Quantitative and qualitative analysis and interpretation of CT perfusion imaging

Journal of Nuclear Cardiology

Volumn 17, Issue 6, 2010, Pages 1091-1100

  Valdiviezo, Carolina ^a   Ambrose, Marietta ^a   Mehra, Vishal ^a   Lardo, Albert C ^a,b   Lima, Joao A C ^a   George, Richard T ^a  

^a JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b Johns Hopkins University   (United States)

Author keywords

CAD; CT perfusion imaging; CTA; Deconvolution analyses; MDCT; Myocardial blood flow; Myocardial perfusion; Patlak plot; Upslope analyses

Indexed keywords

ARTICLE; COMPUTER ASSISTED TOMOGRAPHY; CONTRAST ENHANCEMENT; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; GOLD STANDARD; HEART MUSCLE BLOOD FLOW; HUMAN; IMAGE ANALYSIS; IMAGE DISPLAY; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; MULTIDETECTOR COMPUTED TOMOGRAPHY; MYOCARDIAL PERFUSION IMAGING; NONHUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; QUANTITATIVE ANALYSIS;

CORONARY ARTERY DISEASE; CORONARY CIRCULATION; DOSE-RESPONSE RELATIONSHIP, DRUG; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IODINE; KINETICS; MYOCARDIUM; PERFUSION; RISK; TIME FACTORS; TOMOGRAPHY, X-RAY COMPUTED; X-RAYS;

EID: 78651289834     PISSN: 10713581     EISSN: None     Source Type: Journal    
DOI: 10.1007/s12350-010-9291-6     Document Type: Article

References (46)

1. Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, et al. Heart disease and stroke statistics-2010 update: A report from the American Heart Association. Circulation 2010;121:e46-215.
2. San Roman JA, Vilacosta I, Castillo JA, Rollan MJ, Hernandez M, Peral V, et al. Selection of the optimal stress test for the diagnosis of coronary artery disease. Heart 1998;80:370-6. (Pubitemid 28470770)
3. Schuijf JD, Wijns W, Jukema JW, Atsma DE, de Roos A, Lamb HJ, et al. Relationship between noninvasive coronary angiography with multi-slice computed tomography and myocardial perfusion imaging. J Am Coll Cardiol 2006;48:2508-14. (Pubitemid 44881213)
4. Iskandrian AS, Chae SC, Heo J, Stanberry CD, Wasserleben V, Cave V. Independent and incremental prognostic value of exercise single-photon emission computed tomographic (SPECT) thallium imaging in coronary artery disease. J Am Coll Cardiol 1993; 22:665-70. (Pubitemid 23256923)
5. 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;52:1724-32.
6. 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;359:2324-36.
7. Blankstein R, Shturman LD, Rogers IS, Rocha-Filho JA, Okada DR, Sarwar A, et al. Adenosine-induced stress myocardial per- fusion imaging using dual-source cardiac computed tomography. J Am Coll Cardiol 2009;54:1072-84.
8. George RT, Arbab-Zadeh A, Miller JM, Kitagawa K, Chang HJ, Bluemke DA, et al. 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. Circ Cardiovasc Imaging 2009;2:174-82.
9. George RT, Ichihara T, Lima JA, Lardo AC. A method for reconstructing the arterial input function during helical CT: Implications for myocardial perfusion distribution imaging. Radiology 2009;255:396-404.
10. George RT, Jerosch-Herold M, Silva C, Kitagawa K, Bluemke DA, Lima JA, et al. Quantification of myocardial perfusion using dynamic 64-detector computed tomography. Invest Radiol 2007;42:815-22.
11. George RT, Silva C, Cordeiro MA, DiPaula A, Thompson DR, McCarthy WF, et al. Multidetector computed tomography myo- cardial perfusion imaging during adenosine stress. J Am Coll Cardiol 2006;48:153-60.
12. Kido T, Kurata A, Higashino H, Inoue Y, Kanza RE, Okayama H, et al. Quantification of regional myocardial blood flow using first- pass multidetector-row computed tomography and adenosine tri- phosphate in coronary artery disease. Circ J 2008;72:1086-91.
13. Kurata A, Mochizuki T, Koyama Y, Haraikawa T, Suzuki J, Shigematsu Y, et al. Myocardial perfusion imaging using adeno- sine triphosphate stress multi-slice spiral computed tomography: Alternative to stress myocardial perfusion scintigraphy. Circ J 2005;69:550-7.
14. Wolfkiel CJ, Ferguson JL, Chomka EV, Law WR, Labin IN, Tenzer ML, et al. Measurement of myocardial blood flow by ultrafast computed tomography. Circulation 1987;76:1262-73.
15. Cademartiri F, Mollet NR, van der Lugt A, McFadden EP, Stijnen T, de Feyter PJ, et al. Intravenous contrast material administration at helical 16-detector row CT coronary angiography: Effect of iodine concentration on vascular attenuation. Radiology 2005;236: 661-5.
16. Rumberger JA, Bell MR. Measurement of myocardial perfusion and cardiac output using intravenous injection methods by ultra- fast (cine) computed tomography. Invest Radiol 1992;27:S40-6.
17. Rumberger JA, Feiring AJ, Lipton MJ, Higgins CB, Ell SR, Marcus ML. Use of ultrafast computed tomography to quantitate regional myocardial perfusion: A preliminary report. J Am Coll Cardiol 1987;9:59-69.
18. Newhouse JH, Murphy RX Jr. Tissue distribution of soluble contrast: Effect of dose variation and changes with time. AJR Am J Roentgenol 1981;136:463-7.
19. Wu XS, Ewert DL, Liu YH, Ritman EL. In vivo relation of intramyocardial blood volume to myocardial perfusion. Evidence supporting microvascular site for autoregulation. Circulation 1992;85:730-7.
20. Kitagawa K, George RT, Arbab-Zadeh A, Lima JAC, Lardo AC. Characterization and correction of beam hardening artifacts during dynamic volume computed tomography myocardial perfusion imaging. Radiology 2010 (in press).
21. Bastarrika G, Ramos-Duran L, Rosenblum MA, Kang DK, Rowe GW, Schoepf UJ. Adenosine-stress dynamic myocardial CT per- fusion imaging: Initial clinical experience. Invest Radiol 2010;45: 306-13.
22. Bell MR, Lerman LO, Rumberger JA. Validation of minimally invasive measurement of myocardial perfusion using electron beam computed tomography and application in human volunteers. Heart 1999;81:628-35.
23. Achenbach S, Giesler T, Ropers D, Ulzheimer S, Derlien H, Schulte C, et al. Detection of coronary artery stenoses by contrast- enhanced, retrospectively electrocardiographically-gated, multi- slice spiral computed tomography. Circulation 2001;103:2535-8.
24. Vanhoenacker PK, Heijenbrok-Kal MH, Van Heste R, Decramer I, Van Hoe LR, Wijns W, et al. Diagnostic performance of multi- detector CT angiography for assessment of coronary artery disease: Meta-analysis. Radiology 2007;244:419-28.
25. Christian TF, Frankish ML, Sisemoore JH, Christian MR, Gent- chos G, Bell SP, et al. Myocardial perfusion imaging with first- pass computed tomographic imaging: Measurement of coronary flow reserve in an animal model of regional hyperemia. J Nucl Cardiol 2010;17:625-30.
26. Christian TF, Rettmann DW, Aletras AH, Liao SL, Taylor JL, Balaban RS, et al. Absolute myocardial perfusion in canines measured by using dual-bolus first-pass MR imaging. Radiology 2004;232:677-84.
27. Hsu LY, Rhoads KL, Holly JE, Kellman P, Aletras AH, Arai AE. Quantitative myocardial perfusion analysis with a dual-bolus contrast-enhanced first-pass MRI technique in humans. J Magn Reson Imaging 2006;23:315-22.
28. Jerosch-Herold M, Wilke N, Stillman AE. Magnetic resonance quantification of the myocardial perfusion reserve with a Fermi function model for constrained deconvolution. Med Phys 1998;25:73-84.
29. Axel L. Tissue mean transit time from dynamic computed tomography by a simple deconvolution technique. Invest Radiol 1983;18:94-9.
30. Bassingthwaighte JB, Raymond GM, Ploger JD, Schwartz LM, Bukowski TR. GENTEX, a general multiscale model for in vivo tissue exchanges and intraorgan metabolism. Philos Trans A 2006;364:1423-42.
31. Kroll K, Wilke N, Jerosch-Herold M, Wang Y, Zhang Y, Bache RJ, et al. Modeling regional myocardial flows from residue functions of an intravascular indicator. Am J Physiol 1996;271: H1643-55.
32. Hackstein N, Bauer J, Hauck EW, Ludwig M, Kramer HJ, Rau WS. Measuring single-kidney glomerular filtration rate on single- detector helical CT using a two-point Patlak plot technique in patients with increased interstitial space. AJR Am J Roentgenol 2003;181:147-56.
33. Hackstein N, Wiegand C, Rau WS, Langheinrich AC. Glomerular filtration rate measured by using triphasic helical CT with a two- point Patlak plot technique. Radiology 2004;230:221-6.
34. Tsuchida T, Sadato N, Yonekura Y, Yamamoto K, Waki A, Sugimoto K, et al. Quantification of regional cerebral blood flow with continuous infusion of technetium-99m-ethyl cysteinate dimer. J Nucl Med 1997;38:1699-702.
35. Patlak CS, Blasberg RG, Fenstermacher JD. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. J Cereb Blood Flow Metab 1983;3:1-7.
36. Rutland MD. A single injection technique for subtraction of blood background in 131I-hippuranrenograms. Br J Radiol 1979;52:134-7.
37. Ichihara T, George RT, Lima JAC, et al. Quantitative Analysis of First-Pass Contrast-Enhanced Myocardial Perfusion Multidetector CT Using a Patlak Plot Method and Extraction Fraction Correction During Adenosine Stress. Paper presented at: Nuclear Science Symposium Conference Record, IEEE, 2009.
38. Daghini E, Primak AN, Chade AR, Zhu X, Ritman EL, McCol-lough CH, et al. Evaluation of porcine myocardial microvascular permeability and fractional vascular volume using 64-slice helical computed tomography (CT). Invest Radiol 2007;42:274-82.
39. Keijer JT, van Rossum AC, van Eenige MJ, Bax JJ, Visser FC, Teule JJ, et al. Magnetic resonance imaging of regional myocardial perfusion in patients with single-vessel coronary artery disease: Quantitative comparison with (201)Thallium-SPECT and coronary angiography. J Magn Reson Imaging 2000;11:607-15.
40. Stoll M, Quentin M, Molojavyi A, Thamer V, Decking UK. Spatial heterogeneity of myocardial perfusion predicts local potassium channel expression and action potential duration. Car- diovasc Res 2008;77:489-96.
41. Taillefer R, Ahlberg AW, Masood Y, White CM, Lamargese I, Mather JF, et al. Acute beta-blockade reduces the extent and severity of myocardial perfusion defects with dipyridamole Tc-99 m sestamibi SPECT imaging. J Am Coll Cardiol 2003;42: 1475-83.
42. Yoon AJ, Melduni RM, Duncan SA, Ostfeld RJ, Travin MI. The effect of beta-blockers on the diagnostic accuracy of vasodilator pharmacologic SPECT myocardial perfusion imaging. J Nucl Cardiol 2009;16:358-67.
43. Kitagawa K, Lardo AC, Lima JAC, George RT. Prospective ECG-gated 320 row detector computed tomography: Implications for CT angiography and perfusion imaging. Int J Cardiovasc Imaging 2009;25:201-8.
44. Rodriguez-Granillo GA, Rosales MA, Degrossi E, Rodriguez AE. Signal density of left ventricular myocardial segments and impact of beam hardening artifact: Implications for myocardial perfusion assessment by multidetector CT coronary angiography. Int J Cardiovasc Imaging 2010;26:345-54.
45. Kitagawa K, George RT, Chang H, Lima JAC, Lardo AC. Myo-cardial perfusion assessment using dynamic-mode 256-row multidetector computed tomography: Influence of beam hardening correction. J Cardiovasc Comput Tomogr 2008;2:S24.
46. George RT, Kitagawa K, Laws K, Lardo AC, Lima JAC. Combined adenosine stress perfusion and coronary angiography using 320-row detector dynamic volume computed tomography in patients with suspected coronary artery disease. Circulation 2008;118:S-936.