Technologies for Detection and Therapy of Vascular Plaques
|Inflammation and the Vulnerable Plaque (VP)
It is now well-established that atherosclerosis is an inflammatory disease(1,2). The VP is an atherosclerotic plaque that is prone to disruption, causing thrombosis, which often leads to a clinical event (3-9). Autopsy studies have demonstrated that the majority of cases of sudden death are caused by occlusive coronary thromboses that are associated with an underlying ruptured plaque (3, 10-12). From such autopsy studies, much has been learned about the morphological features that are common to VP. Those histologic characteristics include: 1- a thin fibrous cap, 2- an underlying lipid pool, and 3- an abundance of inflammatory cells.
Need For Novel Technologies To Detect Vulnerable Plaques
Even with today’s best available technology,- an unacceptably high incidence of cardiovascular events remains even after aggressive therapy (13). Novel approaches to prevent myocardial infarctions are needed.
Perhaps the most effective method to prevent MI would be to stabilize vulnerable plaque before they rupture. However, currently available systemic therapies are able to lower the risk of plaque rupture by only 20-40%, leaving the vast majority of vulnerable plaques ripe for rupture (13). As such, it is crucial that vulnerable plaques are localized such that local plaque-stabilizing therapies can be delivered. However, currently available technologies are not able to detect vulnerable plaques. This may be due to the fact that available technologies rely on identifying structural criteria to differentiate the common stable plaque from the rupture-prone vulnerable plaque. Indeed, the most commonly employed method for plaque characterization is coronary arteriography, a method which qualifies plaques based on the degree to which they impinge on and thus narrow the vessel lumen. Multiple angiographic studies that have examined ruptured plaques have found that they are most often associated with insignificant luminal narrowing prior to their rupture . Therefore, technologies that rely on identifying luminal narrowing are not able to identify vulnerable plaques with acceptable sensitivity.
Inflammation is Particularly Important in the Development and Progression of Atherothrombosis
It is now well-established that atherosclerosis is an inflammatory disease(1,2). Histopathological data confirmed the critical association of plaque inflammation and rupture. Numerous studies demonstrate an abundance of inflammatory cells (T cells and macrophages) within ruptured plaques (3-11). Moreover, several large studies have shown a strong association between inflammatory biomarkers and subsequent events(12-15).
Conventional Methods for Identifying Plaques:
The ability to identify high-risk plaque features may prove useful in predicting which plaques will rupture and cause a subsequent event. Such information may significantly refine the risk for patients already known to have disease and may identify a subset of patients at increased risk for a clinical event, who by current methodologies are classified as average-risk.
Several technologies are being studied for their ability to refine risk assessment based on identifying high-risk plaques. Intravascular ultrasound (IVUS) can accurately quantify plaque burden (16) measure distensibility of plaques(17,18), and effects of lipid lowering therapy(19,20), and distinguish fibrous, lipid, and calcified regions(21,22). However, this tool is invasive and also dangerous in the carotids and thus will be limited in its ability to be used as risk-stratifying tool. Moreover, it can not detect plaque inflammation.
Noninvasive methods to identify plaque inflammation could prove to be much more useful for following the effect of therapies and as risk stratification tools.
Multi-detector Computed Tomography (MDCT) has shown promise as a non-invasive tool, and may enable the differentiation of non-calcified lipid laden, non-calcified fibrous, and calcified plaques, based on significant differences in XRay attenuation through the tissue. (23-25). However, current MDCT technologies are not capable of identifying plaque inflammation.
Magnetic Resonance Imaging (MRI) has shown significant promise for plaque characterization, can provide information on plaque composition as well as disease burden (26-28) and can be used to monitor changes in plaque area and volume over time (29). Recent studies demonstrate that MRI can distinguish several morphological features believed to be associated with increased risk of plaque rupture. Gadolinium-enhanced MRI is capable of quantitatively measuring the dimensions of the intact fibrous cap and lipid-rich necrotic core(30-32) and preliminary clinical reports (32,33) suggest that ultrasmall superparamagnetic iron oxide (USPIO) particle-enhanced MRI can detect inflamed atherosclerotic plaques. However, there are no detailed clinical investigations focusing on MRI imaging of plaque inflammation.
Although each of these non-invasive tools has shown promise for plaque characterization, none has demonstrated reliable ability to measure plaque inflammation, which is perhaps the most important feature associated with a plaques vulnerability to rupturing. An imaging technology is needed to complement the structural and/or compositional information derived from MDCT, US, or MRI with information about plaque inflammation and biology.
Anticipated Uses Of the Intravascular Beta Ray Detector
Currently, approximately 1.3 million patients per year undergo diagnostic coronary arteriography (cardiac catheterization) while 1 million patients undergo percutaneous interventions (PCI) per year. Coronary arteriography is only modestly effective at determining future risk of MI. Indeed, given the inability of diagnostic coronary catheterization to detect inflamed, vulnerable plaques, current percutaneous interventions fail to prevent future cardiac deaths (they only improve symptoms). If successful, we propose that the intra-vascular beta probe be used as part of routine coronary angiography. In that case, the beta probe can be inserted after the diagnostic angiogram is obtained (through the existing intravascular sheath). Subsequently, PCI can be performed on the vulnerable plaques detected by the beta probe, resulting in a decrease in cardiac deaths.
Use of PET to Detect Inflamed Tissues:
Positron emission tomography (PET) may represent the most promising non-invasive imaging technology for the detection of inflammation in humans. PET imaging with 18F-Flurodeoxyglucose (FDG) has been used extensively in humans to detect metabolically active tissues such as neoplasms, autoimmune disease, and infection(34-44). Numerous studies demonstrate that FDG uptake is increased in inflamed tissues such as tumors and infectious foci(38,42,45-48). Autoradiographic studies show that FDG localizes to macrophage-dense regions within chronic inflammatory lesions (49) and within macrophages surrounding malignant foci (38,50).
Prior studies have demonstrated that 18FDG uptake is greater in inflamed tissues, such as infectious foci and tumors(38,42,45-47), than in non-inflamed tissues. More specifically, autoradiographic studies demonstrate that, in chronic inflammatory lesions(49) and malignancies(38,50), 18FDG uptake is increased in macrophage-dense regions. The relatively high uptake of 18FDG by macrophages is attributed to three main factors. First, macrophages have high metabolic rates(51), which is typically 5-20 fold higher than background tissues(37,49). Second, macrophages are unable to store glycogen, making them more reliant upon external glucose as a source of fuel for the hexose monophosphate shunt pathway(52-54). Third, the rate of glucose utilization of macrophages can increase 50-fold further when activated (55). While the mechanism for this augmentation is not well established, proposed mechanisms include an increase in glycolytic rate(42,51), and an increase in the expression and translocation of glucose transporters(54,56-59).
FDG-PET Characterization of Plaque Inflammation in Animal Models:
Several groups have demonstrated that FDG accumulates in inflamed atherosclerotic specimens in rabbit models of atherosclerosis (60-62). In a study performed with Watanabe heritable hyperlipidemic (WHHL) rabbits, Ogawa, et al. showed that 18F-FDG uptake correlate with the number of macrophages within the atherosclerotic lesions (R = 0.81, P<0001). More recently, our group demonstrated that non-invasive FDG-PET measurements correlate strongly with inflammation in experimental atherosclerotic lesions.
In that study, inflamed atherosclerotic lesions were induced in nine male New Zealand white rabbits via balloon injury of the aorto-iliac arterial segment and exposure to a high cholesterol diet. Ten rabbits fed standard chow served as controls. Three to six months following balloon injury, the rabbits were injected with FDG (1 mCi/kg) after which aortic uptake of FDG was assessed (3 hrs after injection). Biodistribution of FDG activity within aortic segments was obtained using standard well gamma counting. FDG uptake was also determined non-invasively in a subset of six live atherosclerotic rabbits and five normal rabbits, using PET imaging and measurement of standardized uptake values (SUV) over the abdominal aorta. Plaque macrophage and smooth muscle cell density were determined by planimetric analysis of RAM-11 and smooth muscle actin staining, respectively.
Co-registered PET&CT images demonstrated increased uptake of FDG in atherosclerotic aortas compared to control aortas. Further, well counter measurements of FDG uptake were significantly higher within atherosclerotic aortas compared to control aortas (P<0.001). In parallel with these findings, FDG uptake, as determined by PET, was higher in atherosclerotic aortas (0.68±0.06 vs. 0.13±0.01, SUV atherosclerotic vs. control, P<0.001). Moreover, macrophage density, assessed histologically, correlated with well-counter measurements FDG accumulation (r= 0.79, P<0.001) as well as the non-invasive in vivo (PET) measurements of FDG uptake, (r= 0.93, P<0.0001,). Importantly, FDG uptake did not correlate with either smooth muscle cell staining, vessel wall thickness, or plaque thickness of the specimens . These data show that FDG accumulates in macrophage-rich atherosclerotic plaques and demonstrate that vascular macrophage activity can quantified non-invasively with FDG-PET. As such, measurement of vascular FDG uptake with PET holds promise for the non-invasive characterization of vascular inflammation.
7. Studies in Humans Demonstrating Increased Vascular FDG Uptake:
Several groups have observed increased vascular FDG uptake in patients with diseases associated with vessel wall inflammation such as Takayasu's arteritis, giant cell arteritis, polymyalgia rheumatica and nonspecific aortitis (64-67). Others have also reported an association between atherosclerotic disease and increased FDG uptake in patients (68-70).
Rudd and colleagues demonstrated increased carotid FDG uptake in patients with evidence of a recent ischemic cerebrovascular event (71). In a related ex vivo experiment, that same group reported accumulation of deoxyglucose within macrophage-rich areas of excised human carotid arteries that were incubated with tritiated deoxyglucose (71). Recently, Davies et al reported increased FDG uptake measured by PET (co-registered with MRI), in patients with symptomatic carotid disease (72).
o1. Libby P, Ridker PM. Inflammation and atherosclerosis: role of C-Reactive protein in risk assessment. The American Journal of Medicine 2004;116:9-16.
2. Libby P, Ridker PM, Maseri A. Inflammation and atherosclerosis. Circulation 2002;105:1135-1143.
3. Burke AP, Farb A, Malcom GT, Liang YH, Smialek J, Virmani R. Coronary risk factors and plaque morphology in men with coronary disease who died suddenly [see comments]. N Engl J Med 1997;336:1276-82.
4. 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;93:1354-63.
5. Kolodgie FD, Burke AP, Farb A, et al. The thin-cap fibroatheroma: a type of vulnerable plaque: the major precursor lesion to acute coronary syndromes. Current Opinion in Cardiology 2001;16:285-92.
6. Virmani R, Farb A, Burke AP. Risk factors in the pathogenesis of coronary artery disease. Compr Ther 1998;24:519-29.
7. Davies M, Thomas A. Thrombosis and acute coronary-artery lesions in sudden cardiac ischemic death. N Engl J Med 1984;310:1137-1140.
8. Davies MJ. Acute coronary thrombosis--the role of plaque disruption and its initiation and prevention. Eur Heart J 1995;16 Suppl L:3-7.
9. Davies MJ, Thomas A. Thrombosis and acute coronary-artery lesions in sudden cardiac ischemic death. N Engl J Med 1984;310:1137-40.
10. Davies MJ, Woolf N, Rowles P, Richardson PD. Lipid and cellular constituents of unstable human aortic plaques. Basic Res Cardiol 1994;89:33-9.
11. Golledge J, Cuming R, Ellis M, Davies AH, Greenhalgh RM. Carotid plaque characteristics and presenting symptom. British Journal of Surgery 1997;84:1697-701.
12. Tice JA, Browner W, Tracy RP, Cummings SR. The relation of C-reactive protein levels to total and cardiovascular mortality in older U.S. women. The American Journal of Medicine 2001;114:199-205.
13. Ridker PM, Cushman M, Stampfer MJ, Tracy RP, Hennekens CH. Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men. N Engl J Med 1997;336:973-9.
14. Ridker PM, Rifai N, Pfeffer MA, et al. Circulation 1998;98:839-44.
15. Ridker PM, Glynn RJ, Hennekens CH. C-reactive protein adds to the predictive value of total and HDL cholesterol in determining risk of first myocardial infarction. Circulation 1998;97:2007-11.
16. Nissen SE, Yock P. Intravascular ultrasound: novel pathophysiological insights and current clinical applications. Circulation 2001;103:604-16.
17. Carlier SG, de Korte CL, Brusseau E, Schaar JA, Serruys PW, van der Steen AF. Imaging of atherosclerosis. Elastography. J Cardiovasc Risk 2002;9:237-45.
18. de Korte CL, van der Steen AF, Cepedes EI, et al. Phys Med Biol 2000;45:1465-75.
19. Matsuzaki M, Hiramori K, Imaizumi T, et al.. J Am Coll Cardiol 2002;40:220-7.
20. Schartl M, Bocksch W, Koschyk DH, et al. Circulation 2001;104:387-92.
21. Mintz GS, Nissen SE, Anderson WD, et al. A report of the American College of Cardiology Task Force on Clinical Expert Consensus Documents. J Am Coll Cardiol 2001;37:1478-92.
22. Nair A, Kuban BD, Tuzcu EM, Schoenhagen P, Nissen SE, Vince DG. Coronary plaque classification with intravascular ultrasound radiofrequency data analysis. Circulation 2002;106:2200-6.
23. Becker CR, Nikolaou K, Muders M, et al. Eur Radiol 2003;13:2094-8.
24. Hoffmann U B-SA, Achenbach S, Ferencik M, Brady TJ, Levy D, O'Donnell CJ.. Radiology 2003;Supplement.
25. Leber AW, Knez A, Becker A, et al. Journal of the American College of Cardiology 2004;43:1241-1247.
26. Corti R, Fuster V, Badimon JJ, Hutter R, Fayad ZA. Ann N Y Acad Sci 2001;947:181-95; discussion 195-8.
27. Yuan C, Mitsumori LM, Beach KW, Maravilla KR. Radiology 2001;221:285-99.
28. Toussaint JF, LaMuraglia GM, Southern JF, Fuster V, Kantor HL. Circulation 1996;94:932-8.
29. Helft G, Worthley SG, Fuster V, et al. Circulation 2002;105:993-8.
30. Cai J, Hatsukami TS, Ferguson MS, et al. Circulation 2005;112:3437-3444.
31. Schmitz SA, Coupland SE, Gust R, et al. Investigative Radiology 2000;35:460-71.
32. Ruehm SG, Corot C, Vogt P, Kolb S, Debatin JF. Circulation 2001;103:415-422.
33. Kooi ME, Cappendijk VC, Cleutjens KBJM, et al. Circulation 2003;107:2453-2458.
34. Fischman AJ, Alpert NM. FDG-PET in oncology: there's more to it than looking at pictures. [letter; comment]. Journal of Nuclear Medicine 1993;34:6-11.
35. Palmer WE, Rosenthal DI, Schoenberg OI, et al. Radiology 1995;196:647-55.
36. Yao WJ, Hoh CK, Hawkins RA, et al. J Nucl Med 1995;36:794-9.
37. Yamada S, Kubota K, Kubota R, Ido T, Tamahashi N.. J Nucl Med 1995;36:1301-6.
38. Fischman AJ, Thornton AF, Frosch MP, Swearinger B, Gonzalez RG, Alpert NM. Journal of Nuclear Medicine 1997;38:1027-9.
39. Goldberg MA, Mayo-Smith WW, Papanicolaou N, Fischman AJ, Lee MJ. Clinical Radiology 1997;52:510-5.
40. Diederichs CG, Staib L, Glatting G, Beger HG, Reske SN.. Journal of Nuclear Medicine 1998;39:1030-3.
41. Jadvar H, Fischman AJ. Abdominal Imaging 2001;26:254-9.
42. Lorenzen J, Buchert R, Bohuslavizki KH. Nucl Med Commun 2001;22:779-83.
43. El-Haddad G, Zhuang H, Gupta N, Alavi A. Semin Nucl Med 2004;34:313-29.
44. Deshmukh A, Scott JA, Palmer EL, Hochberg FH, Gruber M, Fischman AJ. Clinical Nuclear Medicine 1996;21:720-5.
45. Jones HA, Cadwallader KA, White JF, Uddin M, Peters AM, Chilvers ER. J Nucl Med 2002;43:652-7.
46. Sugawara Y, Gutowski TD, Fisher SJ, Brown RS, Wahl RL. Eur J Nucl Med 1999;26:333-41.
47. Hunter GJ, Choi NC, McLoud TC, Fischman AJ. Journal of Nuclear Medicine 1993;34:1571-3.
48. Bleeker-Rovers CP, Vos FJ, Wanten GJA, et al. J Nucl Med 2005;46:2014-2019.
49. Kaim AH, Weber B, Kurrer MO, Gottschalk J, Von Schulthess GK, Buck A Radiology 2002;223:446-51.
50. Kubota R, Kubota K, Yamada S, Tada M, Ido T, Tamahashi N. J Nucl Med 1994;35:104-12.
51. Newsholme P, Newsholme EA. Biochem J 1989;261:211-8.
52. Rist RJ, Jones GE, Naftalin RJ. Biochem J 1991;278 ( Pt 1):119-28.
53. Kiyotaki C, Peisach J, Bloom BR. J Immunol 1984;132:857-66.
54. Ahmed N, Kansara M, Berridge MV. Biochem J 1997;327 ( Pt 2):369-75.
55. Babior BM. The respiratory burst of phagocytes. J Clin Invest 1984;73:599-601.
56. Berridge MV, Tan AS. Biochem J 1995;305 ( Pt 3):843-51.
57. Pasternak CA, Aiyathurai JE, Makinde V, et al. J Cell Physiol 1991;149:324-31.
58. Bashan N, Burdett E, Hundal HS, Klip A.. Am J Physiol 1992;262:C682-90.
59. Nefesh I, Bauskin AR, Alkalay I, Golembo M, Ben-Neriah Y. Int Immunol 1991;3:827-31.
60. Vallabhajosula S, Fuster V. Journal of Nucl Med 1997;38:1788-96.
61. Lederman RJ, Raylman RR, Fisher SJ, et al. Nucl Med Commun 2001;22:747-53.
62. Mari C, Nedelman M, Blankenberg F, Ghazarossian V, Strauss RW. Journal of Nuclear Medicine 2001;42.
63. Tawakol A, Migrino RQ, Hoffmann U, et al. J Nuc Cardiol 2005:in press.
64. Hara M, Goodman PC, Leder RA. J Comput Assist Tomogr 1999;23:16-8.
65. Meller J, Altenvoerde G, Munzel U, et al. Eur J Nucl Med 2000;27:1617-25.
66. Blockmans D, Maes A, Stroobants S, et al. Rheumatology (Oxford) 1999;38:444-7.
67. Derdelinckx I, Maes A, Bogaert J, Mortelmans L, Blockmans D. Acta Cardiol 2000;55:193-5.
68. Dunphy MPS, Freiman A, Larson SM, Strauss HW. J Nucl Med 2005;46:1278-1284.
69. Tatsumi M, Cohade C, Nakamoto Y, Wahl RL. Radiology 2003;229:831-7.
70. Ben-Haim S, Kupzov E, Tamir A, Israel O.. J Nucl Med 2004;45:1816-21.
71. Rudd JH, Warburton EA, Fryer TD, et al. Imaging Circulation 2002;105:2708-11.
72. Davies JR, Rudd JHF, Fryer TD, et al. Stroke 2005;36:2642-2647.
73. Tawakol A, Migrino RQ, Bashian GG, et al. Journal American College of Cardiology 2006;in press.
74. Corti R, Ferrari C, Roberti M, Alerci M, Pedrazzi PL, Gallino A. Circulation 1998;98:984-989.
75. Yuan C, Mitsumori LM, Ferguson MS, et al. . Circulation 2001;104:2051-2056.
76. Jander S, Sitzer M, Schumann R, et al. Stroke 1998;29:1625-30.
77. Crisby M, Nordin-Fredriksson G, Shah PK, Yano J, Zhu J, Nilsson J. Circulation 2001;103:926-933.
78. Martin-Ventura JL, Blanco-Colio LM, Gomez-Hernandez A, et al. . Stroke 2005;36:1796-1800.