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Current state of myocardial perfusion assessed by computed tomography

Authors: Boldyreva K.M., Makarenko V.N., Shurupova I.V., Rychina I.E., Dorofeev A.V., Aslanidis I.P.

Company: Bakoulev National Medical Research Center for Cardiovascular Surgery, Moscow, Russian Federation

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Type:  Reviews


DOI: https://doi.org/10.24022/1997-3187-2022-16-2-134-149

For citation: Boldyreva K.M., Makarenko V.M., Shurupova I.V., Rychina I.E., Dorofeev A.V., Aslanidis I.P. Current state of myocardial perfusion assessmed by computed tomography. Creative Cardiology. 2022; 16 (2): 134–49 (in Russ.). DOI: 10.24022/1997-3187-2022-16-2-134-149

Received / Accepted:  15.03.2022 / 05.06.2022

Keywords: computed tomography multislice computed tomography of the coronary arteries dual-energy computed tomography myocardial perfusion myocardial perfusion with computed tomography dynamic and static computed tomographic perfusion

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Abstract

In this article we considering dates of world literatures about use various method computed tomography (CT) for study of myocardial perfusion. We talk about effective functional reserve of blood flow and visualization myocardial perfusion for hemodynamically significant stenosis of coronary arteries which assessment with help of CT. In last decade there is a few new methods for assessment of functional interpretation damage of coronary arteries, based of CT. Today there are few methods for determination ischemia of myocardium, but alternative like CT which makes with CT-angiography may have practically and potentially economical advantage. Interest to CT like a method for physiological assessment of myocardial perfusion in rest and stress status there is a long ago but in last time rise from year to year. From that moment like myocardial perfusion was additional to visualization of coronary arteries, CT have huge potential for determination functional status of myocardium within the framework of one noninvasive examination. Further technically innovation with use different generation of CT-scans and determination of diagnostics references value for differentiation damage of arteries will be have key for wide clinical introducing noninvasive methods for assessment status of myocardial and coronary arteries with patient who have different diseases.

References

  1. Bockeria L.A. Cardiovascular surgery – 2019. Moscow; 2020 (in Russ.).
  2. Barbarash O.L., Karpov Yu.A., Kashtalap V.V., Boschenko A.A., Ruda M.M., Akchurin R.S. et al. Diagnosis and treatment of chronic ischemic heart disease. Practical advice. Cardiological Bulletin. 2015; 3: 3–33 (in Russ.). DOI: 10.15829/29/1560-4071-2020-4076
  3. Pijls N.H., van Schaardenburgh P., Manoharan G., Boersma E., Bech J.W., van't Veer M. et al. Percutaneous coronary intervention of functionally nonsignificant stenosis: 5-year follow-up of the DEFER Study. J. Am. Coll. Cardiol. 2007; 49 (21): 2105–11. DOI: 10.1016/j.jacc.2007.01.087
  4. Tonino P.A., De Bruyne B., Pijls N.H., Siebert U., Ikeno F., van' t Veer M. et al. FAME Study Investigators. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N. Engl. J. Med. 2009; 360 (3): 213–24. DOI: 10.1056/NEJMoa0807611
  5. Collet C., Onuma Y., Andreini D., Sonck J., Pompilio G., Mushtaq S. et al. Coronary computed tomography angiography for heart team decisionmaking in multivessel coronary artery disease. Eur. Heart J. 2018; 39 (41): 3689–98. DOI: 10.1093/eurheartj/ehy581
  6. Nielsen L.H., Ortner N., Nørgaard B.L., Achenbach S., Leipsic J., Abdulla J. The diagnostic accuracy and outcomes after coronary computed tomography angiography vs. conventional functional testing in patients with stable angina pectoris: a systematic review and meta-analysis. Eur. Heart J. Cardiovasc. Imaging. 2014; 15 (9): 961–71. DOI: 10.1093/ehjci/jeu027
  7. George R.T., Jerosch-Herold M., Silva C., Kitagawa K., Bluemke D.A., Lima J.A. et al. Quantification of myocardial perfusion using dynamic 64-detector computed tomography. Invest. Radiol. 2007; 42 (12): 815–22. DOI: 10.1097/RLI. 0b013e318124a884
  8. Knuuti J., Wijns W., Saraste A., Capodanno D., Barbato E., Funck-Brentano C. et al. ESC Scientific Document Group. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur. Heart J. 2020; 41 (3): 407–77. DOI: 10.1093/eurheartj/ehz425
  9. Danad I., Szymonifka J., Schulman-Marcus J., Min J.K. Static and dynamic assessment of myocardial perfusion by computed tomography. Eur. Heart J. Cardiovasc. Imaging. 2016; 17 (8): 836–44. DOI: 10.1093/ehjci/jew044
  10. Johnson T.R., Krauss B., Sedlmair M., Grasruck M., Bruder H., Morhard D. et al. Material differentiation by dual energy CT: initial experience. Eur. Radiol. 2007; 17 (6): 1510–7. DOI: 10.1007/s00330-006-0517-6
  11. Assen M., Vonder M., Pelgrim G.J., Von Knebel Doeberitz P.L., Veligenthart R. Computed tomography for myocardial characterization in ischemic heart disease: a state-of-the-art review. Eur. Radiol. Exp. 2020: 36. DOI: 10.1186/s41747-020-00158-1
  12. Ko S.M., Park J.H., Hwang H.K., Song M.G. Direct comparison of stress- and rest-dual-energy computed tomography for detection of myocardial perfusion defect. Int. J. Cardiovasc. Imaging. 2014; 30 (1): 41–53. DOI: 10.1007/s10554-014-0410-3
  13. Ko B.S., Linde J.J., Ihdayhid A.R., Norgaard B.L., Kofoed K.F., Sørgaard M. et al. Non-invasive CTderived fractional flow reserve and static rest and stress CT myocardial perfusion imaging for detection of haemodynamically significant coronary stenosis. Int. J. Cardiovasc. Imaging. 2019; 35 (11): 2103–12. DOI: 10.1007/s10554-019-01658-x
  14. Bamberg F., Becker A., Schwarz F., Marcus R.P., Greif M., von Ziegler F. et al. Detection of hemodynamically significant coronary artery stenosis: incremental diagnostic value of dynamic CT-based myocardial perfusion imaging. Radiology. 2011; 260 (3): 689–98. DOI: 10.1148/radiol.11110638
  15. Taylor C.A., Fonte T.A., Min J.K. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J. Am. Coll. Cardiol. 2013; 61 (22): 2233–41. DOI: 10.1016/j.jacc. 2012.11.083
  16. Nørgaard B.L., Leipsic J., Gaur S., Seneviratne S., Ko B.S., Ito H. et al. NXT Trial Study Group. Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). J. Am. Coll. Cardiol. 2014; 63 (12): 1145–55. DOI: 10.1016/j.jacc.2013.11.043
  17. Ko B.S., Cameron J.D., Munnur R.K., Wong D.T.L., Fujisawa Y., Sakaguchi T. et al. Noninvasive CTDerived FFR Based on Structural and Fluid Analysis: A Comparison With Invasive FFR for Detection of Functionally Significant Stenosis. JACC Cardiovasc. Imaging. 2017; 10 (6): 663–73. DOI: 10.1016/j.jcmg.2016.07.005
  18. Tesche C., De Cecco C.N., Baumann S., Renker M., McLaurin T.W., Duguay T.M. et al. Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling. Radiology. 2018; 288 (1): 64–72. DOI: 10.1148/radiol. 2018171291
  19. Schoepf U. (Ed.) CT of the Heart. Humana Press; 2019. DOI: 10.1007/978-1-60327-237-7
  20. Vliegenthart R., Henzler T., Moscariello A., Ruzsics B., Bastarrika G., Oudkerk M. et al. CT of coronary heart disease: Part 1, CT of myocardial infarction, ischemia, and viability. Am. J. Roentgenol. 2012; 198 (3): 531–47. DOI: 10.2214/AJR. 11.7082
  21. Abbara S., Blanke P., Maroules C.D., Cheezum M., Choi A.D., Han B.K. 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. DOI: 10.1016/j.jcct.2016.10.002
  22. Patel A.R., Bamberg F., Branch K., Carrascosa P., Chen M., Cury R.C. et al. Society of cardiovascular computed tomography expert consensus document on myocardial computed tomography perfusion imaging. J. Cardiovasc. Comput. Tomogr. 2020; 14 (1): 87–100. DOI: 10.1016/j.jcct.2019.10.003
  23. Coenen A., Lubbers M.M., Kurata A., Kono A., Dedic A., Chelu R.G. et al. Diagnostic value of transmural perfusion ratio derived from dynamic CT-based myocardial perfusion imaging for the detection of haemodynamically relevant coronary artery stenosis. Eur. Radiol. 2017; 27 (6): 2309–16. DOI: 10.1007/s00330-016-4567-0
  24. Hulten E., Ahmadi A., Blankstein R. CT Assessment of myocardial perfusion and fractional flow reserve. Prog. Cardiovasc. Dis. 2015; 57 (6): 623–31. DOI: 10.1016/j.pcad.2015.03.003
  25. Branch K.R., Haley R.D., Bittencourt M.S., Patel A.R., Hulten E., Blankstein R. Myocardial computed tomography perfusion. Cardiovasc. Diagn. Ther. 2017; 7 (5): 452–62. DOI: 10.21037/cdt.2017.06.11
  26. Mahnken A.H., Lautenschläger S., Fritz D., Koos R., Scheuering M. Perfusion weighted color maps for enhanced visualization of myocardial infarction by MSCT: preliminary experience. Int. J. Cardiovasc. Imaging. 2008; 24: 883–90. DOI: 10.1007/s10554-008-9318-0
  27. Wang R., Yu W., Wang Y., He Y., Yang L., Bi T. et al. Incremental value of dual-energy CT to coronary CT angiography for the detection of significant coronary stenosis: comparison with quantitative coronary angiography and single photon emission computed tomography. Int. J. Cardiovasc. Imaging. 2011; 27: 647–56. DOI: 10.1007/s10554-011-9881-7
  28. Bastarrika G., Ramos-Duran L., Rosenblum M.A., Kang D.K., Rowe G.W., Schoepf U.J. Adenosinestress dynamic myocardial CT perfusion imaging: initial clinical experience. Invest. Radiol. 2010; 45 (6): 306–13. DOI: 10.1097/RLI.0b013e3181dfa2f2
  29. Weininger M., Schoepf U.J., Ramachandra A., Fink C., Rowe G.W., Costello P. et al. Adenosinestress 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. Eur. J. Radiol. 2012; 81 (12): 3703–10. DOI: 10.1016/j.ejrad.2010.11.022
  30. Bamberg F., Marcus R.P., Becker A., Hildebrandt K., Bauner K., Schwarz F. et al. Dynamic myocardial CT perfusion imaging for evaluation of myocardial ischemia as determined by MR imaging. JACC Cardiovasc Imaging. 2014; 7 (3): 267–77. DOI: 10.1016/j.jcmg.2013.06.008
  31. Delgado Sánchez-Gracián C., Oca Pernas R., Trinidad López C., Santos Armentia E., Vaamonde Liste A., Vázquez Caamaño M. et al. Quantitative myocardial perfusion with stress dual-energy CT: iodine concentration differences between normal and ischemic or necrotic myocardium. Initial experience. Eur. Radiol. 2016; 26: 3199–207. DOI: 10.1007/s00330-015-4128-y
  32. Hulten E.A., Bittencourt M.S., Ghoshhajra B., Blankstein R. Stress CT perfusion: coupling coronary anatomy with physiology. J. Nucl. Cardiol. 2012; 19 (3): 588–600. DOI: 10.1007/s12350-012- 9546-5
  33. Caruso D., De Santis D., Schoepf U.J., Zerunian M., Eid M., Varga-Szemes A. et al. CT myocardial perfusion: state of the science. Minerva Cardioangiol. 2017; 65 (3): 252–64. DOI: 10.23736/S0026-4725.16.04281-X
  34. Kurata A., Mochizuki T., Koyama Y., Haraikawa T., Suzuki J., Shigematsu Y. et al. Myocardial perfusion imaging using adenosine triphosphate stress multi-slice spiral computed tomography: alternative to stress myocardial perfusion scintigraphy. Circ. J. 2005; 69 (5): 550–7. DOI: 10.1253/circj.69.550
  35. Mahnken A.H., Klotz E., Pietsch H., Schmidt B., Allmendinger T., Haberland U. et al. Quantitative whole heart stress perfusion CT imaging as noninvasive assessment of hemodynamics in coronary artery stenosis: preliminary animal experience. Invest. Radiol. 2010; 45 (6): 298–305. DOI: 10.1097/RLI.0b013e3181dfa3cf
  36. Ho K.T., Chua K.C., Klotz E., Panknin C. Stress and rest dynamic myocardial perfusion imaging by evaluation of complete time-attenuation curves with dual-source CT. JACC. Cardiovasc. Imaging. 2010; 3 (8): 811–20. DOI: 10.1016/j.jcmg.2010.05.009
  37. Leipsic J., Yang T.H., Thompson A., Koo B.K., Mancini G.B., Taylor C. et al. CT angiography 148 Creative Cardiology. 2022; 16 (2) DOI: 10.24022/1997-3187-2022-16-2-134-149 Reviews (CTA) and diagnostic performance of noninvasive fractional flow reserve: results from the Determi-nation of Fractional Flow Reserve by Anatomic CTA (DeFACTO) study. Am. J. Roentgenol. 2014; 202 (5): 989–94. DOI: 10.2214/AJR.13.11441
  38. Magalhães T.A., Cury R.C., Cerci R.J., Parga Filho J.R., Gottlieb I., Nacif M.S. et al. Evaluation of myocardial perfusion by computed tomography – principles, technical background and recommendations. Arq. Bras. Cardiol. 2019; 113 (4): 758–67. DOI: 10.5935/abc.20190217
  39. Koo B.K., Erglis A., Doh J.H., Daniels D.V., Jegere S., Kim H.S. et al. Diagnosis of ischemiacausing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. J. Am. Coll. Cardiol. 2011; 58 (19): 1989–97. DOI: 10.1016/j.jacc.2011.06.066
  40. Min J.K., Leipsic J., Pencina M.J., Berman D.S., Koo B.K., van Mieghem C. et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA. 2012; 308 (12): 1237–45. DOI: 10.1001/2012.jama.11274
  41. Gognieva D., Gamilov T., Pryamonosov R., Betelin V., Ternovoy S.K., Serova N.S. et al. One-Dimensional Mathematical Model-Based Automated Assessment of Fractional Flow Reserve in a Patient with Silent Myocardial Ischemia. Am. J. Case. Rep. 2018; 19: 724–8. DOI: 10.12659/AJCR.908449
  42. Osawa K., Miyoshi T., Koyama Y., Hashimoto K., Sato S., Nakamura K. et al. Additional diagnostic value of first-pass myocardial perfusion imaging without stress when combined with 64-row detector coronary CT angiography in patients with coronary artery disease. Heart. 2014; 100 (13): 1008–15. DOI: 10.1136/heartjnl-2013-305468
  43. Pontone G., Baggiano A., Andreini D., Guaricci A.I., Guglielmo M., Muscogiuri G. et al. Diagnostic accuracy of simultaneous evaluation of coronary arteries and myocardial perfusion with single stress cardiac computed tomography acquisition compared to invasive coronary angiography plus invasive fractional flow reserve. Int. J. Cardiol. 2018; 273: 263–8. DOI: 10.1016/j.ijcard.2018.09.065
  44. Rochitte C.E., George R.T., Chen M.Y., ArbabZadeh A., Dewey M., Miller J.M. et al. Computed tomography angiography and perfusion to assess coronary artery stenosis causing perfusion defects by single photon emission computed tomography: the CORE320 study. Eur. Heart J. 2013; 35 (17): 1120–30. DOI: 10.1093/eurheartj/eht488
  45. Nasis A., Ko B.S., Leung M.C., Antonis P.R., Nandurkar D., Wong D.T. et al. Diagnostic accuracy of combined coronary angiography and adenosine stress myocardial perfusion imaging using 320-detector computed tomography: pilot study. Eur. Radiol. 2013; 23 (7): 1812–21. DOI: 10.1007/s00330-013-2788-z
  46. Pelgrim G.J., Dorrius M., Xie X., den Dekker M.A., Schoepf U.J., Henzler T. et al. The dream of a onestop-shop: Meta-analysis on myocardial perfusion CT. Eur. J. Radiol. 2015; 84 (12): 2411–20. DOI: 10.1016/j.ejrad.2014.12.032
  47. Tashakkor A.Y., Nicolaou S., Leipsic J., Mancini G.B. The emerging role of cardiac computed tomography for the assessment of coronary perfusion: a systematic review and meta-analysis. Can. J. Cardiol. 2012; 28 (4): 413–22. DOI: 10.1016/j.cjca.2012.02.010
  48. Kikuchi Y., Oyama-Manabe N., Naya M., Manabe O., Tomiyama Y., Sasaki T. et al. Quantification of myocardial blood flow using dynamic 320-row multi-detector CT as compared with 15O-H2O PET. Eur. Radiol. 2014; 24 (7): 1547–56. DOI: 10.1007/s00330-014-3164-3
  49. Pontone G., Baggiano A., Andreini D., Guaricci A.I., Guglielmo M., Muscogiuri G. et al. Dynamic stress computed tomography perfusion with a whole-heart coverage scanner in addition to coronary computed tomography angiography and fractional flow reserve computed tomography derived. JACC. Cardiovasc. Imaging. 2019; 12 (12): 2460–71. DOI: 10.1016/j.jcmg.2019.02.015
  50. Tanabe Y., Kido T., Uetani T., Kurata A., Kono T., Ogimoto A. et al. Differentiation of myocardial ischemia and infarction assessed by dynamic computed tomography perfusion imaging and comparison with cardiac magnetic resonance and singlephoton emission computed tomography. Eur. Radiol. 2016; 26 (11): 3790–801. DOI: 10.1007/s00330-016-4238-1
  51. Wichmann J.L., Meinel F.G., Schoepf U.J., Lo G.G., Choe Y.H., Wang Y. et al. Absolute versus relative myocardial blood flow by dynamic CT myocardial perfusion imaging in patients with anatomic coronary artery disease. Am. J. Roentgenol. 2015; 205 (1): 67–72. DOI: 10.2214/AJR.14.14087
  52. Baxa J., Hromádka M., Šedivý J., Štěpánková L., Moláček J., Schmidt B. et al. Regadenoson-Stress Dynamic Myocardial Perfusion Improves Diagnostic Performance of CT Angiography in Assessment of Intermediate Coronary Artery Stenosis in Asymptomatic Patients. Biomed. Res. Int. 2015; 1–7. DOI: 10.1155/2015/105629
  53. Einstein A.J. Effects of radiation exposure from cardiac imaging: how good are the data? J. Am. Coll. Cardiol. 2012; 59 (6): 553–65. DOI: 10.1016/j.jacc.2011.08.079
  54. Williams M.C., Newby D.E. CT myocardial perfusion imaging: current status and future directions. Clin Radiol. 2016; 71 (8): 739–49. DOI: 10.1016/j.crad.2016.03.006
  55. Caruso D., Eid M., Schoepf U.J., Jin K.N., VargaSzemes A., Tesche C. et al. Dynamic CT myocardial perfusion imaging. Eur. J. Radiol. 2016; 85 (10): 1893–9. DOI: 10.1016/j.ejrad.2016.07.017
  56. Delgado C., Vázquez M., Oca R., Vilar M., Trinidad C., Sanmartin M. Myocardial ischemia evaluation with dual-source computed tomography: comparison with magnetic resonance imaging. Rev. Esp. Cardiol. 2013; 66 (11): 864–70. DOI: 10.1016/j.rec.2013.05.026
  57. Zhao R.P., Hao Z.R., Song Z.J. Diagnostic value of Flash dual-source CT coronary artery imaging combined with dual-energy myocardial perfusion imaging for coronary heart disease. Exp. Ther. Med. 2014; 7 (4): 865–8. DOI: 10.3892/etm.2014.1541
  58. De Cecco C.N., Harris B.S., Schoepf U.J., Silverman J.R., McWhite C.B., Krazinski A.W. et al. Incremental value of pharmacological stress cardiac dual-energy CT over coronary CT angiography alone for the assessment of coronary artery disease in a high-risk population. Am. J. Roentgenol. 2014; 203 (1): 70–7. DOI: 10.2214/AJR.13.11772
  59. Pontone G., Baggiano A., Andreini D., Guaricci A.I., Guglielmo M., Muscogiuri G. et al. Stress computed tomography perfusion versus fractional flow reserve CT derived in suspected coronary artery disease: the PERFECTION study. JACC. Cardiovasc. Imaging. 2019; 128 (1): 1487–97. DOI: 10.1016/j.jcmg.2018.08.023
  60. Ihdayhid A.R., Sakaguchi T., Linde J.J., S_rgaard M.H., Kofoed K.F., Fujisawa Y. et al. Performance of computed tomography-derived fractional flow reserve using reduced-order modelling and static computed tomography stress myocardial perfusion imaging for detection of haemodynamically significant coronary stenosis. Eur. Heart J. Cardiovasc. Imaging. 2018; 19 (11): 1234–43. DOI: 10.1093/ehjci/jey114

About Authors

  • Kiriena M. Boldyreva, Junior Researcher, Postgraduate; ORCID
  • Vladimir N. Makarenko, Dr. Med. Sci., Professor, Chief Researcher; ORCID
  • Irina V. Shurupova, Dr. Med. Sci., Senior Researcher; ORCID
  • Inna E. Rychina, Cand. Med. Sci., Senior Researcher, Head of Department; ORCID
  • Aleksey V. Dorofeev, Cand. Med. Sci., Head of Department; ORCID
  • Irakliy P. Aslanidis, Dr. Med. Sci., Professor, Deputy Director, Head of Department; ORCID

Chief Editor

Leo A. Bockeria, MD, PhD, DSc, Professor, Academician of Russian Academy of Sciences, President of Bakoulev National Medical Research Center for Cardiovascular Surgery


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