High Risk Plaque Features on Coronary CT Angiography
Cardiac Computed Tomography (S Achenbach and T Villines, Section Editor)
First Online: 17 June 2014 DOI:
Cite this article as: Bartykowszki, A., Celeng, C., Károlyi, M. et al. Curr Cardiovasc Imaging Rep (2014) 7: 9279. doi:10.1007/s12410-014-9279-8 Abstract
Coronary computed tomography angiography (CCTA) is a non-invasive imaging technique that can detect, characterize and quantify coronary atherosclerotic plaques in routine clinical settings. The distinct morphological features of vulnerable plaques and stable lesions provide an opportunity for CCTA to identify high-risk plaque features and guide stratified therapeutic interventions. Morphological plaque characteristics, such as large plaque volume, positive remodelling, low CT attenuation, spotty calcification and the napkin-ring sign have been linked to elevated risk of acute coronary syndrome. Recent advances in computational fluid dynamics enabled functional plaque assessment through endothelial shear stress and lesion specific fractional flow reserve calculation. The comprehensive, morphological and functional plaque assessment may improve the identification of vulnerable coronary lesions.
Keywords Coronary CT angiography Coronary atherosclerosis Vulnerable plaque High plaque features
This article is part of the Topical Collection on
Cardiac Computed Tomography References Papers of particular interest, published recently, have been highlighted as: •• Of major importance
Go AS et al. Heart disease and stroke statistics–2014 update: a report from the American Heart Association. Circulation. 2014;129(3):e28–e292.
Falk E. Pathogenesis of atherosclerosis. J Am Coll Cardiol. 2006;47(8 Suppl):C7–C12.
Hansson GK. Inflammation, atherosclerosis, and coronary artery disease. N Engl J Med. 2005;352(16):1685–95.
Libby P. Atherosclerosis: the new view. Sci Am. 2002;286(5):46–55.
Burke AP et al. Coronary risk factors and plaque morphology in men with coronary disease who died suddenly. N Engl J Med. 1997;336(18):1276–82.
Falk E et al. Update on acute coronary syndromes: the pathologists’ view. Eur Heart J. 2013;34(10):719–28.
Virmani R et al. Lessons from sudden coronary death: a comprehensive morphological classification scheme for atherosclerotic lesions. Arterioscler Thromb Vasc Biol. 2000;20(5):1262–75.
Narula J, Achenbach S. Napkin-ring necrotic cores: defining circumferential extent of necrotic cores in unstable plaques. J Am Coll Cardiol Img. 2009;2(12):1436–8.
Alkadhi H et al. Low-dose, 128-slice, dual-source CT coronary angiography: accuracy and radiation dose of the high-pitch and the step-and-shoot mode. Heart. 2010;96(12):933–8.
Sun Z, Ng KH. Diagnostic value of coronary CT angiography with prospective ECG-gating in the diagnosis of coronary artery disease: a systematic review and meta-analysis. Int J Cardiovasc Imaging. 2012;28(8):2109–19.
Miller JM et al. Diagnostic performance of coronary angiography by 64-row CT. N Engl J Med. 2008;359(22):2324–36.
Muller JE, Tofler GH, Stone PH. Circadian variation and triggers of onset of acute cardiovascular disease. Circulation. 1989;79(4):733–43.
Virmani R et al. Pathology of the vulnerable plaque. J Am Coll Cardiol. 2006;47(8 Suppl):C13–8.
van der Giessen AG et al. Small coronary calcifications are not detectable by 64-slice contrast enhanced computed tomography. Int J Cardiovasc Imaging. 2011;27(1):143–52.
Stone GW et al. A prospective natural-history study of coronary atherosclerosis. N Engl J Med. 2011;364(3):226–35.
Maurovich-Horvat P et al. Methods of plaque quantification and characterization by cardiac computed tomography. J Cardiovasc Comput Tomogr. 2009;3 Suppl 2:S91–8.
Schepis T et al. Comparison of dual source computed tomography versus intravascular ultrasound for evaluation of coronary arteries at least one year after cardiac transplantation. Am J Cardiol. 2009;104(10):1351–6.
Brodoefel H et al. Coronary plaque quantification by voxel analysis: dual-source MDCT angiography versus intravascular sonography. AJR Am J Roentgenol. 2009;192(3):W84–9.
Petranovic M et al. Assessment of nonstenotic coronary lesions by 64-slice multidetector computed tomography in comparison to intravascular ultrasound: evaluation of nonculprit coronary lesions. J Cardiovasc Comput Tomogr. 2009;3(1):24–31.
Sun J et al. Identification and quantification of coronary atherosclerotic plaques: a comparison of 64-MDCT and intravascular ultrasound. AJR Am J Roentgenol. 2008;190(3):748–54.
Voros S et al. Coronary atherosclerosis imaging by coronary CT angiography: current status, correlation with intravascular interrogation and meta-analysis. J Am Coll Cardiol Img. 2011;4(5):537–48.
A comprehensive review on the CCTA based quantitative and qualitative plaque characterization.
Leber AW 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(3):672–7.
Hur J et al. Quantification and characterization of obstructive coronary plaques using 64-slice computed tomography: a comparison with intravascular ultrasound. J Comput Assist Tomogr. 2009;33(2):186–92.
Boogers MJ et al. Automated quantification of coronary plaque with computed tomography: comparison with intravascular ultrasound using a dedicated registration algorithm for fusion-based quantification. Eur Heart J. 2012;33(8):1007–16.
This study demonstrated the feasibility of semiautomated quantification of coronary plaque burden with CCTA. Quantitative computed tomography and IVUS showed good correlation
Voros S et al. Prospective validation of standardized, 3-dimensional, quantitative coronary computed tomographic plaque measurements using radiofrequency backscatter intravascular ultrasound as reference standard in intermediate coronary arterial lesions: results from the ATLANTA (assessment of tissue characteristics, lesion morphology, and hemodynamics by angiography with fractional flow reserve, intravascular ultrasound and virtual histology, and noninvasive computed tomography in atherosclerotic plaques) I study. J Am Coll Cardiol Intv. 2011;4(2):198–208.
Oberoi S et al. Reproducibility of non-calcified coronary artery plaque burden quantification from coronary CT angiography across different image analysis platforms. AJR Am J Roentgenol. 2014;202(1):W43–9.
Pflederer T et al. Characterization of culprit lesions in acute coronary syndromes using coronary dual-source CT angiography. Atherosclerosis. 2010;211(2):437–44.
Madder RD et al. Features of disrupted plaques by coronary computed tomographic angiography: correlates with invasively proven complex lesions. Circ Cardiovasc Imaging. 2011;4(2):105–13.
Motoyama S et al. Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome. J Am Coll Cardiol. 2009;54(1):49–57.
Kristensen TS et al. Prognostic implications of nonobstructive coronary plaques in patients with non-ST-segment elevation myocardial infarction: a multidetector computed tomography study. J Am Coll Cardiol. 2011;58(5):502–9.
This prospective study demonstrated that the total amount of non-calcified plaque independently associated with an increased risk of recurrent coronary events after NSTEMI
Versteylen MO et al. Additive value of semiautomated quantification of coronary artery disease using cardiac computed tomographic angiography to predict future acute coronary syndrome. J Am Coll Cardiol. 2013;61(22):2296–305.
Narula J et al. Arithmetic of vulnerable plaques for noninvasive imaging. Nat Clin Pract Cardiovasc Med. 2008;5 Suppl 2:S2–S10.
Kopp AF et al. Non-invasive characterisation of coronary lesion morphology and composition by multislice CT: first results in comparison with intracoronary ultrasound. Eur Radiol. 2001;11(9):1607–11.
Schroeder S et al. Noninvasive detection and evaluation of atherosclerotic coronary plaques with multislice computed tomography. J Am Coll Cardiol. 2001;37(5):1430–5.
Becker CR et al. Ex vivo coronary atherosclerotic plaque characterization with multi-detector-row CT. Eur Radiol. 2003;13(9):2094–8.
Leber AW et al. Accuracy of multidetector spiral computed tomography in identifying and differentiating the composition of coronary atherosclerotic plaques: a comparative study with intracoronary ultrasound. J Am Coll Cardiol. 2004;43(7):1241–7.
Pohle K et al. Characterization of non-calcified coronary atherosclerotic plaque by multi-detector row CT: comparison to IVUS. Atherosclerosis. 2007;190(1):174–80.
Ferencik M et al. Arterial wall imaging: evaluation with 16-section multidetector CT in blood vessel phantoms and ex vivo coronary arteries. Radiology. 2006;240(3):708–16.
Gauss S et al. Assessment of coronary artery remodelling by dual-source CT: a head-to-head comparison with intravascular ultrasound. Heart. 2011;97(12):991–7.
Schlett CL et al. Histogram analysis of lipid-core plaques in coronary computed tomographic angiography: ex vivo validation against histology. Investig Radiol. 2013;48(9):646–53.
Kashiwagi M et al. Feasibility of noninvasive assessment of thin-cap fibroatheroma by multidetector computed tomography. J Am Coll Cardiol Img. 2009;2(12):1412–9.
Ito T et al. Comparison of in vivo assessment of vulnerable plaque by 64-slice multislice computed tomography versus optical coherence tomography. Am J Cardiol. 2011;107(9):1270–7.
Ito H, et al. Characteristics of plaque progression detected by serial coronary computed tomography angiography. Heart and vessels, 2013. doi:
Viles-Gonzalez JF et al. In vivo 16-slice, multidetector-row computed tomography for the assessment of experimental atherosclerosis: comparison with magnetic resonance imaging and histopathology. Circulation. 2004;110(11):1467–72.
Achenbach S et al. Influence of slice thickness and reconstruction kernel on the computed tomographic attenuation of coronary atherosclerotic plaque. J Cardiovasc Comput Tomogr. 2010;4(2):110–5.
Cademartiri F 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(7):1426–31.
Suzuki S et al. Accuracy of attenuation measurement of vascular wall in vitro on computed tomography angiography: effect of wall thickness, density of contrast medium, and measurement point. Investig Radiol. 2006;41(6):510–5.
Achenbach S et al. CV imaging: what was new in 2012? JACC Cardiovasc Imaging. 2013;6(6):714–34.
Motoyama S et al. Multislice computed tomographic characteristics of coronary lesions in acute coronary syndromes. J Am Coll Cardiol. 2007;50(4):319–26.
Kim SY et al. The culprit lesion score on multi-detector computed tomography can detect vulnerable coronary artery plaque. Int J Cardiovasc Imaging. 2010;26 Suppl 2:245–52.
Kitagawa T et al. Characterization of non-calcified coronary plaques and identification of culprit lesions in patients with acute coronary syndrome by 64-slice computed tomography. JACC Cardiovasc Imaging. 2009;2(2):153–60.
Glagov S et al. Compensatory enlargement of human atherosclerotic coronary arteries. N Engl J Med. 1987;316(22):1371–5.
Narula J, Strauss HW. The popcorn plaques. Nat Med. 2007;13(5):532–4.
Libby P. Mechanisms of acute coronary syndromes and their implications for therapy. N Engl J Med. 2013;368(21):2004–13.
A comprehensive overview of the pathophysiology and latest therapeutic implications of acut coronary syndrome.
Achenbach S et al. Assessment of coronary remodelling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography. J Am Coll Cardiol. 2004;43(5):842–7.
Mintz GS et al. American College of Cardiology Clinical Expert Consensus Document on Standards for Acquisition, Measurement and Reporting of Intravascular Ultrasound Studies (IVUS). A report of the American College of Cardiology Task Force on Clinical Expert Consensus Documents. J Am Coll Cardiol. 2001;37(5):1478–92.
Kroner ES et al. Positive remodelling on coronary computed tomography as a marker for plaque vulnerability on virtual histology intravascular ultrasound. Am J Cardiol. 2011;107(12):1725–9.
Otsuka F, Finn AV, Virmani R. Do vulnerable and ruptured plaques hide in heavily calcified arteries? Atherosclerosis. 2013;229(1):34–7.
Nakazawa G et al. Efficacy of culprit plaque assessment by 64-slice multidetector computed tomography to predict transient no-reflow phenomenon during percutaneous coronary intervention. Am Heart J. 2008;155(6):1150–7.
Taylor AJ et al. Coronary calcium independently predicts incident premature coronary heart disease over measured cardiovascular risk factors: mean three-year outcomes in the Prospective Army Coronary Calcium (PACC) project. J Am Coll Cardiol. 2005;46(5):807–14.
Greenland P et al. Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA. 2004;291(2):210–5.
Huang H et al. The impact of calcification on the biomechanical stability of atherosclerotic plaques. Circulation. 2001;103(8):1051–6.
Mauriello A et al. Coronary calcification identifies the vulnerable patient rather than the vulnerable Plaque. Atherosclerosis. 2013;229(1):124–9.
Maldonado N et al. A mechanistic analysis of the role of microcalcifications in atherosclerotic plaque stability: potential implications for plaque rupture. Am J Physiol Heart Circ Physiol. 2012;303(5):H619–28.
Kataoka Y et al. Spotty calcification as a marker of accelerated progression of coronary atherosclerosis: insights from serial intravascular ultrasound. J Am Coll Cardiol. 2012;59(18):1592–7.
Ehara S et al. Spotty calcification typifies the culprit plaque in patients with acute myocardial infarction: an intravascular ultrasound study. Circulation. 2004;110(22):3424–9.
Ferencik M et al. A computed tomography-based coronary lesion score to predict acute coronary syndrome among patients with acute chest pain and significant coronary stenosis on coronary computed tomographic angiogram. Am J Cardiol. 2012;110(2):183–9.
van Velzen JE et al. Comprehensive assessment of spotty calcifications on computed tomography angiography: comparison to plaque characteristics on intravascular ultrasound with radiofrequency backscatter analysis. J Nucl Cardiol Off Publ Am Soc Nucl Cardiol. 2011;18(5):893–903.
Ozaki Y et al. Coronary CT angiographic characteristics of culprit lesions in acute coronary syndromes not related to plaque rupture as defined by optical coherence tomography and angioscopy. Eur Heart J. 2011;32(22):2814–23.
Narula J et al. Histopathologic characteristics of atherosclerotic coronary disease and implications of the findings for the invasive and noninvasive detection of vulnerable plaques. J Am Coll Cardiol. 2013;61(10):1041–51.
This postmortem study analized 295 coronary atherosclerotic plaques to define histomorphologic characteristics of vulnerable plaques and suggests that plaques that rupture cause substantial luminal narrowing before the acute event
Kodama T et al. Computed tomographic angiography-verified plaque characteristics and slow-flow phenomenon during percutaneous coronary intervention. JACC Cardiovasc Interv. 2012;5(6):636–43.
Tanaka A et al. Non-invasive assessment of plaque rupture by 64-slice multidetector computed tomography–comparison with intravascular ultrasound. Circ J. 2008;72(8):1276–81.
Maurovich-Horvat P et al. The napkin-ring sign: CT signature of high-risk coronary plaques? JACC. Cardiovascular Imaging. 2010;3(4):440–4.
Maurovich-Horvat P et al. The napkin-ring sign indicates advanced atherosclerotic lesions in coronary CT angiography. J Am Coll Cardiol Img. 2012;5(12):1243–52.
Seifarth H et al. Histopathological correlates of the napkin-ring sign plaque in coronary CT angiography. Atherosclerosis. 2012;224(1):90–6.
Otsuka K et al. Napkin-ring sign on coronary CT angiography for the prediction of acute coronary syndrome. J Am Coll Cardiol Img. 2013;6(4):448–57.
The first prospective study which demonstrated that the napkin-ring sign on the CCTA is strongly associated with future ACS events.
Achenbach S. Computed tomography coronary angiography. J Am Coll Cardiol. 2006;48(10):1919–28.
Meijboom WB et al. Comprehensive assessment of coronary artery stenoses: computed tomography coronary angiography versus conventional coronary angiography and correlation with fractional flow reserve in patients with stable angina. J Am Coll Cardiol. 2008;52(8):636–43.
De Bruyne B et al. Coronary flow reserve calculated from pressure measurements in humans. Validation with positron emission tomography. Circulation. 1994;89(3):1013–22.
Berger A et al. Long-term clinical outcome after fractional flow reserve-guided percutaneous coronary intervention in patients with multivessel disease. J Am Coll Cardiol. 2005;46(3):438–42.
Tonino PA et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. 2009;360(3):213–24.
Pijls NH et al. Experimental basis of determining maximum coronary, myocardial, and collateral blood flow by pressure measurements for assessing functional stenosis severity before and after percutaneous transluminal coronary angioplasty. Circulation. 1993;87(4):1354–67.
Koo BK et al. Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J Am Coll Cardiol. 2011;58(19):1989–97.
Bech GJ et al. Fractional flow reserve to determine the appropriateness of angioplasty in moderate coronary stenosis: a randomized trial. Circulation. 2001;103(24):2928–34.
Fearon WF. Is a myocardial infarction more likely to result from a mild coronary lesion or an ischemia-producing one? Circ Cardiovasc Interv. 2011;4(6):539–41.
Gijsen FJ et al. Strain distribution over plaques in human coronary arteries relates to shear stress. Am J Physiol Heart Circ Physiol. 2008;295(4):H1608–14.
Hachamovitch R et al. Value of stress myocardial perfusion single photon emission computed tomography in patients with normal resting electrocardiograms: an evaluation of incremental prognostic value and cost-effectiveness. Circulation. 2002;105(7):823–9.
Shaw LJ et al. Optimal medical therapy with or without percutaneous coronary intervention to reduce ischemic burden: results from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) trial nuclear substudy. Circulation. 2008;117(10):1283–91.
Caro CG, Fitz-Gerald JM, Schroter RC. Arterial wall shear and distribution of early atheroma in man. Nature. 1969;223(5211):1159–60.
Friedman MH et al. Correlation between wall shear and intimal thickness at a coronary artery branch. Atherosclerosis. 1987;68(1–2):27–33.
Koskinas KC et al. Natural history of experimental coronary atherosclerosis and vascular remodelling in relation to endothelial shear stress: a serial, in vivo intravascular ultrasound study. Circulation. 2010;121(19):2092–101.
Malek AM, Alper SL, Izumo S. Hemodynamic shear stress and its role in atherosclerosis. JAMA. 1999;282(21):2035–42.
Wentzel JJ et al. Endothelial shear stress in the evolution of coronary atherosclerotic plaque and vascular remodelling: current understanding and remaining questions. Cardiovasc Res. 2012;96(2):234–43.
Chatzizisis YS et al. Role of endothelial shear stress in the natural history of coronary atherosclerosis and vascular remodelling: molecular, cellular, and vascular behavior. J Am Coll Cardiol. 2007;49(25):2379–93.
Dey D et al. Automated three-dimensional quantification of non-calcified coronary plaque from coronary CT angiography: comparison with intravascular US. Radiology. 2010;257(2):516–22.
Stone PH et al. Prediction of progression of coronary artery disease and clinical outcomes using vascular profiling of endothelial shear stress and arterial plaque characteristics: the PREDICTION Study. Circulation. 2012;126(2):172–81.
Frauenfelder T et al. In-vivo flow simulation in coronary arteries based on computed tomography datasets: feasibility and initial results. Eur Radiol. 2007;17(5):1291–300.
Jin S et al. Flow patterns and wall shear stress distributions at atherosclerotic-prone sites in a human left coronary artery–an exploration using combined methods of CT and computational fluid dynamics. Conf Proc IEEE Eng Med Biol Soc. 2004;5:3789–91.
Borkin MA et al. Evaluation of artery visualizations for heart disease diagnosis. IEEE Trans Vis Comput Graph. 2011;17(12):2479–88.
Ramkumar PG et al. New advances in cardiac computed tomography. Curr Opin Cardiol. 2009;24(6):596–603.
Gijsen FJ et al. 3D reconstruction techniques of human coronary bifurcations for shear stress computations. J Biomech. 2014;47(1):39–43.
McCullough EC. Photon attenuation in computed tomography. Med Phys. 1975;2(6):307–20.
Alvarez RE, Macovski A. Energy-selective reconstructions in X-ray computerized tomography. Phys Med Biol. 1976;21(5):733–44.
Halliburton SS. Recent technologic advances in multi-detector row cardiac CT. Cardiol Clin. 2009;27(4):655–64.
Ruzsics B et al. Dual-energy CT of the heart for diagnosing coronary artery stenosis and myocardial ischemia-initial experience. Eur Radiol. 2008;18(11):2414–24.
Schwarz F et al. Dual-energy CT of the heart–principles and protocols. Eur J Radiol. 2008;68(3):423–33.
So A et al. Prospectively ECG-triggered rapid kV-switching dual-energy CT for quantitative imaging of myocardial perfusion. JACC Cardiovasc Imaging. 2012;5(8):829–36.
Shinohara M et al. Atherosclerotic plaque imaging using phase-contrast X-ray computed tomography. Am J Physiol Heart Circ Physiol. 2008;294(2):H1094–100.
Momose A, Fukuda J. Phase-contrast radiographs of nonstained rat cerebellar specimen. Med Phys. 1995;22(44):6355–67.
Fitzgerald R. Phase-sensitive x-ray imaging. Phys Today. 2000;53(7):23–6.
Hyafil F et al. Quantification of inflammation within rabbit atherosclerotic plaques using the macrophage-specific CT contrast agent N1177: a comparison with 18F-FDG PET/CT and histology. J Nucl Med. 2009;50(6):959–65.
Cormode DP et al. Atherosclerotic plaque composition: analysis with multicolor CT and targeted gold nanoparticles. Radiology. 2010;256(3):774–82.
Rogers IS et al. Feasibility of FDG imaging of the coronary arteries: comparison between acute coronary syndrome and stable angina. JACC Cardiovasc Imaging. 2010;3(4):388–97.
Joshi NV et al. 18F-fluoride positron emission tomography for identification of ruptured and high-risk coronary atherosclerotic plaques: a prospective clinical trial. Lancet. 2014;383(9918):705–13.
In this prospective clinical trial the authors have shown that intense 18F-NaF uptake localises to recent plaque rupture in patients with acute myocardial infarction.
Marin D et al. Low-tube-voltage, high-tube-current multidetector abdominal CT: improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm–initial clinical experience. Radiology. 2010;254(1):145–53.
Prakash P et al. Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique. Radiology. 2010;256(1):261–9.
Yu Z et al. Fast model-based X-ray CT reconstruction using spatially nonhomogeneous ICD optimization. IEEE Trans Image Process. 2011;20(1):161–75.
Scheffel H et al. Coronary artery plaques: cardiac CT with model-based and adaptive-statistical iterative reconstruction technique. Eur J Radiol. 2012;81(3):e363–9.
Yoo RE et al. Image quality of adaptive iterative dose reduction 3D of coronary CT angiography of 640-slice CT: comparison with filtered back-projection. Int J Cardiovasc Imaging. 2013;29(3):669–76.
Leipsic J, Heilbron BG, Hague C. Iterative reconstruction for coronary CT angiography: finding its way. Int J Cardiovasc Imaging. 2012;28(3):613–20.
Benedek T, Gyongyosi M, Benedek I. Multislice computed tomographic coronary angiography for quantitative assessment of culprit lesions in acute coronary syndromes. Can J Cardiol. 2013;29(3):364–71.
Leipsic J et al. Estimated radiation dose reduction using adaptive statistical iterative reconstruction in coronary CT angiography: the ERASIR study. AJR Am J Roentgenol. 2010;195(3):655–60.
Min JK et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA. 2012;308(12):1237–45.
Takx RA et al. The effect of iterative reconstruction on quantitative computed tomography assessment of coronary plaque composition. Int J Cardiovasc Imaging. 2014;30(1):155–63.
Fuchs TA et al. CT coronary angiography: impact of adapted statistical iterative reconstruction (ASIR) on coronary stenosis and plaque composition analysis. Int J Cardiovasc Imaging. 2013;29(3):719–24.
Renker M et al. Evaluation of heavily calcified vessels with coronary CT angiography: comparison of iterative and filtered back projection image reconstruction. Radiology. 2011;260(2):390–9.
Puchner SB et al. The effect of iterative image reconstruction algorithms on the feasibility of automated plaque assessment in coronary CT angiography. Int J Cardiovasc Imaging. 2013;29(8):1879–88.
PubMed Copyright information
© Springer Science+Business Media New York 2014