medical therapies accordingly and with a more individualized approach (Figure 2). Methodologies, tools and definitions are still developing, however, its probably just a question of time. Figure 2 View largeDownload slide Paradigm shift for imaging-guided personalized anti-atherosclerotic therapy. Based on the possibility of quantifying and characterizing coronary plaque burden with a non-invasive test (CCT) the field of (advanced) primary prevention (i.e. patients in which CAD is present but non obstructive) can become more personalized, and we could even consider that in the future, we will integrate all the information to modulate anti-atherosclerotic therapies. CAD, coronary artery disease; CMR, cardiac magnetic resonance; CT, computed tomography; ECG, electrocardiogram; Echo, echocardiography; FFR, fractional flow reserve; PET, positron emission tomography; SPECT, single-photon emission computed tomography. Figure 2 View largeDownload slide Paradigm shift for imaging-guided personalized anti-atherosclerotic therapy. Based on the possibility of quantifying and characterizing coronary plaque burden with a non-invasive test (CCT) the field of (advanced) primary prevention (i.e. patients in which CAD is present but non obstructive) can become more personalized, and we could even consider that in the future, we will integrate all the information to modulate anti-atherosclerotic therapies. CAD, coronary artery disease; CMR, cardiac magnetic resonance; CT, computed tomography; ECG, electrocardiogram; Echo, echocardiography; FFR, fractional flow reserve; PET, positron emission tomography; SPECT, single-photon emission computed tomography. Conflict of interest: none declared. References 1 Timmis A, Roobottom CA. National Institute for Health and Care Excellence updates the stable chest pain guideline with radical changes to the diagnostic paradigm. Heart  2017; 103: 982– 6. 2 Boden WE, O'Rourke RA, Teo KK, Hartigan PM, Maron DJ, Kostuk WJ et al.  ; COURAGE Trial Research Group. Optimal medical therapy with or without PCI for stable coronary disease. N Engl J Med  2007; 356: 1503– 16. 3 Al-Lamee R, Thompson D, Dehbi HM, Sen S, Tang K, Davies J et al.  ; ORBITA Investigators . Percutaneous coronary intervention in stable angina (ORBITA): a double-blind, randomised controlled trial. Lancet  2018; 391: 31– 40. 4 Leber AW, Becker A, Knez A, von Ziegler F, Sirol M, Nikolaou K et al.   Accuracy of 64-slice computed tomography to classify and quantify plaque volumes in the proximal coronary system: a comparative study using intravascular ultrasound. J Am Coll Cardiol  2006; 47: 672– 7. 5 Achenbach S, Ropers D, Hoffmann U, MacNeill B, Baum U, Pohle K et al.   Assessment of coronary remodeling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography. J Am Coll Cardiol  2004; 43: 842– 7. 6 SCOT-HEART investigators. CT coronary angiography in patients with suspected angina due to coronary heart disease (SCOT-HEART): an open-label, parallel-group, multicentre trial. Lancet  2015; 385: 2383– 91. 7 Andelius L, Mortensen MB, Nørgaard BL, Abdulla J. Impact of statin therapy on coronary plaque burden and composition assessed by coronary computed tomographic angiography—a systematic review and meta-analysis. Eur Heart J Cardiovasc Imaging  2018. doi: 10.1093/ehjci/jey012. 8 Cademartiri F, Mollet NR, Runza G, Bruining N, Hamers R, Somers P et al.   Influence of intracoronary attenuation on coronary plaque measurements using multislice computed tomography: observations in an ex vivo model of coronary computed tomography angiography. Eur Radiol  2005; 15: 1426– 31. 9 Cademartiri F, La Grutta L, Runza G, Palumbo A, Maffei E, Mollet NR et al.   Influence of convolution filtering on coronary plaque attenuation values: observations in an ex vivo model of multislice computed tomography coronary angiography. Eur Radiol  2007; 17: 1842– 9. 10 Bourantas CV, Papadopoulou SL, Serruys PW, Sakellarios A, Kitslaar PH, Bizopoulos P et al.   Noninvasive prediction of atherosclerotic progression: the PROSPECT-MSCT study. JACC Cardiovasc Imaging  2016; 9: 1009– 11. 11 Lee SE, Chang HJ, Rizvi A, Hadamitzky M, Kim YJ, Conte E et al.   TomoGraphic Angiography IMaging (PARADIGM) registry: a comprehensive exploration of plaque progression and its impact on clinical outcomes from a multicenter serial coronary computed tomographic angiography study. Am Heart J  2016; 182: 72– 9. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Heart Journal – Cardiovascular Imaging Oxford University Press

The basis for personalized anti-atherosclerotic cardiovascular medical therapy: role of atherosclerosis imaging with cardiac computed tomography

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Oxford University Press
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Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com.
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2047-2404
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10.1093/ehjci/jey059
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Abstract

This editorial refers to ‘Impact of statin therapy on coronary plaque burden and composition assessed by coronary computed tomographic angiography—a systematic review and meta-analysis’ by L. Andelius et al. doi: 10.1093/ehjci/jey012. Introduction Current evidence is robust about the primary role of cardiac computed tomography (CCT) as diagnostic tool for the detection of suspected obstructive coronary artery disease (CAD). Updated 2017 guidelines of the National Institute for Health and Care Excellence (NICE) from the UK NHS regarding the approach in the detection of suspected obstructive CAD put computed tomography (CT) as the first imaging tool in these settings.1 Evidence is building also on the fact that stable obstructive CAD should not mandatorily be approached with revascularization. In fact, obstructive CAD is not a disease but rather a complication of atherosclerosis. Previous studies already showed that medical therapy could deliver results comparable with percutaneous coronary intervention (PCI) in stable patients.2 The ORBITA trial demonstrated also the relevant placebo effect of PCI in the context of stable CAD.3 The landscape of CAD is changing and there is a demand for, or an ‘evolution towards’ if you will, a more clinical (rather than mechanical) and personalised approach to CAD. Cardiac computed tomography showed its potential in the visualization and quantification of atherosclerotic plaques since the very beginning of its development.4,5 The SCOT-HEART study showed that the diagnostic advantage of CCT translates into a better prognosis6; the explanation is that CCT can always show and diagnose sub-clinical/non-obstructive atherosclerosis (regardless the degree of stenosis), thereby inducing a more aggressive medical therapy and more motivation for adherence to therapeutic schemes. Hence, anti-atherosclerotic medical therapy is the key and should be optimized and individualized as much as possible also accounting for non-obstructive atherosclerotic phenotypes that can be identified using CCT. In this issue of the Journal Andelius et al.7 performed a meta-analysis on the impact of statin therapy on coronary plaque burden using CCT. Morphological computed tomography-based methods to quantify and characterize atherosclerosis plaque burden—Caveats Currently, there is no methodology and/or software platform that is widely recognized or accepted to quantify and characterize atherosclerotic plaque burden and its features with CCT. Surely, there was no unique methodology when the studies of the meta-analysis from Andelius et al.7 were performed. Several technical and physiological factors can affect the measurements in terms of quantification of plaque burden using CCT, thereby affecting reproducibility and comparability of results.8,9 For instance, reconstruction algorithms are different between different CT vendors and also, within the same vendor, between different software releases. Also, there is a consistent impact of intravascular attenuation, related mostly to the volume and rate of intravenous contrast material administration, on the measured attenuation of non-calcified plaque components of the coronary trees. More recently more factors have to be considered, like kilovoltage modulation and iterative reconstructions algorithms. Given all these considerations, there has been an important and constant development of software application with semi-automated segmentation capabilities that allow the extraction of coronary artery walls with reasonable reliability. These softwares are more reliable today as compared to some years ago (Figure 1).10 Figure 1 View largeDownload slide Quantitative assessment of a high-risk plaque with cardiac CT. Example of quantitative assessment of a culprit lesion on a right coronary artery in a patient with Myocardial Infarction with Non-Obstructive Coronary Arteries (STEMI-MINOCA). The image shows visually a non-calcified non-obstructive eccentric plaque in the longitudinal plane (A, arrowheads) and in the axial plane (B, arrowheads) with colour-coded overlay for plaque characteristics; with quantification software it is possible to quantify, besides total plaque volume, also the volume of fibrous, fibro-fatty, and necrotic core components within the plaque (C, D). Figure 1 View largeDownload slide Quantitative assessment of a high-risk plaque with cardiac CT. Example of quantitative assessment of a culprit lesion on a right coronary artery in a patient with Myocardial Infarction with Non-Obstructive Coronary Arteries (STEMI-MINOCA). The image shows visually a non-calcified non-obstructive eccentric plaque in the longitudinal plane (A, arrowheads) and in the axial plane (B, arrowheads) with colour-coded overlay for plaque characteristics; with quantification software it is possible to quantify, besides total plaque volume, also the volume of fibrous, fibro-fatty, and necrotic core components within the plaque (C, D). The patient with non-obstructive coronary artery disease Although, we see all the many current limitations of CCT for the quantification and characterization of coronary plaque burden, we should also look ahead because this is the beginning of a new possible approach to an imaging-guided personalised anti-atherosclerotic therapy. The new PARADIGM (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging) registry is focused on this aspect, which is actually the next step towards this goal.11 Enrolling ≥2000 patients who underwent at least two CCT scans and with a follow-up for adverse cardiovascular events, the PARADIGM aims at observation of the natural course of atherosclerosis and at the identification of the clinical determinants of plaque progression or regression, thereby giving tools for attenuating disease progression and improving clinical outcomes.11 Conclusions Despite all the limitations that CCT still has for the characterization and quantification of plaque burden, there is already consistent evidence that in the near future we will be able to the assess coronary atherosclerosis and adapt our medical therapies accordingly and with a more individualized approach (Figure 2). Methodologies, tools and definitions are still developing, however, its probably just a question of time. Figure 2 View largeDownload slide Paradigm shift for imaging-guided personalized anti-atherosclerotic therapy. Based on the possibility of quantifying and characterizing coronary plaque burden with a non-invasive test (CCT) the field of (advanced) primary prevention (i.e. patients in which CAD is present but non obstructive) can become more personalized, and we could even consider that in the future, we will integrate all the information to modulate anti-atherosclerotic therapies. CAD, coronary artery disease; CMR, cardiac magnetic resonance; CT, computed tomography; ECG, electrocardiogram; Echo, echocardiography; FFR, fractional flow reserve; PET, positron emission tomography; SPECT, single-photon emission computed tomography. Figure 2 View largeDownload slide Paradigm shift for imaging-guided personalized anti-atherosclerotic therapy. Based on the possibility of quantifying and characterizing coronary plaque burden with a non-invasive test (CCT) the field of (advanced) primary prevention (i.e. patients in which CAD is present but non obstructive) can become more personalized, and we could even consider that in the future, we will integrate all the information to modulate anti-atherosclerotic therapies. CAD, coronary artery disease; CMR, cardiac magnetic resonance; CT, computed tomography; ECG, electrocardiogram; Echo, echocardiography; FFR, fractional flow reserve; PET, positron emission tomography; SPECT, single-photon emission computed tomography. Conflict of interest: none declared. References 1 Timmis A, Roobottom CA. National Institute for Health and Care Excellence updates the stable chest pain guideline with radical changes to the diagnostic paradigm. Heart  2017; 103: 982– 6. 2 Boden WE, O'Rourke RA, Teo KK, Hartigan PM, Maron DJ, Kostuk WJ et al.  ; COURAGE Trial Research Group. Optimal medical therapy with or without PCI for stable coronary disease. N Engl J Med  2007; 356: 1503– 16. 3 Al-Lamee R, Thompson D, Dehbi HM, Sen S, Tang K, Davies J et al.  ; ORBITA Investigators . Percutaneous coronary intervention in stable angina (ORBITA): a double-blind, randomised controlled trial. Lancet  2018; 391: 31– 40. 4 Leber AW, Becker A, Knez A, von Ziegler F, Sirol M, Nikolaou K et al.   Accuracy of 64-slice computed tomography to classify and quantify plaque volumes in the proximal coronary system: a comparative study using intravascular ultrasound. J Am Coll Cardiol  2006; 47: 672– 7. 5 Achenbach S, Ropers D, Hoffmann U, MacNeill B, Baum U, Pohle K et al.   Assessment of coronary remodeling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography. J Am Coll Cardiol  2004; 43: 842– 7. 6 SCOT-HEART investigators. CT coronary angiography in patients with suspected angina due to coronary heart disease (SCOT-HEART): an open-label, parallel-group, multicentre trial. Lancet  2015; 385: 2383– 91. 7 Andelius L, Mortensen MB, Nørgaard BL, Abdulla J. Impact of statin therapy on coronary plaque burden and composition assessed by coronary computed tomographic angiography—a systematic review and meta-analysis. Eur Heart J Cardiovasc Imaging  2018. doi: 10.1093/ehjci/jey012. 8 Cademartiri F, Mollet NR, Runza G, Bruining N, Hamers R, Somers P et al.   Influence of intracoronary attenuation on coronary plaque measurements using multislice computed tomography: observations in an ex vivo model of coronary computed tomography angiography. Eur Radiol  2005; 15: 1426– 31. 9 Cademartiri F, La Grutta L, Runza G, Palumbo A, Maffei E, Mollet NR et al.   Influence of convolution filtering on coronary plaque attenuation values: observations in an ex vivo model of multislice computed tomography coronary angiography. Eur Radiol  2007; 17: 1842– 9. 10 Bourantas CV, Papadopoulou SL, Serruys PW, Sakellarios A, Kitslaar PH, Bizopoulos P et al.   Noninvasive prediction of atherosclerotic progression: the PROSPECT-MSCT study. JACC Cardiovasc Imaging  2016; 9: 1009– 11. 11 Lee SE, Chang HJ, Rizvi A, Hadamitzky M, Kim YJ, Conte E et al.   TomoGraphic Angiography IMaging (PARADIGM) registry: a comprehensive exploration of plaque progression and its impact on clinical outcomes from a multicenter serial coronary computed tomographic angiography study. Am Heart J  2016; 182: 72– 9. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

European Heart Journal – Cardiovascular ImagingOxford University Press

Published: Apr 19, 2018

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