Coronary Plaque Imaging with Multi-Slice Computed Tomographic Angiography and Intravascular Ultrasound (Full title below)

Coronary Plaque Imaging with Multi-Slice Computed Tomographic Angiography and Intravascular Ultrasound: A Close Look Inside and Out

The most important cause of morbidity and mortality in the United States and worldwide is atherosclerosis.1 Currently, clinical guidelines for risk stratification are based on the Framingham Risk Score (FRS). However, it has recently been shown that atherosclerosis imaging, for example, coronary artery calcium (CAC) scoring, is independent of, and additive to, the FRS in predicting major cardiovascular events.2 Atherosclerosis is the result of complex interactions between genetic factors and the environment; genetic predisposition can be assessed by evaluating family history and specific genotypes. Phenotyping is typically performed by evaluating the atherogenic milieu through lipoprotein analysis and measuring indicators of inflammation, but since atherosclerosis also requires the presence of a susceptible vessel wall, ultimate phenotyping is performed through atherosclerosis imaging. Atherosclerosis: Targets for Imaging Atherosclerosis is initiated and propagated by the deposition of atherogenic (i.e., apo-B-containing) particles and by the ensuing inflammatory process, while apo-A-containing particles (i.e., HDL particles) are protective. Biochemical factors lead to specific geometric and compositional changes that can be detected by imaging modalities and culminate in the Glagov phenomenon, or the “positive remodeling” process. Initial progression of the plaque occurs in an outward fashion without luminal compromise until plaque burden reaches approximately 40% of the vessel area; after this, further plaque deposition results in progressive luminal narrowing. Hemodynamic and Morphologic Paradigms Currently, cardiovascular care is based on the hemodynamic paradigm, in which a large coronary atherosclerotic plaque causing significant obstruction and hypoperfusion of the myocardium will lead to symptoms of ischemia.3 This paradigm has been the framework of our therapeutic approaches to chronic stable angina, acute coronary syndromes (ACS) and acute myocardial infarction (AMI). However, disruption of a nonobstructive atherosclerotic plaque is the culprit in at least two-thirds of acute coronary events.4,5 The histopathology of such ruptured plaques demonstrates large plaque volume with a large necrotic core covered by a thin fibrous cap (thin-cap fibroatheroma [TCFA]), where the thickness of the fibrous cap is 65 µm or less.6 Therefore, while severe anatomic stenosis can lead to symptoms of ischemia, plaque composition of nonobstructive lesions may identify “at-risk” lesions for future cardiovascular events, introducing the concept of the “morphologic paradigm.” Multiple invasive methods, such as intravascular ultrasound (IVUS),7 IVUS with radiofrequency signal analysis (“virtual histology” or “VH”),8 optical coherence tomography (OCT)9 and near-infrared spectroscopy,10 have been developed to characterize atherosclerotic plaques and eventually may be helpful in identifying unstable plaques prospectively. Through IVUS characterization, ruptured plaques were found to be positively remodeled at the site of plaque disruption and small areas of calcification within the fibrous cap were shown to contribute to plaque instability.11,12 Other studies utilizing IVUS have characterized culprit plaques in patients with ACS by the presence of thrombus, a small residual vessel lumen, greater plaque burden and more pronounced positive remodeling.13–16 When characterized by histopathology, TCFAs are very similar to lesions that sustained plaque rupture. Histopathologic characteristics of TCFAs include a necrotic core with a thin cap infiltrated by macrophages.6 Generally, TCFAs have smaller necrotic cores (24 ± 17% vs. 34 ± 17%), less macrophage infiltration of the fibrous cap (14 ± 10% vs. 26 ± 20%), a decreased number of cholesterol clefts (8 ± 9 vs.12 ± 12) and less calcification compared to ruptured plaques.6 IVUS with radiofrequency backscatter analysis (IVUS-RF) has been developed for clinical use to identify plaques that may be vulnerable to rupture. VH-TCFAs are characterized as plaques without evidence of a thick cap (i.e., 10% in ≥ 3 consecutive frames.17 Coronary artery calcification (CAC) measurement is an important noninvasive modality for the assessment of coronary artery disease (CAD) in the primary prevention setting. This is a low-radiation, computed tomography (CT)-based method that quantifies calcium in the coronary vasculature and hence gives an assessment of overall coronary atherosclerotic burden. However, calcified plaque only represents approximately 20% of the total plaque volume and may not be present in early atherosclerotic disease. In addition to diagnosing CAD, CAC provides prognostic information as well. Spotty regions of calcification are associated with a worse prognosis and mortality increases with increasing numbers of coronary artery involvement.18 While CAC has been shown to correlate with the presence of obstructive CAD, there is much work to be done to improve the detection of noncalcified plaque (NCP).19 We have shown that 8.2% of symptomatic patients with a zero calcium score had a greater than 70% stenosis comprised of NCP, whereas no obstructive disease was seen in asymptomatic patients in the absence of coronary calcium.19 Multi-Slice Computed Tomography (MSCT) Stenosis detection. MSCT has become an increasingly utilized noninvasive imaging modality for the detection of CAD. Using invasive X-ray angiography as a reference, MSCT has been shown to be quite accurate in the detection of coronary arterial stenoses.20 In a meta-analysis of 40 studies, MSCT had high sensitivity and negative predictive value (NPV) for patient-based detection of CAD (99% and 100%, respectively).20 Specificity and positive predictive value (PPV) for patient-based detection of CAD were 89% and 93%, respectively. Semiquantitative plaque analysis. In addition to luminal stenosis detection, MSCT has been utilized for plaque detection and quantification as well. A semiquantitative scoring system based on the 16-segment coronary arterial model has been shown to be quite reproducible with prognostic significance as well.21 Each segment is evaluated for the presence of stenosis (typically described as none, mild, moderate or severe), and plaque is classified based on visual assessment of composition (none, calcified, noncalcified and mixed plaque) (Figure 1). Semiquantitative plaque analysis and outcomes. While MSCT has been shown to have good correlation with invasive coronary angiography, the question of outcomes and prognostic value has remained elusive. Van Werkhoven et al recently found that MSCT is an independent predictor of events and has incremental prognostic value when added to myocardial perfusion imaging. Event rates in patients with nonsignificant CAD ( 50% stenosis).22 When MSCT has excluded obstructive CAD (> 50%), there is a very high NPV for cardiac events over the following 18 months and the event rate is actually lower than the rate predicted by the FRS.23 Pundziute et al demonstrated that in subjects with high pre-test probability, normal coronary arteries by MSCT were associated with an excellent prognosis (0% event rate) compared to a 30% event rate in subjects with either nonobstructive or obstructive (≥ 50% stenosis) CAD. Independent predictors of cardiac events by MSCT included the presence of coronary plaques, obstructive CAD (in particular, obstructive disease in the left main and left anterior descending arteries), number of coronary segments with plaques, number of coronary segments with obstructive plaques and number of coronary segments with mixed plaques.24 Van Werkhoven et al found that NCP was an independent predictor of events.22 Quantitative plaque analysis. There is much promise for the use of MSCT because of its noninvasive nature and, given its good low-contrast resolution, it may be used for quantitative plaque characterization. Accordingly, our laboratory has developed a highly standardized, quantitative approach, which demonstrated more consistent results in distal arterial segments when compared to semiquantitative analysis.3 This quantitative approach also demonstrated that findings of both geometric and plaque parameters were highly reproducible (Table 1). Quantitative plaque geometry. Retrospective studies utilizing IVUS have demonstrated that plaques associated with cardiac events have higher plaque volume and higher lipid content. Percent atheroma volume (PAV), which is calculated as: [total vessel area - lumen area / total vessel area] x 100, has been commonly used in IVUS-based regression trials. We have recently demonstrated that similar to IVUS, the evaluation of PAV by MSCT between two observers is quite reproducible in all coronary segments (CCC = 0.96) as well as in coronary plaques (CCC = 0.92), with a percent standard deviation (SD) of 13.9%, which is similar to SD for IVUS measurements (Figure 2). This is inherently important because of the potential use of MSCT as an imaging endpoint in clinical studies evaluating the efficacy of therapeutic approaches for the treatment of atherosclerosis. Quantitative analysis can be performed in normal coronary arterial segments as well as in coronary segments with significant plaque. We have shown that MSCT can not only demonstrate differences between entirely normal coronary arterial segments and segments containing plaque, but also can detect early vessel wall thickening with preserved luminal size in subjects with an elevated FRS compared to those with a low FRS.3 PAV and remodeling index (RI) were significantly higher in patients with an elevated FRS.3 Quantitative analysis of plaque composition. Coronary angiography enables cardiologists to accurately quantify arterial stenoses, but is limited to the evaluation of “negatively remodeled” vessels and is unable to determine plaque composition. IVUS is considered the gold standard for the visualization of the coronary arterial wall, but is invasive and expensive. MSCT has recently been validated against IVUS and was able to correctly detect 96.6% of segments with NCP, 92.6% of segments with calcified plaque and 90.1% of segments without evidence of atherosclerosis.25 Sensitivity, specificity, PPV and NPV for detection of plaques by MSCT were 97.4%, 90.1%, 89.7% and 97.5%, respectively.25 However, the main limitation of MSCT remains the differentiation among subtypes of noncalcified plaques. Brodoefel recently demonstrated that a Hounsfield Unit (HU)-based analysis provides accurate quantification of coronary plaque volume with improved interobserver reproducibility. However, there was no correlation between the percentage of each plaque component on MSCT versus IVUS-VH.26 Visual estimation of plaque volume was considerably overestimated compared to IVUS. However, our laboratory has recently developed techniques to coregister IVUS with MSCT, which may improve accuracy (Figure 3). MSCT with stable angina and acute coronary syndrome. Today, a major question for cardiologists is how to determine if a nonobstructive lesion is vulnerable for rupture. A study completed by Hoffman et al evaluated plaque composition in culprit and stable lesions in ACS and stable lesions in patients with stable angina.27 They found that NCP was always present in culprit lesions and that although both unstable and stable lesions had mixed plaque, the absence of calcified plaque was very rare in stable lesions, but was frequent in culprit lesions.27 They also demonstrated that the total vessel area and RI were significantly higher in plaques associated with ACS compared to plaques in individuals with stable angina (21.2 ± 7.0 mm² vs. 11.8 ± 5.7 mm²; p Intravascular Ultrasound (IVUS) Gray-scale IVUS. IVUS gray-scale images are utilized by interventional cardiologists to help quantify and characterize plaque burden in coronary arteries. Areas on IVUS that appear bright and homogeneous are classified as calcified and dense fibrous plaques, whereas areas of low echo reflectance are characterized as “soft” or “mixed” plaques.30 However, visual differentiation of plaque components using gray-scale IVUS is difficult, thus quantification of plaque components is typically inaccurate. IVUS with radiofrequency backscatter analysis (IVUS-RF). Analysis of plaque composition with IVUS has further evolved with the addition of radiofrequency (RF) backscatter analysis (IVUS-RF or “VH-IVUS”). Spectral analysis of the RF signal provides a more detailed assessment of tissue characteristics and pixels are identified as one of four major plaque components: fibrous, fibro-fatty, necrotic core and dense calcified plaque. Analysis of the lesion typically begins at the frame with the minimum luminal area (MLA) and extends proximally and distally until plaque burden is From the Piedmont Heart Institute, Atlanta, Georgia. Disclosure: Dr. Voros has received research grants from Volcano Corp., Siemens Medical, and Toshiba America Medical Systems. Manuscirpt submitted June 2, 2009 and final version accepted June 10, 2009. Address for correspondence: Szilard Voros, MD, FACC, 1968 Peachtree Road, N.W., Atlanta, GA 30309. E-mail: szilard.voros@piedmont.org

1. World Health Report 2002: Available at. http://www.worldheart.org. 2007. Ref Type: Online Source

2. Greenland P, LaBree L, Azen SP, et al. Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA 2004;291:210–215.

3. Akram K, Rinehart S, Voros S. Coronary arterial atherosclerotic plaque imaging by contrast-enhanced computed tomography: Fantasy or reality? J Nucl Cardiol 2008;15:818–829.

4. Davies M. The composition of coronary-artery plaques. N Engl J Med 1997;336:1312–1314.

5. Burke AP, Farb A, Malcom GT, et al. Coronary risk factors and plaque morphology in men with coronary disease who died suddenly. N Engl J Med 1997;336:1276–1282.

6. Virmani R, Burke AP, Farb A, Kolodgie FD. Pathology of the vulnerable plaque. J Am Coll Cardiol 2006;47:C13–C18.

7. Schoenhagen P, Sapp SK, Tuzcu EM, et al. Variability of area measurements obtained with different intravascular ultrasound catheter systems: Impact on clinical trials and a method for accurate calibration. J Am Soc Echocardiogr 2003;16:277–284.

8. Moore MP, Spencer T, Salter DM, et al. Characterisation of coronary atherosclerotic morphology by spectral analysis of radiofrequency signal: In vitro intravascular ultrasound study with histological and radiological validation. Heart 1998;79:459–467.

9. Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography. Science 1991;254:1178–1181.

10. Caplan JD, Waxman S, Nesto RW, Muller JE. Near-infrared spectroscopy for the detection of vulnerable coronary artery plaques. J Am Coll Cardiol 2006;47(8 Suppl):C92–C96.

11. Schoenhagen P, Ziada KM, Kapadia SR, et al. Extent and direction of arterial remodeling in stable vsersus unstable coronary syndromes: An intravascular ultrasound study. Circulation 2000;101:598–603.

12. Hassani SE, Mintz GS, Fong HS, et al. Negative remodeling and calcified plaque in octogenarians with acute myocardial infarction: An intravascular ultrasound analysis. J Am Coll Cardiol 2006;47:2413–2419.

13. Sano K, Kawasaki M, Ishihara Y, et al. Assessment of vulnerable plaques causing acute coronary syndrome using integrated backscatter intravascular ultrasound. J Am Coll Cardiol 2006;47:734–741.

14. Nakamura M, Nishikawa H, Mukai S, et al. Impact of coronary artery remodeling on clinical presentation of coronary artery disease: An intravascular ultrasound study. J Am Coll Cardiol 2001;37:63–69.

15. Ehara S, Kobayashi Y, Yoshiyama M, et al. Spotty calcification typifies the culprit plaque in patients with acute myocardial infarction: An intravascular ultrasound study. Circulation 2004;110:3424–3429.

16. Maehara A, Mintz GS, Bui AB, et al. Morphologic and angiographic features of coronary plaque rupture detected by intravascular ultrasound. J Am Coll Cardiol 2002;40:904–910.

17. Voros S. Can Computed Tomography Angiography of the Coronary Arteries Characterize Atherosclerotic Plaque Composition? Is the CAT (Scan) Out of the Bag? J Am Coll Cardiol Intv 2008;1:183–185.

18. Williams M, Shaw LJ, Raggi P, et al. Prognostic value of number and site of calcified coronary lesions compared with the total score. JACC Cardiovasc Imaging 2008;1:61–66.

19. Akram K, O’Donnell RE, King S, et al. Influence of symptomatic status on the prevalence of obstructive coronary artery disease in patients with zero calcium score. Atherosclerosis 2009;203:533–537.

20. Mowatt G, Cook JA, Hillis GS, et al. 64-Slice computed tomography angiography in the diagnosis and assessment of coronary artery disease: Systematic review and meta-analysis. Heart 2008;94:1386–1393.

21. Min JK, Shaw LJ, Devereux RB, et al. Prognostic value of multidetector coronary computed tomographic angiography for prediction of all-cause mortality. J Am Coll Cardiol 2007;50:1161–1170.

22. van Werkhoven J, Schuijf J, Gaemperli O, et al. Prognostic value of multislice computed tomography and gated single-photon emission computed tomography in patients with suspected coronary artery disease. J Am Coll Cardiol 2009;53:623–632.

23. Hadamitzky M, Freismith B, Meyer T, et al. Prognostic value of coronary computed tomographic angiography for prediction of cardiac events in patients with suspected coronary artery disease. JACC Cardiovasc Imaging 2009;2:404–411.

24. Pundziute G, Schuijf J, Jukema J, et al. Prognostic value of multislice computed tomography coronary angiography in patients with known or suspected coronary artery disease. J Am Coll Cardiol 2007;49:62–70.

25. Sun J, Zhang Z, Lu B, et al. Identification and quantification of coronary atherosclerotic plaques: A comparison of 64-MDCT and intravascular ultrasound. Am J Roentgenol 2008;190:748–754.

26. Brodoefel H, Reimann A, Heuschmid M, et al. Characterization of coronary atherosclerosis by dual-source computed tomography and HU-based color mapping: A pilot study. Eur Radiol 2008;18:2466–2474.

27. Hoffmann U, Moselewski F, Nieman K, et al. 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 2006;47:1655–1662.

28. Motoyama S, Kondo T, Sarai M, et al. Multislice computed tomographic characteristics of coronary lesions in acute coronary syndromes. J Am Coll Cardiol 2007;50:319–326.

29. Schmid M, Achenbach S, Ropers D, et al. Assessment of changes in non-calcified atherosclerotic plaque volume in the left main and left anterior descending coronary arteries over time by 64-slice computed tomography. Am J Cardiol 2008;101:579–584.

30. Nair A, Kuban BD, Tuzcu EM, et al. Coronary plaque classification with intravascular ultrasound radiofrequency data analysis. Circulation 2002;106:2200–2206.

31. Mehta SK, McCrary JR, Frutkin AD, et al. Intravascular ultrasound radiofrequency analysis of coronary atherosclerosis: An emerging technology for the assessment of vulnerable plaque. Eur Heart J 2007;28:1283–1288.

32. van Mieghem CA, McFadden EP, de Feyter PJ, et al. Noninvasive detection of subclinical coronary atherosclerosis coupled with assessment of changes in plaque characteristics using novel invasive imaging modalities: The Integrated Biomarker and Imaging Study (IBIS). J Am Coll Cardiol 2006;47:1142.

33. Schaar JA, van der Steen AFW, Mastik F, et al. Intravascular palpography for vulnerable plaque assessment. J Am Coll Cardiol 2006;47:C91.

34. Nishimura RA, Edwards WD, Warnes CA, et al. Intravascular ultrasound imaging: In vitro validation and pathologic correlation. J Am Coll Cardiol 1990;16:145–154.

35. White JA, Pflugfelder PW, Boughner DR, Kostuk WJ. Validation of a three-dimensional intravascular ultrasound imaging technique to assess atherosclerotic burden: Potential for improved assessment of cardiac allograft coronary artery disease. Can J Cardiol 2003;19:1147–1153.

36. Prati F, Arbustini E, Labellarte A, et al. Correlation between high frequency intravascular ultrasound and histomorphology in human coronary arteries. Heart 2001;85:567–570.

37. Nair A, Margolis MP, Kuban BD, Vince DG. Automated coronary plaque characterisation with intravascular ultrasound backscatter: Ex vivo validation. EuroInterv 2007;3:113–120.

38. Diethrich EB, Margolis P, Reid DB, et al. Virtual histology intravascular ultrasound assessment of carotid artery disease: The Carotid Artery Plaque Virtual Histology Evaluation (CAPITAL) study. J Endovasc Ther 2007;14:676–686.

39. Granada JF, Wallace-Bradley D, Win HK, et al. In vivo plaque characterization using intravascular ultrasound-virtual histology in a porcine model of complex coronary lesions. Arterioscler Thromb Vasc Biol 2007;27:387–393.

40. Yamagishi M, Terashima M, Awano K, et al. Morphology of vulnerable coronary plaque: Insights from follow-up of patients examined by intravascular ultrasound beore an acute coronary syndrome. J Am Coll Cardiol 2000; 35:106–111.

41. Varnava AM, Mills PG, Davies MJ. Relationship between coronary artery remodeling and plaque vulnerability. Circulation 2002;105:939–943.

42. Rodriguez-Granillo GA, Garcia-Garcia HM, McFadden EP, et al. In vivo intravascular ultrasound-derived thin-cap fibroatheroma detection using ultrasound radiofrequency data analysis. J Am Coll Cardiol 2005;46:2038–2042.

43. Choi SH, Chae A, Miller E, et al. Relationship between biomarkers of oxidized low-density lipoprotein, statin therapy, quantitative coronary angiography, and atheroma volume. J Am Coll Cardiol 2008;52:24–32.

44. Nissen SE, Tuzcu EM, Libby P, et al; CAMELOT Investigators. Effect of antihypertensive agents on cardiovascular events in patients with coronary disease and normal blood pressure: The CAMELOT study: A randomized controlled trial. JAMA 2004;292:2217–2225.

45. Chhatriwalla AK, Nicholls SJ, Wang TH, et al. Low levels of low-density lipoprotein cholesterol and blood pressure and progression of coronary atherosclerosis. J Am Coll Cardiol 2009;31:1110–1115.

46. Nicholls SJ, Tuzcu EM, Sipahi I, et al. Relationship between atheroma regression and change in lumen size after infusion of apolipoprotein A-I Milano. J Am Coll Cardiol 2006;47:992–997.

47. Nicholls SJ, Tuzcu EM, Sipahi I, et al. Statins, high-density lipoprotein cholesterol, and regression of coronary atherosclerosis. JAMA 2007;297:499–508.

48. Serruys PW, Garcia-Garcia HM, Buszman P, et al. Effects of the direct lipoprotein-associated phospholipase A(2) inhibitor darapladib on human coronary atherosclerotic plaque. Circulation 2008;118:1172–1182.