Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
권호 표지
DOI QR코드

DOI QR Code

Dynamic CT Myocardial Perfusion Imaging in Patients without Obstructive Coronary Artery Disease: Quantification of Myocardial Blood Flow according to Varied Heart Rate Increments after Stress

  • Lihua Yu (Institute of Diagnostic and Interventional Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital) ;
  • Xiaofeng Tao (Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine) ;
  • Xu Dai (Institute of Diagnostic and Interventional Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital) ;
  • Ting Liu (Department of Radiology, First Affiliated Hospital of China Medical University) ;
  • Jiayin Zhang (Institute of Diagnostic and Interventional Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital)
  • Received : 2019.12.13
  • Accepted : 2020.05.09
  • Published : 2021.01.01
Download PDF
⟨ Previous Next ⟩

Abstract

Objective: The present study aimed to investigate the association between myocardial blood flow (MBF) quantified by dynamic CT myocardial perfusion imaging (CT-MPI) and the increments in heart rate (HR) after stress in patients without obstructive coronary artery disease. Materials and Methods: We retrospectively included 204 subjects who underwent both dynamic CT-MPI and coronary CT angiography (CCTA). Patients with more than minimal coronary stenosis (diameter ≥ 25%), history of myocardial infarction/revascularization, cardiomyopathy, and microvascular dysfunction were excluded. Global MBF at stress was measured using hybrid deconvolution and maximum slope model. Furthermore, the HR increments after stress were recorded. Results: The median radiation dose of dynamic CT-MPI plus CCTA was 5.5 (4.5-6.8) mSv. The median global MBF of all subjects was 156.4 (139.8-180.4) mL/100 mL/min. In subjects with HR increment between 10 to 19 beats per minute (bpm), the global MBF was significantly lower than that of subjects with increment between 20 to 29 bpm (153.3 mL/100 mL/min vs. 171.3 mL/100 mL/min, p = 0.027). This difference became insignificant when the HR increment further increased to ≥ 30 bpm. Conclusion: The global MBF value was associated with the extent of increase in HR after stress. Significantly higher global MBF was seen in subjects with HR increment of ≥ 20 bpm.

Keywords

Acknowledgement

This study is supported by National Natural Science Foundation of China (Grant No.: 81671678, 81871435), Medical Guidance Scientific Research Support Project of Shanghai Science and Technology Commission (Grant No.: 19411965100), Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (Grant No.: 20161428) and Innovative research team of high-level local universities in Shanghai.

References

  1. Bamberg F, Becker A, Schwarz F, Marcus RP, 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;260:689-698  https://doi.org/10.1148/radiol.11110638
  2. Bamberg F, Marcus RP, 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;7:267-277  https://doi.org/10.1016/j.jcmg.2013.06.008
  3. Coenen A, Rossi A, Lubbers MM, Kurata A, Kono AK, Chelu RG, et al. Integrating CT myocardial perfusion and CT-FFR in the work-up of coronary artery disease. JACC Cardiovasc Imaging 2017;10:760-770  https://doi.org/10.1016/j.jcmg.2016.09.028
  4. Li Y, Yu M, Dai X, Lu Z, Shen C, Wang Y, et al. Detection of hemodynamically significant coronary stenosis: CT myocardial perfusion versus machine learning CT fractional flow reserve. Radiology 2019;293:305-314  https://doi.org/10.1148/radiol.2019190098
  5. Yu M, Chen X, Dai X, Pan J, Wang Y, Lu B, et al. The value of low-dose dynamic myocardial perfusion CT for accurate evaluation of microvascular obstruction in patients with acute myocardial infarction. AJR Am J Roentgenol 2019;213:798-806  https://doi.org/10.2214/AJR.19.21305
  6. Dai X, Yu M, Pan J, Lu Z, Shen C, Wanget Y, al. Image quality and diagnostic accuracy of coronary CT angiography derived from low-dose dynamic CT myocardial perfusion: a feasibility study with comparison to invasive coronary angiography. Eur Radiol 2019;29:4349-4356  https://doi.org/10.1007/s00330-018-5777-4
  7. Pan J, Yuan M, Yu M, Gao Y, Shen C, Wanget Y, al. Myocardial blood flow quantified by low-dose dynamic CT myocardial perfusion imaging is associated with peak troponin level and impaired left ventricle function in patients with ST-elevated myocardial infarction. Korean J Radiol 2019;20:709-718  https://doi.org/10.3348/kjr.2018.0729
  8. Li Y, Yuan M, Yu M, Lu Z, Shen C, Wang Y, et al. Prevalence of decreased myocardial blood flow in symptomatic patients with patent coronary stents: insights from low-dose dynamic CT myocardial perfusion imaging. Korean J Radiol 2019;20:621-630  https://doi.org/10.3348/kjr.2018.0399
  9. Kono AK, Coenen A, Lubbers M, Kurata A, Rossi A, Dharampal A, 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;49:801-807  https://doi.org/10.1097/RLI.0000000000000087
  10. Karamitsos TD, Ntusi NA, Francis JM, Holloway CJ, Myerson SG, Neubauer S. Feasibility and safety of high-dose adenosine perfusion cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2010;12:66 
  11. Bamberg F, Klotz E, Flohr T, Becker A, Becker CR, Schmidt B, et al. Dynamic myocardial stress perfusion imaging using fast dual-source CT with alternating table positions: initial experience. Eur Radiol 2010;20:1168-1173  https://doi.org/10.1007/s00330-010-1715-9
  12. Rossi A, Merkus D, Klotz E, Mollet N, de Feyter PJ, Krestin GP. Stress myocardial perfusion: imaging with multidetector CT. Radiology 2014;270:25-46  https://doi.org/10.1148/radiol.13112739
  13. Fujita M, Kitagawa K, Ito T, Shiraishi Y, Kurobe Y, Nagata M, et al. Dose reduction in dynamic CT stress myocardial perfusion imaging: comparison of 80-kV/370-mAs and 100-kV/300-mAs protocols. Eur Radiol 2014;24:748-755  https://doi.org/10.1007/s00330-013-3063-z
  14. Cerqueira MD, Weissman NJ, Dilsizian V, Jacobs AK, Kaul S, Laskey WK, et al. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. Circulation 2002;105:539-542  https://doi.org/10.1161/hc0402.102975
  15. Meinel FG, Wichmann JL, Schoepf UJ, Pugliese F, Ebersberger U, Lo GG, et al. Global quantification of left ventricular myocardial perfusion at dynamic CT imaging: prognostic value. J Cardiovasc Comput Tomogr 2017;11:16-24  https://doi.org/10.1016/j.jcct.2016.12.003
  16. Tan SK, Yeong CH, Ng KH, Abdul Aziz YF, Sun Z. Recent update on radiation dose assessment for the state-of-the-art coronary computed tomography angiography protocols. PLoS One 2016;11:e0161543 
  17. Rossi A, Wragg A, Klotz E, Pirro F, Moon JC, Nieman K, 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:e005505 
  18. Rossi A, Dharampal A, Wragg A, Davies LC, van Geuns RJ, Anagnostopoulos C, et al. Diagnostic performance of hyperaemic myocardial blood flow index obtained by dynamic computed tomography: does it predict functionally significant coronary lesions? Eur Heart J Cardiovasc Imaging 2014;15:85-94  https://doi.org/10.1093/ehjci/jet133
  19. Greif M, von Ziegler F, Bamberg F, Tittus J, Schwarz F, D'Anastasi M, et al. CT stress perfusion imaging for detection of haemodynamically relevant coronary stenosis as defined by FFR. Heart 2013;99:1004-1011  https://doi.org/10.1136/heartjnl-2013-303794
  20. Ho KT, Ong HY, Tan G, Yong QW. Dynamic CT myocardial perfusion measurements of resting and hyperaemic blood flow in low-risk subjects with 128-slice dual-source CT. Eur Heart J Cardiovasc Imaging 2015;16:300-306  https://doi.org/10.1093/ehjci/jeu200
  21. Kim EY, Chung WJ, Sung YM, Byun SS, Park JH, Kim JH, et al. Normal range and regional heterogeneity of myocardial perfusion in healthy human myocardium: assessment on dynamic perfusion CT using 128-slice dual-source CT. Int J Cardiovasc Imaging 2014;30 Suppl 1:33-40  https://doi.org/10.1007/s10554-014-0432-x
  22. van Assen M, Pelgrim GJ, De Cecco CN, Stijnen JMA, Zaki BM, Oudkerk M, et al. Intermodel disagreement of myocardial blood flow estimation from dynamic CT perfusion imaging. Eur J Radiol 2019;110:175-180  https://doi.org/10.1016/j.ejrad.2018.11.029
  23. Murthy VL, Bateman TM, Beanlands RS, Berman DS, Borges-Neto S, Chareonthaitawee P, et al. Clinical quantification of myocardial blood flow using PET: joint position paper of the SNMMI Cardiovascular Council and the ASNC. J Nucl Med 2018;59:273-293  https://doi.org/10.2967/jnumed.117.201368
  24. Pontone G, Baggiano A, Andreini D, Guaricci AI, 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;12(8 pt 1):1487-1497 https://doi.org/10.1016/j.jcmg.2018.08.023