Myocardial perfusion imaging with cardiac computed tomography: State of the art

Journal of Cardiovascular Translational Research

Volumn 6, Issue 5, 2013, Pages 695-707

  Patel, Amit R ^a,b   Bhave, Nicole M ^a   Mor Avi, Victor ^a  

^a UNIVERSITY OF CHICAGO   (United States)

^b UNIVERSITY OF CHICAGO MEDICAL CENTER   (United States)

Author keywords

Cardiac computed tomography; Coronary artery disease; Fractional flow reserve; Myocardial perfusion imaging; Stress testing

Indexed keywords

GADOLINIUM; IODINATED CONTRAST MEDIUM; NUCLEAR MAGNETIC RESONANCE IMAGING AGENT;

ANGIOCARDIOGRAPHY; ARTICLE; CAPILLARY DENSITY; CARDIAC IMAGING; CARDIOVASCULAR MAGNETIC RESONANCE; CARDIOVASCULAR PARAMETERS; COMPUTER ASSISTED TOMOGRAPHY; CONTRAST ENHANCEMENT; CORONARY ARTERY BLOOD FLOW; CORONARY ARTERY DISEASE; CORONARY ARTERY OBSTRUCTION; CORONARY HEMODYNAMICS; DIAGNOSTIC ACCURACY; DISEASE SEVERITY; ECHOCARDIOGRAPHY; EXTRACELLULAR SPACE; FRACTIONAL FLOW RESERVE; HEART EJECTION FRACTION; HEART INFARCTION; HEART LEFT VENTRICLE ENDDIASTOLIC VOLUME; HEART LEFT VENTRICLE ENDSYSTOLIC VOLUME; HEART MUSCLE ISCHEMIA; HEART MUSCLE PERFUSION; HEART VENTRICLE WALL MOTION; HUMAN; IMAGE ANALYSIS; IMAGE QUALITY; INTERMETHOD COMPARISON; MULTIDETECTOR COMPUTED TOMOGRAPHY; MYOCARDIAL PERFUSION IMAGING; NON INVASIVE PROCEDURE; NONHUMAN; PRIORITY JOURNAL; RADIATION DOSE; RESTING MYOCARDIAL PERFUSION IMAGING; RISK ASSESSMENT; SINGLE PHOTON EMISSION COMPUTER TOMOGRAPHY; STRESS MYOCARDIAL PERFUSION IMAGING; SYSTOLIC HEART FAILURE; THORAX PAIN; TRANSMURAL PERFUSION RATIO;

CORONARY CIRCULATION; CORONARY DISEASE; FRACTIONAL FLOW RESERVE, MYOCARDIAL; HUMANS; MYOCARDIAL PERFUSION IMAGING; PREDICTIVE VALUE OF TESTS; PROGNOSIS; SEVERITY OF ILLNESS INDEX; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84885663256     PISSN: 19375387     EISSN: 19375395     Source Type: Journal    
DOI: 10.1007/s12265-013-9499-3     Document Type: Article

References (93)

1. Miller, J. M., et al. (2008). Diagnostic performance of coronary angiography by 64-row CT. The New England Journal of Medicine, 359(22), 2324-2336.
2. Min, J. K., et al. (2011). Age- and sex-related differences in all-cause mortality risk based on coronary computed tomography angiography findings results from the International Multicenter CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry) of 23,854 patients without known coronary artery disease. Journal of the American College of Cardiology, 58(8), 849-860.
3. Tonino, P. A., et al. (2009). Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. The New England Journal of Medicine, 360(3), 213-224.
4. Hachamovitch, R., et al. (2003). Comparison of the short-term survival benefit associated with revascularization compared with medical therapy in patients with no prior coronary artery disease undergoing stress myocardial perfusion single photon emission computed tomography. Circulation, 107(23), 2900-2907.
5. Gould, K. L., & Lipscomb, K. (1974). Effects of coronary stenoses on coronary flow reserve and resistance. The American Journal of Cardiology, 34(1), 48-55.
6. Siemers, P. T., et al. (1978). Detection, quantitation and contrast enhancement of myocardial infarction utilizing computerized axial tomography: comparison with histochemical staining and 99mTc-pyrophosphate imaging. Investigative Radiology, 13(2), 103-109.
7. Hoffmann, U., et al. (2004). Acute myocardial infarction: contrast-enhanced multi-detector row CT in a porcine model. Radiology, 231(3), 697-701.
8. Nikolaou, K., et al. (2005). Assessment of myocardial perfusion and viability from routine contrast-enhanced 16-detector-row computed tomography of the heart: preliminary results. European Radiology, 15(5), 864-871.
9. Henneman, M. M., et al. (2006). Comprehensive cardiac assessment with multislice computed tomography: evaluation of left ventricular function and perfusion in addition to coronary anatomy in patients with previous myocardial infarction. Heart, 92(12), 1779-1783.
10. Gupta, M., et al. (2013). Detection and quantification of myocardial perfusion defects by resting single-phase 64-slice cardiac computed tomography angiography compared with SPECT myocardial perfusion imaging. Coronary Artery Disease, 24(4), 290-297.
11. Busch, J. L., et al. (2011). Myocardial hypo-enhancement on resting computed tomography angiography images accurately identifies myocardial hypoperfusion. Journal of Cardiovascular Computed Tomography, 5(6), 412-420.
12. Kachenoura, N., et al. (2009). Value of multidetector computed tomography evaluation of myocardial perfusion in the assessment of ischemic heart disease: comparison with nuclear perfusion imaging. European Radiology, 19(8), 1897-905
13. Zelis, R., et al. (1976). Reflex vasodilation induced by coronary angiography in human subjects. Circulation, 53(3), 490-493.
14. Wagner, A., et al. (2003). Contrast-enhanced MRI and routine single photon emission computed tomography (SPECT) perfusion imaging for detection of subendocardial myocardial infarcts: an imaging study. Lancet, 361(9355), 374-379.
15. Kachenoura, N., et al. (2009). Combined assessment of coronary anatomy and myocardial perfusion using multidetector computed tomography for the evaluation of coronary artery disease. The American Journal of Cardiology, 103(11), 1487-1494.
16. Iwasaki, K., & Matsumoto, T. (2011). Myocardial perfusion defect in patients with coronary artery disease demonstrated by 64-multidetector computed tomography at rest. Clinical Cardiology, 34(7), 454-460.
17. Nagao, M., et al. (2008). Quantification of myocardial perfusion by contrast-enhanced 64-MDCT: characterization of ischemic myocardium. AJR. American Journal of Roentgenology, 191(1), 19-25.
18. Nagao, M., et al. (2009). Detection of myocardial ischemia using 64-slice MDCT. Circulation Journal, 73(5), 905-911.
19. Litt, H. I., et al. (2012). CT angiography for safe discharge of patients with possible acute coronary syndromes. The New England Journal of Medicine, 366(15), 1393-1403.
20. Hoffmann, U., et al. (2012). Coronary CT angiography versus standard evaluation in acute chest pain. The New England Journal of Medicine, 367(4), 299-308.
21. Bezerra, H. G., et al. (2011). Incremental value of myocardial perfusion over regional left ventricular function and coronary stenosis by cardiac CT for the detection of acute coronary syndromes in high-risk patients: a subgroup analysis of the ROMICAT trial. Journal of Cardiovascular Computed Tomography, 5(6), 382-391.
22. Feuchtner, G. M., et al. (2012). Evaluation of myocardial CT perfusion in patients presenting with acute chest pain to the emergency department: comparison with SPECT-myocardial perfusion imaging. Heart, 98(20), 1510-1517.
23. Schepis, T., et al. (2010). Prevalence of first-pass myocardial perfusion defects detected by contrast-enhanced dual-source CT in patients with non-ST segment elevation acute coronary syndromes. European Radiology, 20(7), 1607-14
24. Lessick, J., et al. (2012). Multidetector computed tomography predictors of late ventricular remodeling and function after acute myocardial infarction. European Journal of Radiology, 81(10), 2648-2657.
25. Rodriguez-Granillo, G. A., et al. (2010). Chronic myocardial infarction detection and characterization during coronary artery calcium scoring acquisitions. Journal of Cardiovascular Computed Tomography, 4(2), 99-107.
26. Gupta, M., et al. (2010). Non-contrast cardiac computed tomography can accurately detect chronic myocardial infarction: validation study. Journal of Nuclear Cardiology, 18(1), 96-103
27. Fuchs, T. A., et al. (2012). Hypodense regions in unenhanced CT identify nonviable myocardium: validation versus 18F-FDG PET. European Journal of Nuclear Medicine and Molecular Imaging, 39(12), 1920-1926.
28. Baks, T., et al. (2006). Multislice computed tomography and magnetic resonance imaging for the assessment of reperfused acute myocardial infarction. Journal of the American College of Cardiology, 48(1), 144-152.
29. Mahnken, A. H., et al. (2005). Assessment of myocardial viability in reperfused acute myocardial infarction using 16-slice computed tomography in comparison to magnetic resonance imaging. Journal of the American College of Cardiology, 45(12), 2042-2047.
30. Sato, A., et al. (2012). Prognostic value of myocardial contrast delayed enhancement with 64-slice multidetector computed tomography after acute myocardial infarction. Journal of the American College of Cardiology, 59(8), 730-738.
31. le Polain de Waroux, J.-B., et al.(2008). Combined coronary and late-enhanced multidetector-computed tomography for delineation of the etiology of left ventricular dysfunction: comparison with coronary angiography and contrast-enhanced cardiac magnetic resonance imaging. European Heart Journal 29(20), 2544-51.
32. Dwivedi, G., et al. (2012). Scar imaging using multislice computed tomography versus metabolic imaging by F-18 FDG positron emission tomography: a pilot study. International Journal of Cardiology doi: 10.1016/j.ijcard.2012.09. 218
33. Chen, X., et al. (2012). A framework of whole heart extracellular volume fraction estimation for low-dose cardiac CT images. IEEE Transactions on Information Technology in Biomedicine, 16(5), 842-851.
34. Nacif, M. S., et al. (2012). Interstitial myocardial fibrosis assessed as extracellular volume fraction with low-radiation-dose cardiac CT. Radiology, 264(3), 876-883.
35. Nacif, M. S., et al. (2013). 3D left ventricular extracellular volume fraction by low-radiation dose cardiac CT: assessment of interstitial myocardial fibrosis. Journal of Cardiovascular Computed Tomography, 7(1), 51-57.
36. Ghoshhajra, B.B., et al. (2012). Infarct detection with a comprehensive cardiac CT protocol. Journal of Cardiovascular Computed Tomography, 6(1), 14-23
37. Goetti, R., et al. (2011). Delayed enhancement imaging of myocardial viability: low-dose high-pitch CT versus MRI. European Radiology, 21(10), 2091-2099.
38. Spiro, A. J., et al. (2013). Resting cardiac 64-MDCT does not reliably detect myocardial ischemia identified by radionuclide imaging. AJR. American Journal of Roentgenology, 200(2), 337-342.
39. Mor-Avi, V., et al. (2012). Quantitative three-dimensional evaluation of myocardial perfusion during regadenoson stress using multidetector computed tomography. Journal of Computer Assisted Tomography, 36(4), 443-449.
40. Tarroni, G., et al. (2012). Myocardial perfusion: near-automated evaluation from contrast-enhanced MR images obtained at rest and during vasodilator stress. Radiology, 265(2), 576-583.
41. George, R. T., et al. (2006). Multidetector computed tomography myocardial perfusion imaging during adenosine stress. Journal of the American College of Cardiology, 48(1), 153-160.
42. Ko, B. S., et al. (2012). Combined CT coronary angiography and stress myocardial perfusion imaging for hemodynamically significant stenoses in patients with suspected coronary artery disease: a comparison with fractional flow reserve. JACC. Cardiovascular Imaging, 5(11), 1097-1111.
43. Ko, B. S., et al. (2012). Computed tomography stress myocardial perfusion imaging in patients considered for revascularization: a comparison with fractional flow reserve. European Heart Journal, 33(1), 67-77.
44. Rocha-Filho, J. A., et al. (2010). Incremental value of adenosine-induced stress myocardial perfusion imaging with dual-source CT at cardiac CT angiography. Radiology, 254(2), 410-419.
45. Bettencourt, N., et al. (2011). Incremental value of an integrated adenosine stress-rest MDCT perfusion protocol for detection of obstructive coronary artery disease. Journal of Cardiovascular Computed Tomography, 5(6), 392-405.
46. Magalhaes, T. A., et al. (2011). Additional value of dipyridamole stress myocardial perfusion by 64-row computed tomography in patients with coronary stents. Journal of Cardiovascular Computed Tomography, 5(6), 449-458.
47. Bettencourt, N., et al. (2013). Direct comparison of cardiac magnetic resonance and multidetector computed tomography stress-rest perfusion imaging for detection of coronary artery disease. Journal of the American College of Cardiology, 61(10), 1099-1107.
48. George, R. T., et al. (2012). Computed tomography myocardial perfusion imaging with 320-row detector computed tomography accurately detects myocardial ischemia in patients with obstructive coronary artery disease. Circulation. Cardiovascular Imaging, 5(3), 333-340.
49. Blankstein, R., et al. (2009). Adenosine-induced stress myocardial perfusion imaging using dual-source cardiac computed tomography. Journal of the American College of Cardiology, 54(12), 1072-1084.
50. George, R.T., et al. (2009). Adenosine stress 64 and 256 row detector computed tomography angiography and perfusion imaging: a pilot study evaluating the transmural extent of perfusion abnormalities to predict atherosclerosis causing myocardial ischemia. Circulation: Cardiovascular Imaging 2(3), 174-82.
51. Wang, Y., et al. (2012). Adenosine-stress dynamic myocardial perfusion imaging with second-generation dual-source CT: comparison with conventional catheter coronary angiography and SPECT nuclear myocardial perfusion imaging. AJR. American Journal of Roentgenology, 198(3), 521-529.
52. Nasis, A., et al. (2013). Diagnostic accuracy of combined coronary angiography and adenosine stress myocardial perfusion imaging using 320-detector computed tomography: pilot study. European Radiology 23(7), 1812-21
53. Okada, D. R., et al. (2010). Direct comparison of rest and adenosine stress myocardial perfusion CT with rest and stress SPECT. Journal of Nuclear Cardiology, 17(1), 27-37.
54. Tamarappoo, B. K., et al. (2010). Comparison of the extent and severity of myocardial perfusion defects measured by CT coronary angiography and SPECT myocardial perfusion imaging. Journal of the American College of Cardiology: Cardiovascular Imaging, 3(10), 1010-1019.
55. Qayyum, A.A., et al. (2013). Value of cardiac 320-multidetector computed tomography and cardiac magnetic resonance imaging for assessment of myocardial perfusion defects in patients with known chronic ischemic heart disease. Int J Cardiovasc Imaging
56. Patel, A. R., et al. (2011). Detection of myocardial perfusion abnormalities using ultra-low radiation dose regadenoson stress multidetector computed tomography. Journal of Cardiovascular Computed Tomography, 5(4), 247-254.
57. Ghoshhajra, B. B., et al. (2011). A comparison of reconstruction and viewing parameters on image quality and accuracy of stress myocardial CT perfusion. Journal of Cardiovascular Computed Tomography, 5(6), 459-466.
58. Kachenoura, N., et al. (2010). Volumetric quantification of myocardial perfusion using analysis of multi-detector computed tomography 3D datasets: comparison with nuclear perfusion imaging. European Radiology, 20(2), 337-347.
59. Cury, R. C., et al. (2011). Dipyridamole stress and rest transmural myocardial perfusion ratio evaluation by 64 detector-row computed tomography. Journal of Cardiovascular Computed Tomography, 5(6), 443-448.
60. Hosokawa, K., et al. (2011). Transmural perfusion gradient in adenosine triphosphate stress myocardial perfusion computed tomography. Circulation Journal, 75(8), 1905-1912.
61. George, R. T., et al. (2007). Quantification of myocardial perfusion using dynamic 64-detector computed tomography. Investigative Radiology, 42(12), 815-822.
62. Christian, T. F., et al. (2010). Myocardial perfusion imaging with first-pass computed tomographic imaging: measurement of coronary flow reserve in an animal model of regional hyperemia. Journal of Nuclear Cardiology, 17(4), 625-630.
63. Kido, T., et al. (2008). Quantification of regional myocardial blood flow using first-pass multidetector-row computed tomography and adenosine triphosphate in coronary artery disease. Circulation Journal, 72(7), 1086-1091.
64. So, A., et al. (2012). Non-invasive assessment of functionally relevant coronary artery stenoses with quantitative CT perfusion: preliminary clinical experiences. European Radiology, 22(1), 39-50.
65. Shikata, F., et al. (2010). Regional myocardial blood flow measured by stress multidetector computed tomography as a predictor of recovery of left ventricular function after coronary artery bypass grafting. American Heart Journal, 160(3), 528-534.
66. Mahnken, A. H., et al. (2010). Quantitative whole heart stress perfusion CT imaging as noninvasive assessment of hemodynamics in coronary artery stenosis: preliminary animal experience. Investigative Radiology, 45(6), 298-305.
67. Bamberg, F., et al. (2012). Accuracy of dynamic computed tomography adenosine stress myocardial perfusion imaging in estimating myocardial blood flow at various degrees of coronary artery stenosis using a porcine animal model. Investigative Radiology, 47(1), 71-77.
68. Bastarrika, G., et al. (2010). Adenosine-stress dynamic myocardial CT perfusion imaging: initial clinical experience. Investigative Radiology, 45(6), 306-313.
69. Ho, K. T., et al. (2010). Stress and rest dynamic myocardial perfusion imaging by evaluation of complete time-attenuation curves with dual-source CT. JACC. Cardiovascular Imaging, 3(8), 811-820.
70. Bamberg, F., et al. (2011). Detection of hemodynamically significant coronary artery stenosis: incremental diagnostic value of dynamic CT-based myocardial perfusion imaging. Radiology, 260(3), 689-698.
71. Greif, M., et al. (2013). CT stress perfusion imaging for detection of haemodynamically relevant coronary stenosis as defined by FFR. Heart, 99(14): 1004-11
72. Ruzsics, B., et al. (2009). Comparison of dual-energy computed tomography of the heart with single photon emission computed tomography for assessment of coronary artery stenosis and of the myocardial blood supply. The American Journal of Cardiology, 104(3), 318-326.
73. Arnoldi, E., et al. (2011). CT detection of myocardial blood volume deficits: dual-energy CT compared with single-energy CT spectra. Journal of Cardiovascular Computed Tomography, 5(6), 421-429.
74. So, A., et al. (2012). Prospectively ECG-triggered rapid kV-switching dual-energy CT for quantitative imaging of myocardial perfusion. JACC. Cardiovascular Imaging, 5(8), 829-836.
75. Ko, S. M., et al. (2012). Diagnostic performance of combined noninvasive anatomic and functional assessment with dual-source CT and adenosine-induced stress dual-energy CT for detection of significant coronary stenosis. AJR. American Journal of Roentgenology, 198(3), 512-520.
76. Ko, S. M., et al. (2011). Myocardial perfusion imaging using adenosine-induced stress dual-energy computed tomography of the heart: comparison with cardiac magnetic resonance imaging and conventional coronary angiography. European Radiology, 21(1), 26-35.
77. Weininger, M., et al. (2012). Adenosine-stress dynamic real-time myocardial perfusion CT and adenosine-stress first-pass dual-energy myocardial perfusion CT for the assessment of acute chest pain: initial results. European Journal of Radiology, 81(12), 3703-3710.
78. Meyer, M., et al. (2012). Cost-effectiveness of substituting dual-energy CT for SPECT in the assessment of myocardial perfusion for the workup of coronary artery disease. European Journal of Radiology, 81(12), 3719-3725.
79. Gramer, B. M., et al. (2012). Impact of iterative reconstruction on CNR and SNR in dynamic myocardial perfusion imaging in an animal model. European Radiology, 22(12), 2654-2661.
80. Feuchtner, G., et al. (2011). Adenosine stress high-pitch 128-slice dual source myocardial computed tomography perfusion for imaging of reversible myocardial ischemia: comparison with magnetic resonance imaging. Circulation: Cardiovascular Imaging 4(5), 540-9
81. Kim, S.M., Y.N. Kim, and Y.H. Choe. (2013). Adenosine-stress dynamic myocardial perfusion imaging using 128-slice dual-source CT: optimization of the CT protocol to reduce the radiation dose. Int J Cardiovasc Imaging
82. Rodriguez-Granillo, G. A., et al. (2010). Signal density of left ventricular myocardial segments and impact of beam hardening artifact: implications for myocardial perfusion assessment by multidetector CT coronary angiography. The International Journal of Cardiovascular Imaging, 26(3), 345-354.
83. Kitagawa, K., et al. (2010). Characterization and correction of beam-hardening artifacts during dynamic volume CT assessment of myocardial perfusion. Radiology, 256(1), 111-118.
84. So, A., et al. (2009). Beam hardening correction in CT myocardial perfusion measurement. Physics in Medicine and Biology, 54(10), 3031-3050.
85. Lauzier, P. T., et al. (2012). Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging. Medical Physics, 39(7), 4079-4092.
86. Stenner, P., et al. (2010). Dynamic iterative beam hardening correction (DIBHC) in myocardial perfusion imaging using contrast-enhanced computed tomography. Investigative Radiology, 45(6), 314-323.
87. Stenner, P., et al. (2009). Partial scan artifact reduction (PSAR) for the assessment of cardiac perfusion in dynamic phase-correlated CT. Medical Physics, 36(12), 5683-5694.
88. Ramirez-Giraldo, J. C., et al. (2012). A strategy to decrease partial scan reconstruction artifacts in myocardial perfusion CT: phantom and in vivo evaluation. Medical Physics, 39(1), 214.
89. Yamada, M., et al. (2012). Beam-hardening correction for virtual monochromatic imaging of myocardial perfusion via fast-switching dual-kVp 64-slice computed tomography: a pilot study using a human heart specimen. Circulation Journal, 76(7), 1799-1801.
90. George, R. T., et al. (2011). Diagnostic performance of combined noninvasive coronary angiography and myocardial perfusion imaging using 320-MDCT: the CT angiography and perfusion methods of the CORE320 multicenter multinational diagnostic study. AJR. American Journal of Roentgenology, 197(4), 829-837.
91. Vavere, A. L., et al. (2011). Diagnostic performance of combined noninvasive coronary angiography and myocardial perfusion imaging using 320 row detector computed tomography: design and implementation of the CORE320 multicenter, multinational diagnostic study. Journal of Cardiovascular Computed Tomography, 5(6), 370-381.
92. Mehra, V. C., et al. (2011). A stepwise approach to the visual interpretation of CT-based myocardial perfusion. Journal of Cardiovascular Computed Tomography, 5(6), 357-369.
93. Cury, R. C., et al. (2010). Dipyridamole stress and rest myocardial perfusion by 64-detector row computed tomography in patients with suspected coronary artery disease. The American Journal of Cardiology, 106(3), 310-315.