Identification of Vulnerable Plaques
Various imaging methods allow evaluation in vivo.
Vulnerable plaques are defined as nonobstructive atherosclerotic lesions that are prone to rupture, causing arterial thrombosis and leading to, for example, acute coronary syndromes (ACS) and stroke.1,2 A deep understanding of the pathophysiology of vulnerable plaque could play a key role in optimizing the prevention and treatment of arterial thrombosis, potentially reducing its morbidity and mortality. We discuss the recent advances in noninvasive and intravascular imaging that have significantly improved the ability to evaluate vulnerable plaque in vivo.3,4
Thin-cap fibroatheroma (TCFA) is defined as a lipid plaque with a fibrous cap that is < 65 µm thick and is heavily infiltrated by inflammatory cells and macrophages, indicating the important role of inflammation on plaque instability. Furthermore, neovascularization of the arterial wall caused by the proliferation of adventitial vasa vasorum may connect to intraplaque hemorrhage, which is a common feature of advanced lesions, with plaque rupture and luminal thrombi.5 It is widely recognized that TCFA rupture with subsequent thrombosis is the most common cause of ACS or sudden cardiac death.6
The second most common cause is plaque erosion, a significant substrate for coronary thrombosis, followed by calcified nodule, a less frequent entity.7 Plaque erosion is identified when serial arterial segment with thrombus fails to reveal fibrous cap rupture; typically, the endothelium is absent at the erosion site. Calcified nodule refers to a protruding eruptive dense calcified plaque with fibrous cap disruption and thrombi.8 Although pathology studies were instrumental for a broad comprehension of vulnerable plaque, the potential selection bias and the analysis of a “single snapshot” rather than having prospective longitudinal assessments largely limited the refinement of our knowledge in this setting. Noninvasive and intravascular imaging could potentially overcome these limitations.
CT angiography has been well established for evaluating coronary artery stenosis.9 It also enables the assessment of plaque characteristics, which are categorized as positive remodeling, low attenuation plaques, and spotty calcification in patients with ACS.10,11 The ring-like enhancement, another feature potentially associated with plaque rupture, has been defined as a low attenuation region with adjacent circumferential thin enhancement in a previous report by Tanaka et al.12 A subsequent study showed that the frequency of ring-like enhancement was higher in the TCFA group than in the non-TCFA group in images obtained by optical coherence tomography (OCT).13 Although CT angiography enables the evaluation of the entire coronary system in a noninvasive fashion, some limitations, such as its reduced spatial resolution compared with intravascular imaging modalities, should be taken into account.
MAGNETIC RESONANCE IMAGING
Magnetic resonance imaging (MRI) is capable of detecting features of vulnerable plaque noninvasively, such as intraplaque hemorrhage, a component of the American Heart Association’s definition of type VI plaque.14 This feature is observed as a high signal of T1-weighted imaging and has been associated with strokes of carotid origin.15,16 MRI can detect coronary artery plaques, as well.17,18 A recent study showed that the presence of coronary high-intensity plaques obtained by T1-weighted imaging was significantly associated with adverse coronary events.19 However, coronary plaque imaging using MRI has been challenging due to reduced vessel size compared with the carotids, as well as cardiac and respiratory motion.20
Intravascular ultrasound (IVUS) delivers 100-µm axial resolution images of the arterial wall. IVUS features that are associated with plaque vulnerability include the presence of an echolucent zone, calcium deposits, and positive remodeling.21,22 Yamagishi et al demonstrated that coronary sites with an acute occlusion have more echolucent zones compared with sites without acute events.22 Spotty calcium deposition is frequently observed in patients with acute myocardial infarction. Ehara et al demonstrated that the average number of calcium deposits within an arc of < 90° per patient was significantly higher in acute myocardial infarction than stable angina pectoris (SAP), and calcium deposits were significantly longer in SAP patients.23 Spotty calcifications, especially those that are deep, are frequently observed in lesions with ruptured plaque compared with lesions without ruptured plaque.24 Although positive remodeling was initially regarded as a protective process in reducing effective luminal narrowing, it has been associated with ACS.25 Prospective IVUS studies correlating vulnerable plaque features observed on IVUS with adverse cardiovascular events are warranted.
VIRTUAL HISTOLOGY IVUS
Virtual histology (VH) IVUS data are collected with a 20-MHz, 2.9-F phased-array transducer catheter that acquires ECG-gated IVUS data. Briefly, VH-IVUS uses spectral analysis of IVUS radiofrequency data to construct color-coded tissue maps that label plaque into four major components. The initial experience with VH-IVUS has shown good sensitivity, specificity, and predictive accuracy ranging from 80% to 92% in identifying the four plaque components (fibrous, fibrolipid, necrotic core, and dense calcium) compared with histology.26 TCFA identified by VH-IVUS was more prevalent in those with ACS than in stable angina patients.27
Recent longitudinal studies demonstrated that in patients mostly with stable angina, the majority of the TCFAs observed at baseline had healed at 12-month follow-up, whereas untreated nonculprit lesions in patients with ST-elevation myocardial infarction (STEMI) frequently exhibited TCFA morphology that does not change over a 13-month follow-up course.28,29 The PROSPECT study demonstrated that nonculprit lesions associated with recurrent ischemic events were more likely to be characterized by a plaque burden ≥ 70% or a minimal luminal area ≤ 4 mm2, or to be classified on the basis of VH-IVUS as TCFA.30 This was the first trial that investigated the natural history of vulnerable plaque using IVUS. Despite the definition of TCFA derived from VH-IVUS used in the PROSPECT trial, it is important to highlight that this imaging modality does not have the ability to accurately measure the thickness of the fibrous cap due to its insufficient axial resolution. Recently, the correlation between necrotic core size determined by VH-IVUS and histopathology has been questioned; therefore, further validation studies are required to completely elucidate the accuracy of VH-IVUS in detecting vulnerable plaque.31
The catheter-based near-infrared spectroscopy (NIRS) has the potential to identify and quantify lipid core plaques, as it can penetrate blood and several millimeters into the tissue. Lipid core plaques are defined as fibroatheroma > 60° in circumferential extent, > 200 µm thick, with a mean fibrous cap thickness < 450 µm.32,33 Thus, NIRS can detect lipid core plaques in a map with pullback position and degrees of circumferential extent; however, it is unable to indicate the depth of lipid core plaques. The current NIRS system is combined with IVUS as a single catheter. In a study using histopathology as the gold standard, NIRS was able to identify lipid-rich plaques more accurately than IVUS. Importantly, the combination of NIRS and IVUS was more accurate than both methods individually.34 Lipid core burden index, one of the output values from NIRS that indicates the amount of lipid in a scanned artery, and its combination with remodeling index calculated by IVUS were correlated with OCT findings of lipid plaque and TCFA.35,36 Clinically, NIRS-IVUS might predict the occurrence of periprocedural myocardial infarction during percutaneous coronary intervention by identifying extensive lipid core plaques, most likely due to embolization of plaque contents.37
In addition, Oemrawsingh et al suggested in a single-center, prospective, observational study that coronary lipid core burden index obtained by NIRS in nonculprit coronary arteries in patients with SAP and ACS has the potential to be associated with major adverse cardiac events during 1-year follow-up.38 Additional investigation is required, however, to clarify whether NIRS findings can play a role in the identification of vulnerable plaque.
Intravascular OCT is a near-infrared light-based imaging system that delivers images with 10- to 20-µm axial resolution. It therefore enables visualization of blood vessel wall microstructures in vivo at an unprecedented level of detail.39
OCT is the only imaging modality available for clinical use that is capable of measuring the fibrous cap thickness overlying a lipid plaque, therefore enabling the detection of TCFA. Kume et al demonstrated that after accounting for tissue shrinkage during histologic preparation, there is a good correlation between OCT and histologic examination in determining fibrous cap thickness (r = 0.9; P < .001).40 Importantly, fibrous cap thickness varies according to the clinical presentation, as shown by in vivo studies using OCT measurements. Patients with STEMI were found to have a considerably thinner fibrous cap in comparison with patients with non-STEMI and stable angina.41 Takarada et al demonstrated that statin therapy significantly increased the fibrous cap thickness in patients with hypercholesterolemia at 9-month follow-up.42 Furthermore, ruptured TCFA observed in the carotids has been demonstrated as a predictor of transient ischemic attack or stroke.43 Recent OCT study showed that atorvastatin therapy at 20 mg compared with 5 mg provided a greater increase in fibrous cap thickness in coronary plaques of patients with unstable angina pectoris.44 However, the current methodology for determining fibrous cap thickness is based on manual individual measurements of arbitrary points (ie, the thinnest regions determined by visual assessment), which might cause high variability and reduced accuracy (Figure 1). Besides, such one-dimensional analysis of fibrous cap thickness does not take into account the three-dimensional (3D) morphology of coronary artery disease, which largely limited the advancement of the clinical knowledge in this field.
Aiming at overcoming this important limitation of previous studies, a semiautomated method that allows comprehensive quantification of fibrous cap thickness and 3D visualization of its longitudinal and circumferential distribution along the vessel has been investigated (Figure 2). The method has been found to be highly accurate, yet more consistent than human experts.45,46 Moreover, Galon et al demonstrated that the novel OCT-based 3D quantification of the fibrous cap showed thinner fibrous cap thickness and larger areas of TCFA in nonculprit sites of STEMI compared with stable angina.47 Although the mechanisms of fibrous cap rupture remain unclear, it is possible that its mechanical stability may not only depend on a focal, thin point, but rather on the thickness of confluent regions of thin cap distributed along the plaque. Therefore, we need to further investigate in a prospective fashion whether this more comprehensive methodology to identify and quantify different fibrous cap thicknesses along the plaque may refine our ability to predict future plaque rupture and its devastating consequences.
Macrophage infiltration in the fibrous cap plays an important role in the pathogenesis of plaque rupture.3 OCT is the only imaging modality that can visualize macrophages in vivo (Figure 3). Terney et al demonstrated good correlation between OCT and histologic measurements of fibrous cap macrophage density.48 Tahara et al demonstrated in murine aortas that OCT shows excellent correlation with histology in macrophage identification.49 Recently, Di Vito et al demonstrated that OCT was able to identify and quantify macrophage presence in coronary artery specimens using tissue property indexes (sensitivity of 100% and specificity of 96.8%).50 Although the identification of fibrous cap inflammation in vivo by OCT still lacks correlation with clinical outcomes, Galon et al demonstrated more inflammation in the fibrous cap of nonculprit lesions of STEMI compared with stable angina patients.47
Neovascularization is a common feature of vulnerable plaque. The high resolution of OCT enables the detection of neovascularization in vivo. Kitabata et al showed that the high-sensitivity C-reactive protein levels in the neovascularization group were significantly greater than those in the non-neovascular group.51 Tian et al showed that in patients with ACS, culprit plaques with neovascularization had vulnerable features such as thinner fibrous cap, greater lipid arc, longer lipid core length, and more frequent TCFA compared with those without neovascularization.52 Kato et al demonstrated that neovascularization was more frequently located close to the lumen in patients with ACS compared with non-ACS.53
Erosion and Calcified Nodules
OCT has the ability to distinguish the etiology of coronary thrombosis. OCT-derived erosion is defined as the absence of fibrous cap disruption and the presence of thrombus. Calcified nodule is defined as fibrous cap disruption detected over a protruding, superficial calcified plaque. Jia et al demonstrated in patients with ACS that 31% of the lesions were classified as erosion and 8% as calcified nodules.54 Furthermore, calcified nodules were also observed by OCT in unstable carotid plaques.43 However, OCT has some limitations to distinguish the etiology of acute coronary thrombosis. First, the definitions of plaque erosion and calcified nodule as detected by OCT were not validated by pathology. Second, the presence of (red) thrombus overlying the culprit lesion might preclude the ability to estimate plaque characteristics. Finally, OCT does not have sufficient resolution to detect a single layer of endothelium; therefore, the pathologic definition of plaque erosion cannot be directly applied to OCT.
Although several imaging modalities have been investigated for the detection of morphologic aspects of vulnerable plaque in vivo with promising results, a precise prediction of which plaques will cause future adverse events is still lacking. Although OCT seems to be the most suitable imaging system in this setting due to its high resolution and unique ability to measure fibrous cap thickness, neovascularization, and inflammation, potential methodologic limitations observed in the majority of the studies that utilized OCT as reference might have precluded a better understanding of this complex scenario. A recent methodology that accounts for the 3D nature of atherosclerosis distribution might shed light on this topic in future prospective studies.
Daisuke Nakamura, MD, is with Harrington Heart and Vascular Institute, University Hospitals Case Medical Center, Case Western Reserve University in Cleveland, Ohio. He has stated that he has no financial interests related to this article.
Setsu Nishino, MD, PhD, is with Harrington Heart and Vascular Institute, University Hospitals Case Medical Center, Case Western Reserve University in Cleveland, Ohio. He has stated that he has no financial interests related to this article.
Guilherme F. Attizzani, MD, is with Harrington Heart and Vascular Institute, University Hospitals Case Medical Center, Case Western Reserve University in Cleveland, Ohio. He has disclosed that he has financial relationships with Medtronic, St. Jude Medical, and Edwards Lifesciences.
Hiram G. Bezerra, MD, PhD, is with Harrington Heart and Vascular Institute, University Hospitals Case Medical Center, Case Western Reserve University in Cleveland, Ohio. He has disclosed that he has financial relationships with Cardiokinetix, St. Jude Medical, and Edwards Lifesciences.
Marco A. Costa, MD, PhD, is with Harrington Heart and Vascular Institute, University Hospitals Case Medical Center, Case Western Reserve University in Cleveland, Ohio. He has disclosed that he has financial relationships with Cardiokinetix, Abbott Vascular, St. Jude Medical, Edwards Lifesciences, Boston Scientific, and Medtronic. Dr. Costa may be reached at firstname.lastname@example.org.
1. Schaar JA, Muller JE, Falk E, et al. Terminology for high-risk and vulnerable coronary artery plaques. Report of a meeting on the vulnerable plaque, June 17 and 18, 2003, Santorini, Greece. Eur Heart J. 2004;25:1077-1082.
2. Spagnoli LG, Mauriello A, Snagiorgi G, et al. Extracranial thrombotically active carotid plaque as a risk factor for ischemic stroke. JAMA. 2004;292:1845-1852.
3. Braunwald E. Noninvasive detection of vulnerable coronary plaques: locking the barn door before the horse is stolen. J Am Coll Cardiol. 2009;54:58-59.
4. Mintz GS. Clinical utility of intravascular imaging and physiology in coronary artery disease. J Am Coll Cardiol. 2014;64:207-222.
5. Virmani R, Burke AP, Farb A, et al. Pathology of the vulnerable plaque. J Am Coll Cardiol. 2006;47(suppl 8):
6. Fuster V, Badimon L, Badimon JJ, Chesebro JH. The pathogenesis of coronary artery disease and the acute coronary syndromes. N Engl J Med. 1992;326:242-250.
7. Farb A, Burke AP, Tang AL, et al. Coronary plaque erosion without rupture into a lipid core. A frequent cause of coronary thrombosis in sudden coronary death. Circulation. 1996;93:1354-1363.
8. Virmani R, Kolodgie FD, Burke AP, et al. Lessons from sudden coronary death: a comprehensive morphological classification scheme for atherosclerotic lesions. Arterioscler Thromb Vasc Biol. 2000;20:1262-1275.
9. Voros S, Rinehart S, Qian Z, et al. Coronary atherosclerosis imaging by coronary CT angiography: current status, correlation with intravascular interrogation and meta-analysis. JACC Cardiovasc Imaging. 2011;4:537-548.
10. 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.
11. Motoyama S, Sarai M, Harigaya H, et al. Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome. J Am Coll Cardiol. 2009;54:49-57.
12. Tanaka A, Shimada K, Yoshida K, et al. Non-invasive assessment of plaque rupture by 64-slice multidetector computed tomography—comparison with intravascular ultrasound. Circ J. 2008;72:1276-1281.
13. Kashiwagi M, Tanaka A, Kitabata H, et al. Feasibility of noninvasive assessment of thin-cap fibroatheroma by multidetector computed tomography. JACC Cardiovasc Imaging. 2009;2:1412-1419.
14. Stary HC, Chandler AB, Dinsmore RE, et al. A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis. Circulation. 1995;92:1355-1374.
15. McNally JS, Kim SE, Yoon HC, et al. Carotid magnetization-prepared rapid acquisition with gradient-echo signal is associated with acute territorial cerebral ischemic events detected by diffusion-weighted MRI. Circ Cardiovasc Imaging. 2012;5:376-382.
16. Yamada N, Higashi M, Otsubo R, et al. Association between signal hyperintensity on T1-weighted MR imaging of carotid plaques and ipsilateral ischemic events. AJNR Am J Neuroradiol. 2007;28:287-292.
17. Maintz D, Ozgun M, Hoffmeier A, et al. Selective coronary artery plaque visualization and differentiation by contrast-enhanced inversion prepared MRI. Eur Heart J. 2006;27:1732-1736.
18. Yeon SB, Sabir A, Clouse M, et al. Delayed-enhancement cardiovascular magnetic resonance coronary artery wall imaging: comparison with multislice computed tomography and quantitative coronary angiography. J Am Coll Cardiol. 2007;50:441-447.
19. Noguchi T, Kawasaki T, Tanaka A, et al. High-intensity signals in coronary plaques on noncontrast T1-weighted magnetic resonance imaging as a novel determinant of coronary events. J Am Coll Cardiol. 2014;63:989-999.
20. Nikolaou K, Alkadhi H, Bamberg F, et al. MRI and CT in the diagnosis of coronary artery disease: indications and applications. Insights Imaging. 2011;2:9-24.
21. Huang H, Virmani R, Younis H, et al. The impact of calcification on the biomechanical stability of atherosclerotic plaques. Circulation. 2001;103:1051-1056.
22. Yamagishi M, Terashima M, Awano K, et al. Morphology of vulnerable coronary plaque: insights from follow-up of patients examined by intravascular ultrasound before an acute coronary syndrome. J Am Coll Cardiol. 2000;35:106-111.
23. 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.
24. Fujii K, Carlier SG, Mintz G, et al. Intravascular ultrasound study of patterns of calcium in ruptured coronary plaques. Am J Cardiol. 2005;96:352-357.
25. 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.
26. Nair A, Kuban BD, Tuzcu EM, et al. Coronary plaque classification with intravascular ultrasound radiofrequency data analysis. Circulation. 2002;106:2200-2206.
27. Rodriguez-Granillo GA, Garcia-Garcia HM, Mc Fadden 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.
28. Kubo T, Maehara A, Mintz GS, et al. The dynamic nature of coronary artery lesion morphology assessed by serial virtual histology intravascular ultrasound tissue characterization. J Am Coll Cardiol. 2010;55:1590-1597.
29. Zhao Z, Wizenbichler B, Mintz GS, et al. Dynamic nature of nonculprit coronary artery lesion morphology in STEMI: a serial IVUS analysis from the HORIZONS-AMI trial. JACC Cardiovasc Imaging. 2013;6:86-95.
30. Stone GW, Maehara A, Lansky AJ, et al. A prospective natural-history study of coronary atherosclerosis. N Engl J Med. 2011;364:226-235.
31. Thim T, Hagensen MK, Wallace-Bradley D, et al. Unreliable assessment of necrotic core by virtual histology intravascular ultrasound in porcine coronary artery disease. Circ Cardiovasc Imaging. 2010;3:384-391.
32. Gardner CM, Tan H, Hull EL, et al. Detection of lipid core coronary plaques in autopsy specimens with a novel catheter-based near-infrared spectroscopy system. JACC Cardiovasc Imaging. 2008;1:638-648.
33. Waxman S, Dixon SR, L’Allier P, et al. In vivo validation of a catheter-based near-infrared spectroscopy system for detection of lipid core coronary plaques: initial results of the SPECTACL study. JACC Cardiovasc Imaging. 2009;2:858-868.
34. Kang SJ, Mintz GS, Pu J, et al. Combined IVUS and NIRS detection of fibroatheromas: histopathological validation in human coronary arteries. JACC Cardiovasc Imaging. 2015;8:184-194.
35. Yonetsu T, Suh W, Abtahian F, et al. Comparison of near-infrared spectroscopy and optical coherence tomography for detection of lipid. Catheter Cardiovasc Interv. 2014;84:710-717.
36. Roleder T, Kovacic JC, Ali Z, et al. Combined NIRS and IVUS imaging detects vulnerable plaque using a single catheter system: a head-to-head comparison with OCT. EuroIntervention. 2014;10:303-311.
37. Goldstein JA, Maini B, Dixon SR, et al. Detection of lipid-core plaques by intracoronary near-infrared spectroscopy identifies high risk of periprocedural myocardial infarction. Circ Cardiovasc Interv. 2011;4:429-437.
38. Oemrawsingh RM, Cheng JM, García-García HM, et al. Near-infrared spectroscopy predicts cardiovascular outcome in patients with coronary artery disease. J Am Coll Cardiol. 2014;64:2510-2518.
39. Bezerra HG, Costa MA, Guagliumi G, et al. Intracoronary optical coherence tomography: a comprehensive review clinical and research applications. JACC Cardiovasc Interv. 2009;2:1035-1046.
40. Kume T, Akasaka T, Kawamoto T, et al. Measurement of the thickness of the fibrous cap by optical coherence tomography. Am Heart J. 2006;152:755.e1-4
41. Jang IK, Tearney GJ, MacNeill B, et al. In vivo characterization of coronary atherosclerotic plaque by use of optical coherence tomography. Circulation. 2005;111:1551-1555.
42. Takarada S, Imanishi T, Ishibashi K, et al. The effect of lipid and inflammatory profiles on the morphological changes of lipid-rich plaques in patients with non–ST-segment elevated acute coronary syndrome: follow-up study by optical coherence tomography and intravascular ultrasound. JACC Cardiovasc Interv. 2010;3:766-772.
43. Jones MR, Attizzani GF, Given CA 2nd, et al. Intravascular frequency-domain optical coherence tomography assessment of carotid artery disease in symptomatic and asymptomatic patients. JACC Cardiovasc Interv. 2014;7:674-684.
44. Komukai K, Kubo T, Akasaka T, et al. Effect of atorvastatin therapy on fibrous cap thickness in coronary atherosclerotic plaque as assessed by optical coherence tomography. J Am Coll Cardiol. 2014;64:2207-2217.
45. Wang Z, Chamie D, Bezerra HG, et al. Volumetric quantification of fibrous caps using intravascular optical coherence tomography. Biomed Opt Express. 2012;3:1413-1426.
46. Bezerra HG, Attizzani GF, Costa MA. Three-dimensional imaging of fibrous cap by frequency-domain optical coherence tomography. Catheter Cardiovasc Interv. 2013;81:547-549.
47. Galon MZ, Wang Z, Bezerra HG, et al. Differences determined by optical coherence tomography volumetric analysis in non-culprit lesion morphology and inflammation in ST-segment elevation myocardial infarction and stable angina pectoris patients. Catheter Cardiovasc Interv. 2015;85:E108-115.
48. Terney GJ, Yavushita H, Hoiser SL, et al. Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography. Circulation. 2003;107:113-119.
49. Tahara S, Morooka T, Wang Z, et al. Intravascular optical coherence tomography detection of atherosclerosis and inflammation in murine aorta. Arterioscler Thromb Vasc Biol. 2012;32:1150-1157.
50. Di Vito L, Agozzino M, Prati F, et al. Identification and quantification of macrophage presence in coronary atherosclerotic plaques by optical coherence tomography [published online ahead of print January 14, 2015]. Eur Heart J Cardiovasc Imaging.
51. Kitabata, H, Tanaka, A, Kubo T, et al. Relation of microchannel structure identified by optical coherence tomography to plaque vulnerability in patients with coronary artery disease. Am J Cardiol. 2010;105:1673-1678.
52. Tian J, Hou J, Xing L, et al. Significance of intraplaque neovascularization for vulnerability: optical coherence tomography study. Heart. 2012;98:1504-1509.
53. Kato K, Yonetsu T, Jang IK et al. Nonculprit plaques in patients with acute coronary syndromes have more vulnerable features compared with those with non-acute coronary syndromes; 3-vessel optical coherence tomography study. Circ Cardiovasc Imaging. 2012:5;433-440.
54. Jia H, Abtahian F, Aguirre AD, et al. In vivo diagnosis of plaque erosion and calcified nodule in patients with acute coronary syndrome by intravascular optical coherence tomography. J Am Coll Cardiol. 2013:62:1748-1758.