Low-Attenuation Noncalcified Plaque on Coronary Computed Tomography Angiography Predicts Myocardial Infarction: Results From the Multicenter SCOT-HEART Trial (Scottish Computed Tomography of the HEART)

Michelle C Williams, Jacek Kwiecinski, Mhairi Doris, Priscilla McElhinney, Michelle S D'Souza, Sebastien Cadet, Philip D Adamson, Alastair J Moss, Shirjel Alam, Amanda Hunter, Anoop S V Shah, Nicholas L Mills, Tania Pawade, Chengjia Wang, Jonathan Weir McCall, Michael Bonnici-Mallia, Christopher Murrills, Giles Roditi, Edwin J R van Beek, Leslee J Shaw, Edward D Nicol, Daniel S Berman, Piotr J Slomka, David E Newby, Marc R Dweck, Damini Dey, Michelle C Williams, Jacek Kwiecinski, Mhairi Doris, Priscilla McElhinney, Michelle S D'Souza, Sebastien Cadet, Philip D Adamson, Alastair J Moss, Shirjel Alam, Amanda Hunter, Anoop S V Shah, Nicholas L Mills, Tania Pawade, Chengjia Wang, Jonathan Weir McCall, Michael Bonnici-Mallia, Christopher Murrills, Giles Roditi, Edwin J R van Beek, Leslee J Shaw, Edward D Nicol, Daniel S Berman, Piotr J Slomka, David E Newby, Marc R Dweck, Damini Dey

Abstract

Background: The future risk of myocardial infarction is commonly assessed using cardiovascular risk scores, coronary artery calcium score, or coronary artery stenosis severity. We assessed whether noncalcified low-attenuation plaque burden on coronary CT angiography (CCTA) might be a better predictor of the future risk of myocardial infarction.

Methods: In a post hoc analysis of a multicenter randomized controlled trial of CCTA in patients with stable chest pain, we investigated the association between the future risk of fatal or nonfatal myocardial infarction and low-attenuation plaque burden (% plaque to vessel volume), cardiovascular risk score, coronary artery calcium score or obstructive coronary artery stenoses.

Results: In 1769 patients (56% male; 58±10 years) followed up for a median 4.7 (interquartile interval, 4.0-5.7) years, low-attenuation plaque burden correlated weakly with cardiovascular risk score (r=0.34; P<0.001), strongly with coronary artery calcium score (r=0.62; P<0.001), and very strongly with the severity of luminal coronary stenosis (area stenosis, r=0.83; P<0.001). Low-attenuation plaque burden (7.5% [4.8-9.2] versus 4.1% [0-6.8]; P<0.001), coronary artery calcium score (336 [62-1064] versus 19 [0-217] Agatston units; P<0.001), and the presence of obstructive coronary artery disease (54% versus 25%; P<0.001) were all higher in the 41 patients who had fatal or nonfatal myocardial infarction. Low-attenuation plaque burden was the strongest predictor of myocardial infarction (adjusted hazard ratio, 1.60 (95% CI, 1.10-2.34) per doubling; P=0.014), irrespective of cardiovascular risk score, coronary artery calcium score, or coronary artery area stenosis. Patients with low-attenuation plaque burden greater than 4% were nearly 5 times more likely to have subsequent myocardial infarction (hazard ratio, 4.65; 95% CI, 2.06-10.5; P<0.001).

Conclusions: In patients presenting with stable chest pain, low-attenuation plaque burden is the strongest predictor of fatal or nonfatal myocardial infarction. These findings challenge the current perception of the supremacy of current classical risk predictors for myocardial infarction, including stenosis severity. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01149590.

Keywords: atherosclerosis; cardiovascular diseases; computed tomography angiography; coronary artery disease; myocardial infarction; plaque, atherosclerotic.

Figures

Figure 1.
Figure 1.
Coronary CT angiography (CCTA) plaque analysis. Images from a 67-year-old female who presented with atypical chest pain. She was a nonsmoker with a history of hypertension, a previous transient ischemic attack, and normal exercise tolerance test. Her 10-year cardiovascular risk score was 14%, coronary artery calcium score was 62 Agatston units, and coronary computed tomography angiography identified obstructive disease in the left anterior descending (LAD) and first diagonal. Curved planar reformations show (A) proximal LAD, (B) first diagonal, and (C) mid-LAD. Red overlay illustrates noncalcified plaque in the individual segment only, but all plaque in each vessel was analyzed for the per patient assessment. D, Shows a zoomed in view of the mid LAD plaque with blue lumen, red noncalcified plaque and orange low-attenuation plaque. She subsequently presented with acute myocardial infarction and underwent invasive coronary angiography (E).
Figure 2.
Figure 2.
Correlations between plaque burden subtypes, calcium score, coronary stenosis and cardiovascular risk score. Correlations between plaque burden subtypes and Agatston coronary artery calcium score, coronary artery area stenosis and ASSIGN (Assessing cardiovascular risk using SIGN guidelines) cardiovascular risk score. P<0.001 for all. CACS indicates Agatston coronary artery calcium score.
Figure 3.
Figure 3.
Correlations between low-attenuation plaque burden, cardiovascular risk score, calcium score and coronary stenosis. Correlations between total low-attenuation plaque burden and 10-year cardiovascular risk score, Agatston coronary artery calcium score, and coronary artery area stenosis. CACS indicates Agatston coronary artery calcium score.
Figure 4.
Figure 4.
Plaque burden and fatal or nonfatal myocardial infarction. Quantitative assessment of atherosclerotic plaque burden in patients with and without a primary event of fatal or nonfatal myocardial infarction (P≤0.01 for all). CACS indicates Agatston coronary artery calcium score, and MI, myocardial infarction.
Figure 5.
Figure 5.
Low-attenuation plaque burden and fatal or nonfatal myocardial infarction. Cumulative incidence of fatal or nonfatal myocardial infarction in patients with and without a low-attenuation plaque burden greater than 4%. MI indicates myocardial infarction.

References

    1. Knuuti J, Wijns W, Saraste A, Capodanno D, Barbato E, Funck-Brentano C, Prescott E, Storey RF, Deaton C, Cuisset T, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes: the Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC). European Heart Journal. 2019 doi: 10.1093/eurheartj/ehz425.
    1. Fihn SD, Blankenship JC, Alexander KP, Bittl JA, Byrne JG, Fletcher BJ, Fonarow GC, Lange RA, Levine GN, Maddox TM, et al. 2014 ACC/AHA/AATS/PCNA/SCAI/STS focused update of the guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines, and the American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. Circulation. 2014;130:1749–1767. doi: 10.1161/CIR.0000000000000095.
    1. Miller JM, Rochitte CE, Dewey M, Arbab-Zadeh A, Niinuma H, Gottlieb I, Paul N, Clouse ME, Shapiro EP, Hoe J, et al. Diagnostic performance of coronary angiography by 64-row CT. N Engl J Med. 2008;359:2324–2336. doi: 10.1056/NEJMoa0806576.
    1. Motoyama S, Sarai M, Harigaya H, Anno H, Inoue K, Hara T, Naruse H, Ishii J, Hishida H, Wong ND, et al. Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome. J Am Coll Cardiol. 2009;54:49–57. doi: 10.1016/j.jacc.2009.02.068.
    1. Min JK, Shaw LJ, Devereux RB, Okin PM, Weinsaft JW, Russo DJ, Lippolis NJ, Berman DS, Callister TQ. Prognostic value of multidetector coronary computed tomographic angiography for prediction of all-cause mortality. J Am Coll Cardiol. 2007;50:1161–1170. doi: 10.1016/j.jacc.2007.03.067.
    1. Motoyama S, Ito H, Sarai M, Kondo T, Kawai H, Nagahara Y, Harigaya H, Kan S, Anno H, Takahashi H, et al. Plaque characterization by coronary computed tomography angiography and the likelihood of Acute coronary events in mid-term follow-up. J Am Coll Cardiol. 2015;66:337–346. doi: 10.1016/j.jacc.2015.05.069.
    1. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M, Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15:827–832. doi: 10.1016/0735-1097(90)90282-t.
    1. McClelland RL, Chung H, Detrano R, Post W, Kronmal RA. Distribution of coronary artery calcium by race, gender, and age: results from the Multi-Ethnic Study of Atherosclerosis (MESA). Circulation. 2006;113:30–37. doi: 10.1161/CIRCULATIONAHA.105.580696.
    1. Shah S, Bellam N, Leipsic J, Berman DS, Quyyumi A, Hausleiter J, Achenbach S, Al-Mallah M, Budoff MJ, Cademartiri F, et al. CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter Registry) Investigators. Prognostic significance of calcified plaque among symptomatic patients with nonobstructive coronary artery disease. J Nucl Cardiol. 2014;21:453–466. doi: 10.1007/s12350-014-9865-9.
    1. McClelland RL, Jorgensen NW, Budoff M, Blaha MJ, Post WS, Kronmal RA, Bild DE, Shea S, Liu K, Watson KE, et al. 10-year coronary heart disease risk prediction using coronary artery calcium and traditional risk factors: derivation in the MESA (Multi-Ethnic Study of Atherosclerosis) with validation in the HNR (Heinz Nixdorf Recall) study and the DHS (Dallas Heart Study). J Am Coll Cardiol. 2015;66:1643–1653. doi: 10.1016/j.jacc.2015.08.035.
    1. Hoffmann U, Massaro JM, D’Agostino RB, Sr, Kathiresan S, Fox CS, O’Donnell CJ. Cardiovascular event prediction and risk reclassification by coronary, aortic, and valvular calcification in the Framingham Heart study. J Am Heart Assoc. 2016;5(2):e002144.
    1. Joshi NV, Vesey AT, Williams MC, Shah AS, Calvert PA, Craighead FH, Yeoh SE, Wallace W, Salter D, Fletcher AM, et al. 18F-fluoride positron emission tomography for identification of ruptured and high-risk coronary atherosclerotic plaques: a prospective clinical trial. Lancet. 2014;383:705–713. doi: 10.1016/S0140-6736(13)61754-7.
    1. Virmani R, Kolodgie FD, Burke AP, Farb A, Schwartz SM. Lessons from sudden coronary death: a comprehensive morphological classification scheme for atherosclerotic lesions. Arterioscler Thromb Vasc Biol. 2000;20:1262–1275. doi: 10.1161/01.atv.20.5.1262.
    1. Virmani R, Burke AP, Kolodgie FD, Farb A. Vulnerable plaque: the pathology of unstable coronary lesions. J Interv Cardiol. 2002;15:439–446. doi: 10.1111/j.1540-8183.2002.tb01087.x.
    1. Stone GW, Maehara A, Lansky AJ, de Bruyne B, Cristea E, Mintz GS, Mehran R, McPherson J, Farhat N, Marso SP, et al. PROSPECT Investigators. A prospective natural-history study of coronary atherosclerosis. N Engl J Med. 2011;364:226–235. doi: 10.1056/NEJMoa1002358.
    1. Voros S, Rinehart S, Qian Z, Joshi P, Vazquez G, Fischer C, Belur P, Hulten E, Villines TC. Coronary atherosclerosis imaging by coronary CT angiography: current status, correlation with intravascular interrogation and meta-analysis. JACC Cardiovasc Imaging. 2011;4:537–548. doi: 10.1016/j.jcmg.2011.03.006.
    1. Williams MC, Moss AJ, Dweck M, Adamson PD, Alam S, Hunter A, Shah ASV, Pawade T, Weir-McCall JR, Roditi G, et al. Coronary artery plaque characteristics associated with adverse outcomes in the SCOT-HEART study. J Am Coll Cardiol. 2019;73:291–301. doi: 10.1016/j.jacc.2018.10.066.
    1. Dey D, Cheng VY, Slomka PJ, Nakazato R, Ramesh A, Gurudevan S, Germano G, Berman DS. Automated 3-dimensional quantification of noncalcified and calcified coronary plaque from coronary CT angiography. J Cardiovasc Comput Tomogr. 2009;3:372–382. doi: 10.1016/j.jcct.2009.09.004.
    1. Dey D, Diaz Zamudio M, Schuhbaeck A, Juarez Orozco LE, Otaki Y, Gransar H, Li D, Germano G, Achenbach S, Berman DS, et al. Relationship between quantitative adverse plaque features from coronary computed tomography angiography and downstream impaired myocardial flow reserve by 13N-ammonia positron emission tomography: a pilot study. Circ Cardiovasc Imaging. 2015;8:e003255. doi: 10.1161/CIRCIMAGING.115.003255.
    1. Newby DE, Williams MC, Flapan AD, Forbes JF, Hargreaves AD, Leslie SJ, Lewis SC, McKillop G, McLean S, Reid JH, et al. Role of multidetector computed tomography in the diagnosis and management of patients attending the rapid access chest pain clinic, The Scottish Computed Tomography of the Heart (SCOT-HEART) trial: study protocol for randomized controlled trial. Trials. 2012;13:184. doi: 10.1186/1745-6215-13-184.
    1. Newby DE, Adamson PD, Berry C, Boon NA, Dweck MR, Flather M, Forbes J, Hunter A, Lewis S, MacLean S, et al. SCOT-HEART Investigators. Coronary CT angiography and 5-year risk of myocardial infarction. N Engl J Med. 2018;379:924–933. doi: 10.1056/NEJMoa1805971.
    1. 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;385:2383–2391.
    1. Williams MC, Hunter A, Shah ASV, Assi V, Lewis S, Smith J, Berry C, Boon NA, Clark E, Flather M, et al. SCOT-HEART Investigators. Use of coronary computed tomographic angiography to guide management of patients with coronary disease. J Am Coll Cardiol. 2016;67:1759–1768. doi: 10.1016/j.jacc.2016.02.026.
    1. Woodward M, Brindle P, Tunstall-Pedoe H SIGN group on risk estimation. Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC). Heart. 2007;93:172–176. doi: 10.1136/hrt.2006.108167.
    1. Williams MC, Golay SK, Hunter A, Weir-McCall JR, Mlynska L, Dweck MR, Uren NG, Reid JH, Lewis SC, Berry C, et al. Observer variability in the assessment of CT coronary angiography and coronary artery calcium score: substudy of the Scottish COmputed Tomography of the HEART (SCOT-HEART) trial. Open Heart. 2015;2:e000234. doi: 10.1136/openhrt-2014-000234.
    1. Øvrehus KA, Schuhbaeck A, Marwan M, Achenbach S, Nørgaard BL, Bøtker HE, Dey D. Reproducibility of semi-automatic coronary plaque quantification in coronary CT angiography with sub-mSv radiation dose. J Cardiovasc Comput Tomogr. 2016;10:114–120. doi: 10.1016/j.jcct.2015.11.003.
    1. Matsumoto H, Watanabe S, Kyo E, Tsuji T, Ando Y, Otaki Y, Cadet S, Gransar H, Berman DS, Slomka P, et al. Standardized volumetric plaque quantification and characterization from coronary CT angiography: a head-to-head comparison with invasive intravascular ultrasound. Eur Radiol. 2019;29:6129–6139. doi: 10.1007/s00330-019-06219-3.
    1. WOSCOPS. Computerised record linkage: compared with traditional patient follow-up methods in clinical trials and illustrated in a prospective epidemiological study. The West of Scotland Coronary Prevention Study Group. J Clin Epidemiol. 1995;48:1441–1452.
    1. Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd-Jones D, McEvoy JW, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140:e596–e646. doi: 10.1161/CIR.0000000000000678.
    1. Adamson PD, Newby DE, Hill CL, Coles A, Douglas PS, Fordyce CB. Comparison of international guidelines for assessment of suspected stable angina: insights from the PROMISE and SCOT-HEART. JACC Cardiovasc Imaging. 2018;11:1301–1310. doi: 10.1016/j.jcmg.2018.06.021.
    1. Miedema MD, Dardari ZA, Nasir K, Blankstein R, Knickelbine T, Oberembt S, Shaw L, Rumberger J, Michos ED, Rozanski A, et al. Association of coronary artery calcium with long-term, cause-specific mortality among young adults. JAMA Netw Open. 2019;2:e197440. doi: 10.1001/jamanetworkopen.2019.7440.
    1. Hadamitzky M, Täubert S, Deseive S, Byrne RA, Martinoff S, Schömig A, Hausleiter J. Prognostic value of coronary computed tomography angiography during 5 years of follow-up in patients with suspected coronary artery disease. Eur Heart J. 2013;34:3277–3285. doi: 10.1093/eurheartj/eht293.
    1. Chang HJ, Lin FY, Lee SE, Andreini D, Bax J, Cademartiri F, Chinnaiyan K, Chow BJW, Conte E, Cury RC, et al. Coronary atherosclerotic precursors of acute coronary syndromes. J Am Coll Cardiol. 2018;71:2511–2522. doi: 10.1016/j.jacc.2018.02.079.
    1. Maddox TM, Stanislawski MA, Grunwald GK, Bradley SM, Ho PM, Tsai TT, Patel MR, Sandhu A, Valle J, Magid DJ, et al. Nonobstructive coronary artery disease and risk of myocardial infarction. JAMA. 2014;312:1754–1763. doi: 10.1001/jama.2014.14681.
    1. Little WC, Constantinescu M, Applegate RJ, Kutcher MA, Burrows MT, Kahl FR, Santamore WP. Can coronary angiography predict the site of a subsequent myocardial infarction in patients with mild-to-moderate coronary artery disease? Circulation. 1988;78(5 Pt 1):1157–1166. doi: 10.1161/01.cir.78.5.1157.
    1. Boden WE, O’Rourke RA, Teo KK, Hartigan PM, Maron DJ, Kostuk WJ, Knudtson M, Dada M, Casperson P, Harris CL, et al. COURAGE Trial Research Group. Optimal medical therapy with or without PCI for stable coronary disease. N Engl J Med. 2007;356:1503–1516. doi: 10.1056/NEJMoa070829.
    1. Chang HJ, Lin FY, Lee SE, Andreini D, Bax J, Cademartiri F, Chinnaiyan K, Chow BJW, Conte E, Cury RC, et al. Coronary atherosclerotic precursors of acute coronary syndromes. J Am Coll Cardiol. 2018;71:2511–2522. doi: 10.1016/j.jacc.2018.02.079.
    1. Lee SE, Chang HJ, Rizvi A, Hadamitzky M, Kim YJ, Conte E, Andreini D, Pontone G, Volpato V, Budoff MJ, et al. Rationale and design of the Progression of AtheRosclerotic PlAque DetermIned by Computed 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;182:72–79. doi: 10.1016/j.ahj.2016.09.003.
    1. Kwiecinski J, Dey D, Cadet S, Lee SE, Tamarappoo B, Otaki Y, Huynh PT, Friedman JD, Dweck MR, Newby DE, et al. Predictors of 18F-sodium fluoride uptake in patients with stable coronary artery disease and adverse plaque features on computed tomography angiography. Eur Heart J Cardiovasc Imaging. 2020;21:58–66. doi: 10.1093/ehjci/jez152.
    1. Ihdayhid AR, Goeller M, Dey D, Nerlekar N, Yap G, Thakur U, Adams D, Cameron J, Seneviratne S, Achenbach S, et al. Comparison of coronary atherosclerotic plaque burden and composition as assessed on coronary computed tomography angiography in East Asian and European-origin Caucasians. Am J Cardiol. 2019;124:1012–1019. doi: 10.1016/j.amjcard.2019.06.020.
    1. Hell MM, Motwani M, Otaki Y, Cadet S, Gransar H, Miranda-Peats R, Valk J, Slomka PJ, Cheng VY, Rozanski A, et al. Quantitative global plaque characteristics from coronary computed tomography angiography for the prediction of future cardiac mortality during long-term follow-up. Eur Heart J Cardiovasc Imaging. 2017;18:1331–1339. doi: 10.1093/ehjci/jex183.
    1. Goeller M, Achenbach S, Cadet S, Kwan AC, Commandeur F, Slomka PJ, Gransar H, Albrecht MH, Tamarappoo BK, Berman DS, et al. Pericoronary adipose tissue computed tomography attenuation and high-risk plaque aharacteristics in acute coronary syndrome compared with stable coronary artery disease. JAMA Cardiol. 2018;3:858–863. doi: 10.1001/jamacardio.2018.1997.
    1. Oikonomou EK, Williams MC, Kotanidis CP, Desai MY, Marwan M, Antonopoulos AS, Thomas KE, Thomas S, Akoumianakis I, Fan LM, et al. A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography. Eur Heart J. 2019;40:3529–3543. doi: 10.1093/eurheartj/ehz592.

Source: PubMed

3
S'abonner