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Advanced Coronary Artery Vessel Wall Imaging and Future Directions

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Vessel Based Imaging Techniques

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Abstract

Accurate and reliable coronary angiographic imaging techniques that assess not only the luminal stenosis but also lesion characteristics may potentially improve personal risk stratification of coronary atherosclerosis and guide therapeutic decision-making. Ongoing development in noninvasive coronary vessel wall imaging techniques is producing novel clinical tools that aim to improve the current diagnosis performance and treatment outcome. Previous technical limitations such as long scan time, complex procedures, and motion sensitivity are being reduced or eliminated by advanced acquisition, reconstruction, and post-processing techniques. New contrast mechanisms and imaging biomarkers are being explored to provide in-depth interrogation of the disease characteristics. In this chapter we review the recent technical developments in the most promising noninvasive coronary vessel wall imaging modalities, including MRI, CT, and PET. The discussion will focus on the latest technical advances and new directions of lesion characterization.

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References

  1. Xie Y, Pang J, Yang Q, Li D. Magnetic resonance imaging of coronary arteries: latest technical innovations and clinical experiences. Cardiovasc Innov Appl. 2016;2(1):85–99.

    Google Scholar 

  2. Xie Y, Jin H, Zeng M, Li D. Coronary artery plaque imaging. Curr Atheroscler Rep. 2017;19(9):37.

    Article  PubMed  Google Scholar 

  3. Dweck MR, Puntman V, Vesey AT, Fayad ZA, Nagel E. MR imaging of coronary arteries and plaques. J Am Coll Cardiol Img. 2016;9(3):306–16.

    Article  Google Scholar 

  4. Tarkin JM, Dweck MR, Evans NR, Takx RA, Brown AJ, Tawakol A, et al. Imaging atherosclerosis. Circ Res. 2016;118(4):750–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Adamson PD, Newby DE. Non-invasive imaging of the coronary arteries. Eur Heart J. 2018;0:1–11.

    Google Scholar 

  6. Miao C, Chen S, Macedo R, Lai S, Liu K, Li D, et al. Positive remodeling of the coronary arteries detected by magnetic resonance imaging in an asymptomatic population: MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2009;53(18):1708–15.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Stone GW, Maehara A, Lansky AJ, de Bruyne B, Cristea E, Mintz GS, et al. A prospective natural-history study of coronary atherosclerosis. N Engl J Med. 2011;364(3):226–35.

    Article  CAS  PubMed  Google Scholar 

  8. Macedo R, Chen S, Lai S, Shea S, Malayeri AA, Szklo M, et al. MRI detects increased coronary wall thickness in asymptomatic individuals: the multi-ethnic study of atherosclerosis (MESA). J Magn Reson Imaging. 2008;28(5):1108–15.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Terashima M, Nguyen PK, Rubin GD, Meyer CH, Shimakawa A, Nishimura DG, et al. Right coronary wall CMR in the older asymptomatic advance cohort: positive remodeling and associations with type 2 diabetes and coronary calcium. J Cardiovasc Magn Reson. 2010;12:75.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Fayad ZA, Fuster V, Fallon JT, Jayasundera T, Worthley SG, Helft G, et al. Noninvasive in vivo human coronary artery lumen and wall imaging using black-blood magnetic resonance imaging. Circulation. 2000;102(5):506–10.

    Article  CAS  PubMed  Google Scholar 

  11. Botnar RM, Stuber M, Kissinger KV, Kim WY, Spuentrup E, Manning WJ. Noninvasive coronary vessel wall and plaque imaging with magnetic resonance imaging. Circulation. 2000;102(21):2582–7.

    Article  CAS  PubMed  Google Scholar 

  12. Kim WY, Stuber M, Kissinger KV, Andersen NT, Manning WJ, Botnar RM. Impact of bulk cardiac motion on right coronary MR angiography and vessel wall imaging. J Magn Reson Imaging. 2001;14(4):383–90.

    Article  CAS  PubMed  Google Scholar 

  13. Abd-Elmoniem KZ, Weiss RG, Stuber M. Phase-sensitive black-blood coronary vessel wall imaging. Magn Reson Med. 2010;63(4):1021–30.

    Article  PubMed  Google Scholar 

  14. Abd-Elmoniem KZ, Gharib AM, Pettigrew RI. Coronary vessel wall 3-T MR imaging with time-resolved acquisition of phase-sensitive dual inversion-recovery (TRAPD) technique: initial results in patients with risk factors for coronary artery disease. Radiology. 2012;265(3):715–23.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Andia ME, Henningsson M, Hussain T, Phinikaridou A, Protti A, Greil G, et al. Flow-independent 3D whole-heart vessel wall imaging using an interleaved T2-preparation acquisition. Magn Reson Med. 2013;69(1):150–7.

    Article  PubMed  Google Scholar 

  16. Cruz G, Atkinson D, Henningsson M, Botnar RM, Prieto C. Highly efficient nonrigid motion-corrected 3D whole-heart coronary vessel wall imaging. Magn Reson Med. 2017;77(5):1894–908.

    Article  CAS  PubMed  Google Scholar 

  17. Xie G, Bi X, Liu J, Yang Q, Natsuaki Y, Conte AH, et al. Three-dimensional coronary dark-blood interleaved with gray-blood (cDIG) magnetic resonance imaging at 3 tesla. Magn Reson Med. 2016;75(3):997–1007.

    Article  PubMed  Google Scholar 

  18. Hellings WE, Peeters W, Moll FL, Piers SR, van Setten J, Van der Spek PJ, et al. Composition of carotid atherosclerotic plaque is associated with cardiovascular outcome: a prognostic study. Circulation. 2010;121(17):1941–50.

    Article  PubMed  Google Scholar 

  19. Virmani R, Burke AP, Farb A, Kolodgie FD. Pathology of the vulnerable plaque. J Am Coll Cardiol. 2006;47(8 Suppl):C13–8.

    Article  CAS  PubMed  Google Scholar 

  20. 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(5):1262–75.

    Article  CAS  PubMed  Google Scholar 

  21. Maintz D, Ozgun M, Hoffmeier A, Fischbach R, Kim WY, Stuber M, et al. Selective coronary artery plaque visualization and differentiation by contrast-enhanced inversion prepared MRI. Eur Heart J. 2006;27(14):1732–6.

    Article  PubMed  Google Scholar 

  22. Moody AR, Murphy RE, Morgan PS, Martel AL, Delay GS, Allder S, et al. Characterization of complicated carotid plaque with magnetic resonance direct thrombus imaging in patients with cerebral ischemia. Circulation. 2003;107(24):3047–52.

    Article  PubMed  Google Scholar 

  23. Kawasaki T, Koga S, Koga N, Noguchi T, Tanaka H, Koga H, et al. Characterization of hyperintense plaque with noncontrast T(1)-weighted cardiac magnetic resonance coronary plaque imaging: comparison with multislice computed tomography and intravascular ultrasound. J Am Coll Cardiol Img. 2009;2(6):720–8.

    Article  Google Scholar 

  24. Oei ML, Ozgun M, Seifarth H, Bunck A, Fischbach R, Orwat S, et al. T1-weighted MRI for the detection of coronary artery plaque haemorrhage. Eur Radiol. 2010;20(12):2817–23.

    Article  PubMed  Google Scholar 

  25. Noguchi T, Kawasaki T, Tanaka A, Yasuda S, Goto Y, Ishihara M, 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(10):989–99.

    Article  PubMed  Google Scholar 

  26. Noguchi T, Tanaka A, Kawasaki T, Goto Y, Morita Y, Asaumi Y, et al. Effect of intensive statin therapy on coronary high-intensity plaques detected by noncontrast T1-weighted imaging: the AQUAMARINE pilot study. J Am Coll Cardiol. 2015;66(3):245–56.

    Article  CAS  PubMed  Google Scholar 

  27. Xie Y, Kim YJ, Pang J, Kim JS, Yang Q, Wei J, et al. Coronary atherosclerosis T1-weighed characterization with integrated anatomical reference: comparison with high-risk plaque features detected by invasive coronary imaging. J Am Coll Cardiol Img. 2017;10(6):637–48.

    Article  Google Scholar 

  28. Jansen CH, Perera D, Makowski MR, Wiethoff AJ, Phinikaridou A, Razavi RM, et al. Detection of intracoronary thrombus by magnetic resonance imaging in patients with acute myocardial infarction. Circulation. 2011;124(4):416–24.

    Article  CAS  PubMed  Google Scholar 

  29. Ehara S, Hasegawa T, Nakata S, Matsumoto K, Nishimura S, Iguchi T, et al. Hyperintense plaque identified by magnetic resonance imaging relates to intracoronary thrombus as detected by optical coherence tomography in patients with angina pectoris. Eur Heart J Cardiovasc Imaging. 2012;13(5):394–9.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Matsumoto K, Ehara S, Hasegawa T, Sakaguchi M, Otsuka K, Yoshikawa J, et al. Localization of coronary high-intensity signals on T1-weighted MR imaging: relation to plaque morphology and clinical severity of angina pectoris. J Am Coll Cardiol Img. 2015;8(10):1143–52.

    Article  Google Scholar 

  31. Matsumoto K, Ehara S, Hasegawa T, Nishimura S, Shimada K. The signal intensity of coronary culprit lesions on T1-weighted magnetic resonance imaging is directly correlated with the accumulation of vulnerable morphologies. Int J Cardiol. 2017;231:284–6.

    Article  PubMed  Google Scholar 

  32. Liu W, Xie Y, Wang C, Du Y, Nguyen C, Wang Z, et al. Atherosclerosis T1-weighted characterization (CATCH): evaluation of the accuracy for identifying intraplaque hemorrhage with histological validation in carotid and coronary artery specimens. J Cardiovasc Magn Reson. 2018;20(1):27.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Yeon SB, Sabir A, Clouse M, Martinezclark PO, Peters DC, Hauser TH, 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(5):441–7.

    Article  PubMed  Google Scholar 

  34. Dill T, Ekinci O, Hansel J, Kluge A, Breidenbach C, Hamm CW. Delayed contrast-enhanced magnetic resonance imaging for the detection of autoimmune myocarditis and long-term follow-up. J Cardiovasc Magn Reson. 2005;7(2):521–3.

    Article  PubMed  Google Scholar 

  35. Schneeweis C, Schnackenburg B, Stuber M, Berger A, Schneider U, Yu J, et al. Delayed contrast-enhanced MRI of the coronary artery wall in takayasu arteritis. PLoS One. 2012;7(12):e50655.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Botnar RM, Buecker A, Wiethoff AJ, Parsons EC Jr, Katoh M, Katsimaglis G, et al. In vivo magnetic resonance imaging of coronary thrombosis using a fibrin-binding molecular magnetic resonance contrast agent. Circulation. 2004;110(11):1463–6.

    Article  PubMed  Google Scholar 

  37. Makowski MR, Wiethoff AJ, Blume U, Cuello F, Warley A, Jansen CH, et al. Assessment of atherosclerotic plaque burden with an elastin-specific magnetic resonance contrast agent. Nat Med. 2011;17(3):383–8.

    Article  CAS  PubMed  Google Scholar 

  38. von Bary C, Makowski M, Preissel A, Keithahn A, Warley A, Spuentrup E, et al. MRI of coronary wall remodeling in a swine model of coronary injury using an elastin-binding contrast agent. Circ Cardiovasc Imaging. 2011;4(2):147–55.

    Article  Google Scholar 

  39. Phinikaridou A, Andia ME, Protti A, Indermuehle A, Shah A, Smith A, et al. Noninvasive magnetic resonance imaging evaluation of endothelial permeability in murine atherosclerosis using an albumin-binding contrast agent. Circulation. 2012;126(6):707–19.

    Article  CAS  PubMed  Google Scholar 

  40. Pedersen SF, Thrysoe SA, Paaske WP, Thim T, Falk E, Ringgaard S, et al. CMR assessment of endothelial damage and angiogenesis in porcine coronary arteries using gadofosveset. J Cardiovasc Magn Reson. 2011;13:10.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Engel LC, Landmesser U, Gigengack K, Wurster T, Manes C, Girke G, et al. Novel approach for in vivo detection of vulnerable coronary plaques using molecular 3-T CMR imaging with an albumin-binding probe. J Am Coll Cardiol Img. 2019;12(2):297–306.

    Article  Google Scholar 

  42. Pepe A, Lombardi M, Takacs I, Positano V, Panzarella G, Picano E. Nitrate-induced coronary vasodilation by stress-magnetic resonance imaging: a novel noninvasive test of coronary vasomotion. J Magn Reson Imaging. 2004;20(3):390–4.

    Article  PubMed  Google Scholar 

  43. Terashima M, Meyer CH, Keeffe BG, Putz EJ, de la Pena-Almaguer E, Yang PC, et al. Noninvasive assessment of coronary vasodilation using magnetic resonance angiography. J Am Coll Cardiol. 2005;45(1):104–10.

    Article  PubMed  Google Scholar 

  44. Hays AG, Hirsch GA, Kelle S, Gerstenblith G, Weiss RG, Stuber M. Noninvasive visualization of coronary artery endothelial function in healthy subjects and in patients with coronary artery disease. J Am Coll Cardiol. 2010;56(20):1657–65.

    Article  PubMed  Google Scholar 

  45. Lin K, Lloyd-Jones DM, Liu Y, Bi X, Li D, Carr JC. Noninvasive evaluation of coronary distensibility in older adults: a feasibility study with MR angiography. Radiology. 2011;261(3):771–8.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Lin K, Lloyd-Jones DM, Taimen K, Liu Y, Bi X, Li D, et al. The detection of coronary stiffness in cardiac allografts using MR imaging. Eur J Radiol. 2014;83(8):1402–7.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Commandeur F, Goeller M, Dey D. Cardiac CT: technological advances in hardware, software, and machine learning applications. Curr Cardiovasc Imaging Rep. 2018;11(8):19.

    Article  PubMed  PubMed Central  Google Scholar 

  48. 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(4):827–32.

    Article  CAS  PubMed  Google Scholar 

  49. Callister T, Cooil B, Raya S, Lippolis N, Russo D, Raggi P. Coronary artery disease: improved reproducibility of calcium scoring with an electron-beam CT volumetric method. Radiology. 1998;208(3):807–14.

    Article  CAS  PubMed  Google Scholar 

  50. McCollough CH, Ulzheimer S, Halliburton SS, Shanneik K, White RD, Kalender WA. Coronary artery calcium: a multi-institutional, multimanufacturer international standard for quantification at cardiac CT. Radiology. 2007;243(2):527–38.

    Article  PubMed  Google Scholar 

  51. Arad Y, Goodman KJ, Roth M, Newstein D, Guerci AD. Coronary calcification, coronary disease risk factors, C-reactive protein, and atherosclerotic cardiovascular disease events: the St. Francis Heart Study. J Am Coll Cardiol. 2005;46(1):158–65.

    Article  CAS  PubMed  Google Scholar 

  52. Shaw L, Raggi P, Schisterman E, Berman D, Callister T. Prognostic value of cardiac risk factors and coronary artery calcium screening for all-cause mortality. Radiology. 2003;228(3):826–33.

    Article  PubMed  Google Scholar 

  53. Berman DS, Hachamovitch R, Shaw LJ, Friedman JD, Hayes SW, Thomson LE, et al. Roles of nuclear cardiology, cardiac computed tomography, and cardiac magnetic resonance: noninvasive risk stratification and a conceptual framework for the selection of noninvasive imaging tests in patients with known or suspected coronary artery disease. J Nucl Med. 2006;47(7):1107–18.

    PubMed  Google Scholar 

  54. Arad Y, Spadaro LA, Goodman K, Newstein D, Guerci AD. Prediction of coronary events with electron beam computed tomography. J Am Coll Cardiol. 2000;36(4):1253–60.

    Article  CAS  PubMed  Google Scholar 

  55. Raggi P, Callister TQ, Cooil B, He ZX, Lippolis NJ, Russo DJ, et al. Identification of patients at increased risk of first unheralded acute myocardial infarction by electron-beam computed tomography. Circulation. 2000;101(8):850–5.

    Article  CAS  PubMed  Google Scholar 

  56. Park R, Detrano R, Xiang M, Fu P, Ibrahim Y, LaBree L, et al. Combined use of computed tomography coronary calcium scores and C-reactive protein levels in predicting cardiovascular events in nondiabetic individuals. Circulation. 2002;106(16):2073–7.

    Article  CAS  PubMed  Google Scholar 

  57. Shemesh J, Morag-Koren N, Goldbourt U, Grossman E, Tenenbaum A, Fisman EZ, et al. Coronary calcium by spiral computed tomography predicts cardiovascular events in high-risk hypertensive patients. J Hypertens. 2004;22(3):605–10.

    Article  CAS  PubMed  Google Scholar 

  58. Wong ND, Hsu JC, Detrano RC, Diamond G, Eisenberg H, Gardin JM. Coronary artery calcium evaluation by electron beam computed tomography and its relation to new cardiovascular events. Am J Cardiol. 2000;86(5):495–8.

    Article  CAS  PubMed  Google Scholar 

  59. Kondos GT, Hoff JA, Sevrukov A, Daviglus ML, Garside DB, Devries SS, et al. Electron-beam tomography coronary artery calcium and cardiac events: a 37-month follow-up of 5635 initially asymptomatic low- to intermediate-risk adults. Circulation. 2003;107(20):2571–6.

    Article  PubMed  Google Scholar 

  60. Greenland P, LaBree L, Azen SP, Doherty TM, Detrano RC. Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA. 2004;291(2):210–5.

    Article  CAS  PubMed  Google Scholar 

  61. LaMonte MJ, FitzGerald SJ, Church TS, Barlow CE, Radford NB, Levine BD, et al. Coronary artery calcium score and coronary heart disease events in a large cohort of asymptomatic men and women. Am J Epidemiol. 2005;162(5):421–9.

    Article  PubMed  Google Scholar 

  62. Taylor AJ, Bindeman J, Feuerstein I, Cao F, Brazaitis M, O'Malley PG. 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.

    Article  CAS  PubMed  Google Scholar 

  63. Vliegenthart R, Oudkerk M, Hofman A, Oei HH, van Dijck W, van Rooij FJ, et al. Coronary calcification improves cardiovascular risk prediction in the elderly. Circulation. 2005;112(4):572–7.

    Article  PubMed  Google Scholar 

  64. Becker A, Knez A, Becker C, Leber A, Anthopounou L, Boekstegers P, et al. [Prediction of serious cardiovascular events by determining coronary artery calcification measured by multi-slice computed tomography]. Dtsch Med Wochenschr. 2005;130(43):2433–8.

    Article  CAS  Google Scholar 

  65. Detrano R, Guerci AD, Carr JJ, Bild DE, Burke G, Folsom AR, et al. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008;358(13):1336–45.

    Article  CAS  PubMed  Google Scholar 

  66. Taylor AJ, Cerqueira M, Hodgson JM, Mark D, Min J, O’Gara P, et al. ACCF/SCCT/ACR/AHA/ASE/ASNC/NASCI/SCAI/SCMR 2010 Appropriate Use Criteria for Cardiac Computed Tomography: A Report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, the Society of Cardiovascular Computed Tomography, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the American Society of Nuclear Cardiology, the North American Society for Cardiovascular Imaging, the Society for Cardiovascular Angiography and Interventions, and the Society for Cardiovascular Magnetic Resonance. J Am Coll Cardiol. 2010;56(22):1864–94.

    Article  PubMed  Google Scholar 

  67. Budoff MJ, Dowe D, Jollis JG, Gitter M, Sutherland J, Halamert E, et al. Diagnostic performance of 64-multidetector row coronary computed tomographic angiography for evaluation of coronary artery stenosis in individuals without known coronary artery disease: results from the prospective multicenter ACCURACY (Assessment by Coronary Computed Tomographic Angiography of Individuals Undergoing Invasive Coronary Angiography) Trial. J Am Coll Cardiol. 2008;52(21):1724–32.

    Article  PubMed  Google Scholar 

  68. Hausleiter J, Meyer T, Hadamitzky M, Zankl M, Gerein P, DorrLer K, et al. Non-invasive coronary computed tomographic angiography for patients with suspected coronary artery disease: the Coronary Angiography by Computed Tomography with the Use of a Submillimeter resolution (CACTUS) trial. Eur Heart J. 2007;28(24):3034–41.

    Article  PubMed  Google Scholar 

  69. Achenbach S, Ropers U, Kuettner A, Anders K, Pflederer T, Komatsu S, et al. Randomized comparison of 64-slice single- and dual-source computed tomography coronary angiography for the detection of coronary artery disease. J Am Coll Cardiol Cardiovasc Imaging. 2008;1(2):177–86.

    Article  Google Scholar 

  70. Miller JM, Rochitte CE, Dewey M, Arbab-Zadeh A, Niinuma H, Gottlieb I, et al. Diagnostic performance of coronary angiography by 64-row CT. N Engl J Med. 2008;359(22):2324–36.

    Article  CAS  PubMed  Google Scholar 

  71. Meijboom WB, van Mieghem CAG, Mollet NR, Pugliese F, Weustink AC, van Pelt N, et al. 64-slice computed tomography coronary angiography in patients with high, intermediate, or low pretest probability of significant coronary artery disease. J Am Coll Cardiol. 2007;50:1469–75.

    Article  PubMed  Google Scholar 

  72. Abbara S, Blanke P, Maroules CD, Cheezum M, Choi AD, Han BK, et al. SCCT guidelines for the performance and acquisition of coronary computed tomographic angiography: a report of the society of Cardiovascular Computed Tomography Guidelines Committee: endorsed by the North American Society for Cardiovascular Imaging (NASCI). J Cardiovasc Comput Tomogr. 2016;10(6):435–49.

    Article  PubMed  Google Scholar 

  73. Cury RC, Abbara S, Achenbach S, Agatston A, Berman DS, Budoff MJ, et al. CAD-RADSTM coronary artery disease–reporting and data system. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology. J Cardiovasc Comput Tomogr. 2016;10(4):269–81.

    Article  PubMed  Google Scholar 

  74. Douglas PS, Hoffmann U, Patel MR, Mark DB, Al-Khalidi HR, Cavanaugh B, et al. Outcomes of anatomical versus functional testing for coronary artery disease. N Engl J Med. 2015;372(14):1291–300.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. 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(9985):2383–91.

    Article  Google Scholar 

  76. Newby DE, Adamson PD, Berry C, Boon NA, Dweck MR, Flather M, et al. Coronary CT angiography and 5-year risk of myocardial infarction. N Engl J Med. 2018;379(10):924–33.

    Article  PubMed  Google Scholar 

  77. Achenbach S, Moselewski F, Ropers D, Ferencik M, Hoffmann U, MacNeill B, et al. Detection of calcified and noncalcified coronary atherosclerotic plaque by contrast-enhanced, submillimeter multidetector spiral computed tomography: a segment-based comparison with intravascular ultrasound. Circulation. 2004;109(1):14–7.

    Article  PubMed  Google Scholar 

  78. Achenbach S, Ropers D, Hoffmann U, MacNeill B, Baum U, Pohle K, et al. Assessment of coronary remodeling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography. J Am Coll Cardiol. 2004;43(5):842–7.

    Article  PubMed  Google Scholar 

  79. Leber AW, Becker A, Knez A, von Ziegler F, Sirol M, Nikolaou K, 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.

    Article  PubMed  Google Scholar 

  80. Leber AW, Knez A, Becker A, Becker C, von Ziegler F, Nikolaou K, 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.

    Article  PubMed  Google Scholar 

  81. Pundziute G, Schuijf JD, Jukema JW, Decramer I, Sarno G, Vanhoenacker PK, et al. Evaluation of plaque characteristics in acute coronary syndromes: non-invasive assessment with multi-slice computed tomography and invasive evaluation with intravascular ultrasound radiofrequency data analysis. Eur Heart J. 2008;29(19):2373–81.

    Article  PubMed  Google Scholar 

  82. Schepis T, Marwan M, Pflederer T, Seltmann M, Ropers D, Daniel WG, et al. Quantification of noncalcified coronary atherosclerotic plaques with Dual Source Computed Tomography: comparison to intravascular ultrasound. Heart. 2010;96:610–5.

    Article  PubMed  Google Scholar 

  83. Petranovic M, Soni A, Bezzera H, Loureiro R, Sarwar A, Raffel C, 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.

    Article  PubMed  Google Scholar 

  84. Dey D, Schepis T, Marwan M, Slomka PJ, Berman DS, Achenbach S. Automated three-dimensional quantification of non-calcified coronary plaque from coronary CT angiography: comparison with intravascular ultrasound. Radiology. 2010;257(2):516–22.

    Article  PubMed  Google Scholar 

  85. Boogers MJ, Broersen A, van Velzen JE, de Graaf FR, El-Naggar HM, Kitslaar PH, 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.

    Article  PubMed  Google Scholar 

  86. Voros S, Rinehart S, Qian Z, Joshi P, Vazquez G, Fischer C, et al. Coronary atherosclerosis imaging by coronary CT angiography current status, correlation with intravascular interrogation and meta-analysis. JACC Cardiovasc Imaging. 2011;4(5):537–48.

    Article  PubMed  Google Scholar 

  87. Motoyama S, Sarai M, Harigaya H, Anno H, Inoue K, Hara T, et al. Computed tomographic angiography characteristics of atherosclerotic plaques subsequently resulting in acute coronary syndrome. J Am Coll Cardiol. 2009;54(1):49–57.

    Article  PubMed  Google Scholar 

  88. Motoyama S, Kondo T, Sarai M, Sugiura A, Harigaya H, Sato T, et al. Multislice computed tomographic characteristics of coronary lesions in acute coronary syndromes. J Am Coll Cardiol. 2007;50(4):319–26.

    Article  PubMed  Google Scholar 

  89. Pflederer T, Marwan M, Schepis T, Ropers D, Seltmann M, Muschiol G, Daniel WG, Achenbach S. Characterization of culprit lesions in acute coronary syndromes using coronary dual-source CT angiography. Atherosclerosis. 2010;211(2):437–44.

    Article  CAS  PubMed  Google Scholar 

  90. Puchner SB, Liu T, Mayrhofer T, Truong QA, Lee H, Fleg JL, et al. High-risk plaque detected on coronary CT angiography predicts acute coronary syndromes independent of significant stenosis in acute chest pain: results from the ROMICAT-II trial. J Am Coll Cardiol. 2014;64(7):684–92.

    Article  PubMed  PubMed Central  Google Scholar 

  91. Maurovich-Horvat P, Hoffmann U, Vorpahl M, Nakano M, Virmani R, Alkadhi H. The napkin-ring sign: CT signature of high-risk coronary plaques? JACC Cardiovasc Imaging. 2010;3(4):440–4.

    Article  PubMed  Google Scholar 

  92. Narula J, Achenbach S. Napkin-ring necrotic cores: defining circumferential extent of necrotic cores in unstable plaques. JACC Cardiovasc Imaging. 2009;2(12):1436–8.

    Article  PubMed  Google Scholar 

  93. Kristensen TS, Kofoed KF, Kuhl JT, Nielsen WB, Nielsen MB, Kelbaek H. 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.

    Article  PubMed  Google Scholar 

  94. Versteylen MO, Kietselaer BL, Dagnelie PC, Joosen IA, Dedic A, Raaijmakers RH, 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.

    Article  PubMed  Google Scholar 

  95. Motoyama S, Ito H, Sarai M, Kondo T, Kawai H, Nagahara Y, 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(4):337–46.

    Article  PubMed  Google Scholar 

  96. Hell MM, Motwani M, Otaki Y, Cadet S, Gransar H, Miranda-Peats R, Valk J, PJ SL, Cheng V, Rozanski R, Tamarappoo BK, Hayes S, Achenbach S, Berman DS, Dey D, et al. Eur Heart J Cardiovasc Imaging. 2017;18(12):1331–9.

    Article  PubMed  PubMed Central  Google Scholar 

  97. Chang HJ, Lin FY, Lee SE, Andreini D, Bax J, Cademartiri F, et al. Coronary atherosclerotic precursors of acute coronary syndromes. J Am Coll Cardiol. 2018;71(22):2511–22.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Moreno PR, Narula J. Thinking outside the lumen: fractional flow reserve versus intravascular imaging for major adverse cardiac event prediction. J Am Coll Cardiol. 2014;63(12):1141–4.

    Article  PubMed  Google Scholar 

  99. Ahmadi A, Leipsic J, Blankstein R, Taylor C, Hecht H, Stone GW, et al. Do plaques rapidly progress prior to myocardial infarction? The interplay between plaque vulnerability and progression. Circ Res. 2015;117(1):99–104.

    Article  CAS  PubMed  Google Scholar 

  100. Tamarappoo B, Otaki Y, Doris M, Arnson Y, Gransar HG, Hayes S, Friedman J, Thomson LEJ, Wang F, Rozanski A, Slomka PJ, Dey D, Berman DS. Improvement in LDL is associated with decrease in non-calcified plaque volume on coronary CTA as measured by automated quantitative software. J Cardiovasc Comput Tomogr. 2018;12(5):385–90.

    Article  PubMed  Google Scholar 

  101. Lee S-E, Chang H-J, Sung JM, Park H-B, Heo R, Rizvi A, et al. Effects of statins on coronary atherosclerotic plaques. JACC Cardiovasc Imaging. 2018;11:1475.

    Article  PubMed  Google Scholar 

  102. Gaur S, Ovrehus KA, Dey D, Leipsic J, Botker HE, Jensen JM, et al. Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions. Eur Heart J. 2016;37(15):1220–7.

    Article  PubMed  PubMed Central  Google Scholar 

  103. Diaz Zamudio M, Dey D, Schuhbaeck A, Nakazato R, Slomka PJ, Bermand DS, Achenbach S, Min JK, Doh JH, Koo BK. Automated quantitative plaque burden from coronary CT Angiography noninvasively predicts hemodynamic significance by fractional flow reserve in intermediate coronary lesions. Radiology. 2015;276(2):408–15.

    Article  PubMed  Google Scholar 

  104. Motwani M, Dey D, Berman DS, Germano G, Achenbach S, Al-Mallah MH, et al. Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis. Eur Heart J. 2017;38(7):500–7.

    PubMed  Google Scholar 

  105. Dey D, Gaur S, Ovrehus KA, Slomka PJ, Betancur J, Goeller M, et al. Integrated prediction of lesion-specific ischaemia from quantitative coronary CT angiography using machine learning: a multicentre study. Eur Radiol. 2018;28:2655–64.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Mahabadi AA, Massaro JM, Rosito GA, Levy D, Murabito JM, Wolf PA, et al. Association of pericardial fat, intrathoracic fat, and visceral abdominal fat with cardiovascular disease burden: the Framingham Heart Study. Eur Heart J. 2009;30(7):850–6.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Mahabadi AA, Reinsch N, Lehmann N, Altenbernd J, Kalsch H, Seibel RM, et al. Association of pericoronary fat volume with atherosclerotic plaque burden in the underlying coronary artery: a segment analysis. Atherosclerosis. 2010;211(1):195–9.

    Article  CAS  PubMed  Google Scholar 

  108. Tamarappoo B, Dey D, Shmilovich H, Nakazato R, Gransar H, Cheng VY, et al. Increased pericardial fat volume measured from noncontrast CT predicts myocardial ischemia by SPECT. JACC Cardiovasc Imaging. 2010;3(11):1104–12.

    Article  PubMed  PubMed Central  Google Scholar 

  109. Mazurek T, Zhang L, Zalewski A, Mannion JD, Diehl JT, Arafat H, et al. Human epicardial adipose tissue is a source of inflammatory mediators. Circulation. 2003;108:2460–6.

    Article  PubMed  Google Scholar 

  110. Shimabukuro M, Hirata Y, Tabata M, Dagvasumberel M, Sato H, Kurobe H, et al. Epicardial adipose tissue volume and adipocytokine imbalance are strongly linked to human coronary atherosclerosis. Arterioscler Thromb Vasc Biol. 2013;33(5):1077–84.

    Article  CAS  PubMed  Google Scholar 

  111. Bucerius J, Mani V, Wong S, Moncrieff C, Izquierdo-Garcia D, Machac J, et al. Arterial and fat tissue inflammation are highly correlated : a prospective 18F-FDG PET/CT study. Eur J Nucl Med Mol Imaging. 2014;41(5):934–45.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Gorter PM, van Lindert ASR, de Vos AM, Meijs MFL, van der Graaf Y, Doevendans PA, et al. Quantification of epicardial and peri-coronary fat using cardiac computed tomography; reproducibility and relation with obesity and metabolic syndrome in patients suspected of coronary artery disease. Atherosclerosis. 2008;197(2):896–903.

    Article  CAS  PubMed  Google Scholar 

  113. Antonopoulos AS, Sanna F, Sabharwal N, Thomas S, Oikonomou EK, Herdman L, et al. Detecting human coronary inflammation by imaging perivascular fat. Sci Transl Med. 2017;9(398).

    Article  PubMed  CAS  Google Scholar 

  114. Oikonomou EK, Marwan M, Desai MY, Mancio J, Alashi A, Hutt Centeno E, et al. Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data. Lancet. 2018;392(10151):929–39.

    Article  PubMed  PubMed Central  Google Scholar 

  115. Goeller M, Achenbach S, Cadet S, Kwan AC, Commandeur F, Slomka PJ, et al. Pericoronary adipose tissue computed tomography attenuation and high-risk plaque characteristics in acute coronary syndrome compared with stable coronary artery disease. JAMA Cardiol. 2018;3(9):858–63.

    Article  PubMed  PubMed Central  Google Scholar 

  116. Rudd JH, Warburton EA, Fryer TD, Jones HA, Clark JC, Antoun N, et al. Imaging atherosclerotic plaque inflammation with [18F]-fluorodeoxyglucose positron emission tomography. Circulation. 2002;105(23):2708–11.

    Article  CAS  PubMed  Google Scholar 

  117. Rudd JH, Hyafil F, Fayad ZA. Inflammation imaging in atherosclerosis. Arterioscler Thromb Vasc Biol. 2009;29(7):1009–16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Tawakol A, Migrino RQ, Hoffmann U, Abbara S, Houser S, Gewirtz H, et al. Noninvasive in vivo measurement of vascular inflammation with F-18 fluorodeoxyglucose positron emission tomography. J Nucl Cardiol. 2005;12(3):294–301.

    Article  PubMed  Google Scholar 

  119. Alexanderson E, Slomka P, Cheng V, Meave A, Saldana Y, Garcia-Rojas L, et al. Fusion of positron emission tomography and coronary computed tomographic angiography identifies fluorine 18 fluorodeoxyglucose uptake in the left main coronary artery soft plaque. J Nucl Cardiol. 2008;15(6):841–3.

    Article  PubMed  Google Scholar 

  120. Rogers IS, Nasir K, Figueroa AL, Cury RC, Hoffmann U, Vermylen DA, et al. Feasibility of FDG imaging of the coronary arteries: comparison between acute coronary syndrome and stable angina. J Am Coll Cardiol Img. 2010;3(4):388–97.

    Article  Google Scholar 

  121. Williams G, Kolodny GM. Suppression of myocardial 18F-FDG uptake by preparing patients with a high-fat, low-carbohydrate diet. AJR Am J Roentgenol. 2008;190(2):W151–6.

    Article  PubMed  Google Scholar 

  122. Rominger A, Saam T, Vogl E, Ubleis C, la Fougere C, Forster S, et al. In vivo imaging of macrophage activity in the coronary arteries using 68Ga-DOTATATE PET/CT: correlation with coronary calcium burden and risk factors. J Nucl Med. 2010;51(2):193–7.

    Article  PubMed  Google Scholar 

  123. Tahara N, Mukherjee J, de Haas HJ, Petrov AD, Tawakol A, Haider N, et al. 2-deoxy-2-[18F]fluoro-D-mannose positron emission tomography imaging in atherosclerosis. Nat Med. 2014;20(2):215–9.

    Article  CAS  PubMed  Google Scholar 

  124. Dweck MR, Chow MW, Joshi NV, Williams MC, Jones C, Fletcher AM, et al. Coronary arterial 18F-sodium fluoride uptake: a novel marker of plaque biology. J Am Coll Cardiol. 2012;59(17):1539–48.

    Article  CAS  PubMed  Google Scholar 

  125. Joshi NV, Vesey A, Newby DE, Dweck MR. Will 18F-sodium fluoride PET-CT imaging be the magic bullet for identifying vulnerable coronary atherosclerotic plaques? Curr Cardiol Rep. 2014;16(9):521.

    Article  PubMed  Google Scholar 

  126. Joshi NV, Vesey AT, Williams MC, Shah AS, Calvert PA, Craighead FH, 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.

    Article  PubMed  Google Scholar 

  127. Rubeaux M, Joshi NV, Dweck MR, Fletcher A, Motwani M, Thomson LE, et al. Motion correction of 18F-NaF PET for imaging coronary atherosclerotic plaques. J Nucl Med. 2016;57(1):54–9.

    Article  CAS  PubMed  Google Scholar 

  128. Manber R, Thielemans K, Hutton BF, Barnes A, Ourselin S, Arridge S, et al. Practical PET respiratory motion correction in clinical PET/MR. J Nucl Med. 2015;56(6):890–6.

    Article  PubMed  Google Scholar 

  129. Kustner T, Schwartz M, Martirosian P, Gatidis S, Seith F, Gilliam C, et al. MR-based respiratory and cardiac motion correction for PET imaging. Med Image Anal. 2017;42:129–44.

    Article  PubMed  Google Scholar 

  130. Furst S, Grimm R, Hong I, Souvatzoglou M, Casey ME, Schwaiger M, et al. Motion correction strategies for integrated PET/MR. J Nucl Med. 2015;56(2):261–9.

    Article  PubMed  CAS  Google Scholar 

  131. Robson PM, Dey D, Newby DE, Berman D, Li D, Fayad ZA, et al. MR/PET imaging of the cardiovascular system. JACC Cardiovasc Imaging. 2017;10(10 Pt A):1165–79.

    Article  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA

    Yibin Xie, Damini Dey & Debiao Li

  2. Department of Medicine, University of California, Los Angeles, Los Angeles, CA, USA

    Damini Dey & Debiao Li

  3. Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA

    Debiao Li

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  1. University of Washington, Seattle, WA, USA

    Chun Yuan

  2. University of Washington, Seattle, WA, USA

    Thomas S. Hatsukami

  3. University of Washington, Seattle, WA, USA

    Mahmud Mossa-Basha

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Xie, Y., Dey, D., Li, D. (2020). Advanced Coronary Artery Vessel Wall Imaging and Future Directions. In: Yuan, C., Hatsukami, T., Mossa-Basha, M. (eds) Vessel Based Imaging Techniques . Springer, Cham. https://doi.org/10.1007/978-3-030-25249-6_13

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