Abstract
Objectives
To present an overview of studies using serial coronary computed tomography angiography (CCTA) as a tool for finding both quantitative (changes) and qualitative plaque characteristics as well as epicardial adipose tissue (EAT) volume changes as predictors of plaque progression and/or major adverse cardiac events (MACE) and outline the challenges and advantages of using a serial non-invasive imaging approach for assessing cardiovascular prognosis.
Methods
A literature search was performed in PubMed, Embase, Web of Science, Cochrane Library and Emcare. All observational cohort studies were assessed for quality using the Newcastle–Ottawa Scale (NOS). The NOS score was then converted into Agency for Healthcare Research and Quality (AHRQ) standards: good, fair and poor.
Results
A total of 36 articles were analyzed for this review, 3 of which were meta-analyses and one was a technical paper. Quantitative baseline plaque features seem to be more predictive of MACE and/or plaque progression as compared to qualitative plaque features.
Conclusions
A critical review of the literature focusing on studies utilizing serial CCTA revealed that mainly quantitative baseline plaque features and quantitative plaque changes are predictive of MACE and/or plaque progression contrary to qualitative plaque features. Significant questions regarding the clinical implications of these specific quantitative and qualitative plaque features as well as the challenges of using serial CCTA have yet to be resolved in studies using this imaging technique.
Key Points
• Use of (serial) CCTA can identify plaque characteristics and plaque changes as well as changes in EAT volume that are predictive of plaque progression and/or major adverse events (MACE) at follow-up.
• Studies utilizing serial CCTA revealed that mainly quantitative baseline plaque features and quantitative plaque changes are predictive of MACE and/or plaque progression contrary to qualitative plaque features.
• Ultimately, serial CCTA is a promising technique for the evaluation of cardiovascular prognosis, yet technical details remain to be refined.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00330-021-08393-9/MediaObjects/330_2021_8393_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00330-021-08393-9/MediaObjects/330_2021_8393_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00330-021-08393-9/MediaObjects/330_2021_8393_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00330-021-08393-9/MediaObjects/330_2021_8393_Fig4_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00330-021-08393-9/MediaObjects/330_2021_8393_Fig5_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs00330-021-08393-9/MediaObjects/330_2021_8393_Fig6_HTML.png)
Similar content being viewed by others
Abbreviations
- %DS:
-
Percentage diameter stenosis
- ACS:
-
Acute coronary syndrome
- CAD:
-
Coronary artery disease
- CCTA:
-
Coronary computed tomography angiography
- CI:
-
Confidence interval
- CX:
-
Circumflex artery
- EAT:
-
Epicardial adipose tissue
- EFV:
-
Epicardial fat volume
- HR:
-
Hazard ratio
- HRP:
-
High-risk plaque features
- HU:
-
Hounsfield units
- ICA:
-
Invasive coronary angiography
- IQR:
-
Interquartile range
- IVOCT:
-
Intravascular optical coherence tomography
- IVUS:
-
Intravascular ultrasound
- LAD:
-
Left anterior descending artery
- LAP:
-
Low-attenuation plaque
- LAPV:
-
Low-attenuation plaque volume
- LM:
-
Left main
- MACE:
-
Major adverse cardiac events
- OR:
-
Odds ratio
- PAV:
-
Percentage atheroma volume
- PR:
-
Positive remodelling
- TPV:
-
Total plaque volume
References
Roth GA, Johnson C, Abajobir A et al (2017) Global, regional, and national burden of cardiovascular diseases for 10 causes, 1990 to 2015. J Am Coll Cardiol 70(1):1–25
Camargo GC, Rothstein T, Derenne ME et al (2017) Factors associated with coronary artery disease progression assessed by serial coronary computed tomography angiography. Arq Bras Cardiol 108(5):396–404
Virmani R, Burke AP, Farb A, Kolodgie FD (2006) Pathology of the vulnerable plaque. J Am Coll Cardiol 47(8 Suppl):C13–C18
Psaltis PJ, Talman AH, Munnur K et al (2016) Relationship between epicardial fat and quantitative coronary artery plaque progression: insights from computer tomography coronary angiography. Int J Cardiovasc Imaging 32(2):317–328
Hoffmann U, Moselewski F, Nieman K et al (2006) Noninvasive assessment of plaque morphology and composition in culprit and stable lesions in acute coronary syndrome and stable lesions in stable angina by multidetector computed tomography. J Am Coll Cardiol 47(8):1655–1662
Fischer C, Hulten E, Belur P, Smith R, Voros S, Villines TC (2013) Coronary CT angiography versus intravascular ultrasound for estimation of coronary stenosis and atherosclerotic plaque burden: a meta-analysis. J Cardiovasc Comput Tomogr 7(4):256–266
Knuuti J, Ballo H, Juarez-Orozco LE et al (2018) The performance of non-invasive tests to rule-in and rule-out significant coronary artery stenosis in patients with stable angina: a meta-analysis focused on post-test disease probability. Eur Heart J 39(35):3322–3330
Weber C, Deseive S, Brim G et al (2020) Coronary plaque volume and predictors for fast plaque progression assessed by serial coronary CT angiography-a single-center observational study. Eur J Radiol 123:108805
Yu M, Li W, Lu Z, Wei M, Yan J, Zhang J (2018) 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. Int J Cardiol 264:181–186
Lee SE, Sung JM, Andreini D et al (2019) Differences in progression to obstructive lesions per high-risk plaque features and plaque volumes with CCTA. JACC Cardiovasc Imaging 13(6):1409–1417
Nakanishi K, Fukuda S, Tanaka A et al (2014) Persistent epicardial adipose tissue accumulation is associated with coronary plaque vulnerability and future acute coronary syndrome in non-obese subjects with coronary artery disease. Atherosclerosis 237(1):353–360
Narula J, Chandrashekhar Y, Ahmadi A et al (2021) SCCT 2021 expert consensus document on coronary computed tomographic angiography: a report of the Society of Cardiovascular Computed Tomography. J Cardiovasc Comput Tomogr 15(3):192–217
Papadopoulou SL, Garcia-Garcia HM, Rossi A et al (2013) Reproducibility of computed tomography angiography data analysis using semiautomated plaque quantification software: implications for the design of longitudinal studies. Int J Cardiovasc Imaging 29(5):1095–1104
de Graaf MA, Broersen A, Kitslaar PH et al (2013) Automatic quantification and characterization of coronary atherosclerosis with computed tomography coronary angiography: cross-correlation with intravascular ultrasound virtual histology. Int J Cardiovasc Imaging 29(5):1177–1190
Dalager MG, Bottcher M, Andersen G et al (2011) Impact of luminal density on plaque classification by CT coronary angiography. Int J Cardiovasc Imaging 27(4):593–600
de Knegt MC, Haugen M, Jensen AK et al (2019) Coronary plaque composition assessed by cardiac computed tomography using adaptive Hounsfield unit thresholds. Clin Imaging 57:7–14
Lee SE, Chang HJ, Sung JM et al (2018) Effects of statins on coronary atherosclerotic plaques: The PARADIGM Study. JACC Cardiovasc Imaging 11(10):1475–1484
Lee SE, Sung JM, Andreini D et al (2019) Differential association between the progression of coronary artery calcium score and coronary plaque volume progression according to statins: the Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging (PARADIGM) study. Eur Heart J Cardiovasc Imaging 20(11):1307–1314
Smit JM, van Rosendael AR, El Mahdiui M et al (2020) Impact of clinical characteristics and statins on coronary plaque progression by serial computed tomography angiography. Circ Cardiovasc Imaging 13(3):9
van Rosendael AR, Lin FY, Ma X et al (2020) Percent atheroma volume: optimal variable to report whole-heart atherosclerotic plaque burden with coronary CTA, the PARADIGM study. J Cardiovasc Comput Tomogr 14(5):400–406
Deseive S, Straub R, Kupke M et al (2018) Automated quantification of coronary plaque volume from CT angiography improves CV risk prediction at long-term follow-up. JACC Cardiovascular Imaging 11(2):280–2.
Hadamitzky M, Taubert S, Deseive S et al (2013) Prognostic value of coronary computed tomography angiography during 5 years of follow-up in patients with suspected coronary artery disease. Eur Heart J 34(42):3277–3285
Maurovich-Horvat P, Schlett CL, Alkadhi H et al (2012) The napkin-ring sign indicates advanced atherosclerotic lesions in coronary CT angiography. JACC Cardiovascular Imaging 5(12):1243–52.
Motoyama S, Kondo T, Sarai M et al (2007) Multislice computed tomographic characteristics of coronary lesions in acute coronary syndromes. J Am Coll Cardiol 50(4):319–326
Otsuka K, Fukuda S, Tanaka A et al (2013) Napkin-ring sign on coronary CT angiography for the prediction of acute coronary syndrome. JACC Cardiovascular Imaging 6(4):448–57.
Hoffmann U, Moselewski F, Nieman K et al (2006) Noninvasive assessment of plaque morphology and composition in culprit and stable lesions in acute coronary syndrome and stable lesions in stable angina by multidetector computed tomography. J Am Coll Cardiol 47(8):1655–1662
Puchner SB, Liu T, Mayrhofer T et al (2014) High-risk plaque detected on coronary CT angiography predicts acute coronary syndromes independent of significant stenosis in acute chest pain. J Am Coll Cardiol 64(7):684–692
Motoyama S, Sarai M, Harigaya H et al (2009) Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome. J Am Coll Cardiol 54(1):49–57
Han D, Kolli KK, Al’Aref SJ et al (2020) Machine learning framework to identify individuals at risk of rapid progression of coronary atherosclerosis: from the PARADIGM Registry. J Am Heart Assoc. 9(5):e013958
Nerlekar N, Ha FJ, Cheshire C et al (2018) Computed tomographic coronary angiography–derived plaque characteristics predict major adverse cardiovascular events. Circ Cardiovasc Imaging 11(1):e006973
Nicholls SJ, Hsu A, Wolski K et al (2010) Intravascular ultrasound-derived measures of coronary atherosclerotic plaque burden and clinical outcome. J Am Coll Cardiol 55(21):2399–2407
Lee SE, Sung JM, Andreini D et al (2020) Per-lesion versus per-patient analysis of coronary artery disease in predicting the development of obstructive lesions: the Progression of AtheRosclerotic PlAque DetermIned by Computed TmoGraphic Angiography Imaging (PARADIGM) study. Int J Cardiovasc Imaging 36(12):2357–2364
You S, Sun JS, Park SY, Baek Y, Kang DK (2016) Relationship between indexed epicardial fat volume and coronary plaque volume assessed by cardiac multidetector CT. Medicine (Baltimore) 95(27):8
Motoyama S, Ito H, Sarai M et al (2015) Plaque characterization by coronary computed tomography angiography and the likelihood of acute coronary events in mid-term follow-up. J Am Coll Cardiol 66(4):337–346
van Rosendael AR, Lin FY, van den Hoogen IJ et al (2021) Progression of whole-heart atherosclerosis by coronary CT and major adverse cardiovascular events. J Cardiovasc Comput Tomogr 15(4):322–330
Gu H, Lu B, Gao Y et al (2020) Prognostic value of atherosclerosis progression for prediction of cardiovascular events in patients with nonobstructive coronary artery disease. Acad Radiol 28(7):980–987
Zeb I, Li D, Nasir K et al (2013) Effect of statin treatment on coronary plaque progression - a serial coronary CT angiography study. Atherosclerosis 231(2):198–204
Li Z, Hou Z, Yin W et al (2016) Effects of statin therapy on progression of mild noncalcified coronary plaque assessed by serial coronary computed tomography angiography: a multicenter prospective study. Am Heart J 180:29–38
Symons R, Morris JZ, Wu CO et al (2016) Coronary CT angiography: variability of CT scanners and readers in measurement of plaque volume. Radiology 281(3):737–748
Taron J, Lee S, Aluru J, Hoffmann U, Lu MT (2020) A review of serial coronary computed tomography angiography (CTA) to assess plaque progression and therapeutic effect of anti-atherosclerotic drugs. Int J Cardiovasc Imaging 36(12):2305–2317
Halliburton SS, Abbara S, Chen MY et al (2011) SCCT guidelines on radiation dose and dose-optimization strategies in cardiovascular CT. J Cardiovasc Comput Tomogr 5(4):198–224
Cao Q, Broersen A, Kitslaar PH, Yuan M, Lelieveldt BPF, Dijkstra J (2020) Automatic coronary artery plaque thickness comparison between baseline and follow-up CCTA images. Med Phys 47(3):1083–1093
Dahal S, Budoff MJ (2019) Implications of serial coronary computed tomography angiography in the evaluation of coronary plaque progression. Curr Opin Lipidol 30(6):446–451
Lakshmanan S, Rezvanizadeh V, Budoff MJ (2020) Comprehensive plaque assessment with serial coronary CT angiography: translation to bedside. Int J Cardiovasc Imaging 36(12):2335–2346
Acknowledgements
The Department of Cardiology of Leiden University Medical Centre received research grants from Biotronik, Medtronic, Boston Scientific, GE Healthcare and Edwards Lifesciences. Arthur Scholte received a speaker’s fee from Canon Medical Systems. This research did not receive any specific grants from funding agencies in the public, commercial or not-for-profit sectors.
Funding
The authors state that this work has not received any funding.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Guarantor
The scientific guarantor of this publication is Wouter Jukema.
Conflict of Interest
The authors of this manuscript declare relationships with the following companies: Arthur Scholte received a speaker’s fee from Canon Medical Systems. The remaining authors have nothing to disclose.
Statistics and Biometry
No complex statistical methods were necessary for this paper.
Informed Consent
Written informed consent was not required for this study because it concerns a review article.
Ethical Approval
Institutional review board approval was not required because it concerns a review article.
Methodology
• review article
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
van Driest, F.Y., Bijns, C.M., van der Geest, R.J. et al. Utilizing (serial) coronary computed tomography angiography (CCTA) to predict plaque progression and major adverse cardiac events (MACE): results, merits and challenges. Eur Radiol 32, 3408–3422 (2022). https://doi.org/10.1007/s00330-021-08393-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00330-021-08393-9