Vol 80, No 2 (2022)
Original article
Published online: 2022-01-18

open access

Page views 5469
Article views/downloads 697
Get Citation

Connect on Social Media

Connect on Social Media

Incremental value of volumetric quantification for myocardial perfusion imaging by computed tomography

Anna Oleksiak1, Cezary Kępka2, Koen Nieman3, Mariusz Dębski2, Marcin Demkow2, Mariusz Kruk2
Pubmed: 35040484
Kardiol Pol 2022;80(2):163-171.

Abstract

Background: The extent of myocardial ischemia is the crucial prognostic factor for interventional treatment decision making for coronary artery disease. The ability of computed tomography perfusion (CTP) to provide the missing volumetric information and its clinical value remains unknown. Aims: The study aimed to compare a novel ischemic volume quantification method based on dynamic computed tomography perfusion (VOL CTP) with other CT-based imaging modalities for revascularization prediction. Methods: In this prospective study, 53 (25 females, 63.5 [8.5] years old) consecutive symptomatic patients with 50%–90% coronary artery stenosis (n ≥1) on coronary computed tomography angiography underwent computed-tomography-derived fractional flow reserve (CT-FFR) analysis and dynamic CTP. We calculated the percentage of myocardial ischemia on the CTP-derived images. A 10% cut-off was used to define functionally significant ischemia. The outcomes include coronary revas-cularization during the follow-up of 2.5 (interquartile range, 1.4–2.8) years. Physicians were blinded to the results of CTP and CT-FFR. Results: Of the 53 patients in the study (68 arteries with 50%–90% stenosis), 16 underwent revascularization (12 elective, 4 event-driven). In the CTP quantitative analysis, 26 patients had ischemia. Overall, 18 patients had ischemia ≥10% on volumetric ischemia quantification based on dynamic computed tomography perfusion (VOL CTP), and 28 patients had CT-FFR < 0.8. VOL CTP, standard CTP, CT-FFR, and computed tomography coronary angiography (CTA) ≥70% performed well for the prediction of total revascularization. Area under the curve was 0.973 vs. 0.865, vs. 0.793, vs. 0.668, respectively. The VOL CTP with ≥10% cut-off was superior to the CT-FFR, standard CTP, and CTA ≥70% (P < 0.001; P = 0.002 and P < 0.001 respectively). Conclusions: VOL CTP quantification is feasible and adds important, actionable information to that provided by standard CTP or CT-FFR in patients with 50%–90% coronary artery stenosis.

References

  1. Knuuti J, Wijns W, Saraste A, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2020; 41(3): 407–477.
  2. Danad I, Szymonifka J, Twisk JWR, et al. Diagnostic performance of cardiac imaging methods to diagnose ischaemia-causing coronary artery disease when directly compared with fractional flow reserve as a reference standard: a meta-analysis. Eur Heart J. 2017; 38(13): 991–998.
  3. Seitun S, Clemente A, De Lorenzi C, et al. Cardiac CT perfusion and FFR: pathophysiological features in ischemic heart disease. Cardiovasc Diagn Ther. 2020; 10(6): 1954–1978.
  4. Yang DH, Kim YH, Roh JH, et al. Diagnostic performance of on-site CT-derived fractional flow reserve versus CT perfusion. Eur Heart J Cardiovasc Imaging. 2017; 18(4): 432–440.
  5. Coenen A, Rossi A, Lubbers MM, et al. Integrating CT myocardial perfusion and CT-FFR in the work-up of coronary artery disease. JACC Cardiovasc Imaging. 2017; 10(7): 760–770.
  6. Neumann FJ, Sousa-Uva M, Ahlsson A, et al. 2018 ESC/EACTS Guidelines on myocardial revascularization. EuroIntervention. 2019; 14(14): 1435–1534.
  7. Tanabe Y, Kido T, Kurata A, et al. Combined assessment of subtended myocardial volume and myocardial blood flow for diagnosis of obstructive coronary artery disease using cardiac computed tomography: A feasibility study. J Cardiol. 2020; 76(3): 259–265.
  8. Oleksiak A, Kruk M, Pugliese F, et al. Regadenoson dynamic computed tomography myocardial perfusion using low-dose protocol for evaluation of the ischemic burden. ULYSSES study. J Cardiovasc Comput Tomogr. 2020; 14(5): 428–436.
  9. Thygesen K, Alpert J, Jaffe A, et al. Fourth universal definition of myocardial infarction (2018). Circulation. 2018; 138(20).
  10. Raff GL, Abidov A, Achenbach S, et al. SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography. J Cardiovasc Comput Tomogr. 2009; 3(2): 122–136.
  11. Renker M, Schoepf UJ, Wang R, et al. Comparison of diagnostic value of a novel noninvasive coronary computed tomography angiography method versus standard coronary angiography for assessing fractional flow reserve. Am J Cardiol. 2014; 114(9): 1303–1308.
  12. Kruk M, Wardziak Ł, Demkow M, et al. Workstation-Based calculation of CTA-based FFR for intermediate stenosis. JACC Cardiovasc Imaging. 2016; 9(6): 690–699.
  13. Solecki M, Kruk M, Demkow M, et al. What is the optimal anatomic location for coronary artery pressure measurement at CT-derived FFR? J Cardiovasc Comput Tomogr. 2017; 11(5): 397–403.
  14. Kruk M, Demkow M, Solecki M, et al. The location of distal coronary artery pressure measurement matters for computed tomography-derived fractional flow reserve. JACC Cardiovasc Imaging. 2018; 11(2 Pt 1): 284–285.
  15. Oleksiak A, Kruk M, Śpiewak M, et al. Safety of regadenoson with theophylline reversal during dynamic computed tomography perfusion and magnetic resonance imaging in patients with coronary artery disease. Kardiol Pol. 2020; 78(7-8): 709–714.
  16. Oleksiak A, Sobieszczańska-Małek M, Kruk M, et al. Feasibility of computed tomography perfusion for detection of cardiac allograft rejection following heart transplantation. JACC Cardiovasc Imaging. 2020; 13(5): 1286–1289.
  17. Kwon O, Hwang HJ, Koo HJ, et al. Ischemic burden assessment of myocardial perfusion CT, compared with SPECT using semi-quantitative and quantitative approaches. Int J Cardiol. 2019; 278: 287–294.
  18. Kono AK, Coenen A, Lubbers M, et al. Relative myocardial blood flow by dynamic computed tomographic perfusion imaging predicts hemodynamic significance of coronary stenosis better than absolute blood flow. Invest Radiol. 2014; 49(12): 801–807.
  19. Rossi A, Wragg A, Klotz E, et al. Dynamic Computed Tomography Myocardial Perfusion Imaging: Comparison of Clinical Analysis Methods for the Detection of Vessel-Specific Ischemia. Circ Cardiovasc Imaging. 2017; 10(4).
  20. Pontone G, Andreini D, Guaricci AI, et al. Incremental diagnostic value of stress computed tomography myocardial perfusion with whole-heart coverage CT scanner in intermediate- to high-risk symptomatic patients suspected of coronary artery disease. JACC Cardiovasc Imaging. 2019; 12(2): 338–349.
  21. Nakamura S, Kitagawa K, Goto Y, et al. Incremental prognostic value of myocardial blood flow quantified with stress dynamic computed tomography perfusion imaging. JACC Cardiovasc Imaging. 2019; 12(7 Pt 2): 1379–1387.
  22. Nakamura S, Kitagawa K, Goto Y, et al. Prognostic value of stress dynamic computed tomography perfusion with computed tomography delayed enhancement. JACC Cardiovasc Imaging. 2020; 13(8): 1721–1734.
  23. Meinel FG, Pugliese F, Schoepf UJ, et al. Prognostic value of stress dynamic myocardial perfusion CT in a multicenter population with known or suspected coronary artery disease. AJR Am J Roentgenol. 2017; 208(4): 761–769.
  24. Meinel FG, Wichmann JL, Schoepf UJ, et al. Global quantification of left ventricular myocardial perfusion at dynamic CT imaging: Prognostic value. J Cardiovasc Comput Tomogr. 2017; 11(1): 16–24.
  25. van Assen M, De Cecco CN, Eid M, et al. Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease. J Cardiovasc Comput Tomogr. 2019; 13(3): 26–33.
  26. Pontone G, Guaricci AI, Palmer SC, et al. Diagnostic performance of non-invasive imaging for stable coronary artery disease: A meta-analysis. Int J Cardiol. 2020; 300: 276–281.
  27. Pontone G, Baggiano A, Andreini D, 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): 2460–2471.
  28. Baggiano A, Fusini L, Del Torto A, et al. Sequential Strategy Including FFR Plus Stress-CTP Impacts on Management of Patients with Stable Chest Pain: The Stress-CTP RIPCORD Study. J Clin Med. 2020; 9(7).
  29. Driessen RS, Danad I, Stuijfzand WJ, et al. Comparison of coronary computed tomography angiography, fractional flow reserve, and perfusion imaging for ischemia diagnosis. J Am Coll Cardiol. 2019; 73(2): 161–173.



Polish Heart Journal (Kardiologia Polska)