Dose Reduction of Dynamic Computed Tomography Myocardial Perfusion Imaging by Tube Voltage Change: Investigation in a Swine Model

Overview

Journal Front Cardiovasc Med

Specialty Cardiology & Vascular Diseases

Date 2022 Mar 21

PMID 35310988

Authors

Wenlei Geng

Yang Gao

Na Zhao

Hankun Yan

Wei Ma

Yunqiang An

Liujun Jia

Bin Lu

Affiliations

Soon will be listed here.

Abstract

Background: It is unclear whether tube voltage influences the measurement of perfusion parameters. The present study sought to evaluate the influence of tube voltage change on myocardial blood flow (MBF) measurements in dynamic computed tomography myocardial perfusion imaging (CTP).

Methods And Results: Seven swine [mean weight 55.8 kg ± 1.6 (standard deviation)] underwent rest and stress dynamic CTP with tube voltages of 100 and 70 kV. The image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), radiation dose and MBF value were compared. The 70 kV images had higher CT attenuation and higher image noise (27.9 ± 2.4 vs. 21.5 ± 1.9, < 0.001) than the 100 kV images, resulting in a higher SNR (20.5 ± 1.6 vs. 15.6 ± 1.8, < 0.001) and CNR (17.6 ± 1.5 vs. 12.4 ± 1.7, < 0.001). Compared to the use of conventional 100 kV, 70 kV yielded an approximately 64.6% radiation dose reduction while generating comparable MBF values, both at rest (88.3 ± 14.9 ml/100 g/min vs. 85.6 ± 17.4 ml/100 g/min, = 0.21) and stress (101.4 ± 21.5 ml/100 g/min vs. 99.6 ± 21.4 ml/100 g/min, = 0.58) states.

Conclusion: Dynamic CTP using 70 kV instead of 100 kV does not substantially influence the MBF value but significantly reduces the radiation dose. Additional research is required to investigate the clinical significance of this change.

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References

So A, Wisenberg G, Teefy P, Yadegari A, Bagur R, Hadway J . Functional CT assessment of extravascular contrast distribution volume and myocardial perfusion in acute myocardial infarction. Int J Cardiol. 2018; 266:15-23. DOI: 10.1016/j.ijcard.2018.02.101. View

Kalra M, Sodickson A, Mayo-Smith W . CT Radiation: Key Concepts for Gentle and Wise Use. Radiographics. 2015; 35(6):1706-21. DOI: 10.1148/rg.2015150118. View

Yang J, Dou G, He B, Jin Q, Chen Z, Jing J . Stress Myocardial Blood Flow Ratio by Dynamic CT Perfusion Identifies Hemodynamically Significant CAD. JACC Cardiovasc Imaging. 2019; 13(4):966-976. DOI: 10.1016/j.jcmg.2019.06.016. View

Kim S, Cho Y, Choe Y . Adenosine-stress dynamic myocardial perfusion imaging using 128-slice dual-source CT in patients with normal body mass indices: effect of tube voltage, tube current, and iodine concentration on image quality and radiation dose. Int J Cardiovasc Imaging. 2014; 30 Suppl 2:95-103. DOI: 10.1007/s10554-014-0524-7. View

Meijboom W, van Mieghem C, Van Pelt N, Weustink A, Pugliese F, Mollet N . Comprehensive assessment of coronary artery stenoses: computed tomography coronary angiography versus conventional coronary angiography and correlation with fractional flow reserve in patients with stable angina. J Am Coll Cardiol. 2008; 52(8):636-43. DOI: 10.1016/j.jacc.2008.05.024. View

Takafuji M, Kitagawa K, Ishida M, Goto Y, Nakamura S, Nagasawa N . Myocardial Coverage and Radiation Dose in Dynamic Myocardial Perfusion Imaging Using Third-Generation Dual-Source CT. Korean J Radiol. 2020; 21(1):58-67. PMC: 6960309. DOI: 10.3348/kjr.2019.0323. View

So A, Hsieh J, Li J, Hadway J, Kong H, Lee T . Quantitative myocardial perfusion measurement using CT perfusion: a validation study in a porcine model of reperfused acute myocardial infarction. Int J Cardiovasc Imaging. 2011; 28(5):1237-48. DOI: 10.1007/s10554-011-9927-x. View

Vanhoenacker P, Heijenbrok-Kal M, Van Heste R, Decramer I, Van Hoe L, Wijns W . Diagnostic performance of multidetector CT angiography for assessment of coronary artery disease: meta-analysis. Radiology. 2007; 244(2):419-28. DOI: 10.1148/radiol.2442061218. View

Rossi A, Uitterdijk A, Dijkshoorn M, Klotz E, Dharampal A, van Straten M . Quantification of myocardial blood flow by adenosine-stress CT perfusion imaging in pigs during various degrees of stenosis correlates well with coronary artery blood flow and fractional flow reserve. Eur Heart J Cardiovasc Imaging. 2012; 14(4):331-8. DOI: 10.1093/ehjci/jes150. View

10.

Lira D, Padole A, Kalra M, Singh S . Tube potential and CT radiation dose optimization. AJR Am J Roentgenol. 2014; 204(1):W4-10. DOI: 10.2214/AJR.14.13281. View

11.

Koonce J, Vliegenthart R, Schoepf U, Schmidt B, Wahlquist A, Nietert P . Accuracy of dual-energy computed tomography for the measurement of iodine concentration using cardiac CT protocols: validation in a phantom model. Eur Radiol. 2013; 24(2):512-8. PMC: 4126413. DOI: 10.1007/s00330-013-3040-6. View

12.

Gramer B, Muenzel D, Leber V, von Thaden A, Feussner H, Schneider A . Impact of iterative reconstruction on CNR and SNR in dynamic myocardial perfusion imaging in an animal model. Eur Radiol. 2012; 22(12):2654-61. DOI: 10.1007/s00330-012-2525-z. View

13.

Neumann F, Sousa-Uva M, Ahlsson A, Alfonso F, Banning A, Benedetto U . 2018 ESC/EACTS Guidelines on myocardial revascularization. EuroIntervention. 2019; 14(14):1435-1534. DOI: 10.4244/EIJY19M01_01. View

14.

Pontone G, Baggiano A, Andreini D, Guaricci A, Guglielmo M, Muscogiuri G . 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. DOI: 10.1016/j.jcmg.2019.02.015. View

15.

Fujita M, Kitagawa K, Ito T, Shiraishi Y, Kurobe Y, Nagata M . Dose reduction in dynamic CT stress myocardial perfusion imaging: comparison of 80-kV/370-mAs and 100-kV/300-mAs protocols. Eur Radiol. 2013; 24(3):748-55. DOI: 10.1007/s00330-013-3063-z. View

16.

Li Y, Dai X, Lu Z, Shen C, Zhang J . Diagnostic performance of quantitative, semi-quantitative, and visual analysis of dynamic CT myocardial perfusion imaging: a validation study with invasive fractional flow reserve. Eur Radiol. 2020; 31(1):525-534. DOI: 10.1007/s00330-020-07145-5. View

17.

Lu M, Wang S, Sirajuddin A, Arai A, Zhao S . Dynamic stress computed tomography myocardial perfusion for detecting myocardial ischemia: A systematic review and meta-analysis. Int J Cardiol. 2018; 258:325-331. DOI: 10.1016/j.ijcard.2018.01.095. View

18.

Skornitzke S, Hirsch J, Kauczor H, Stiller W . Evaluation of the effect of image noise on CT perfusion measurements using digital perfusion phantoms. Eur Radiol. 2018; 29(4):2089-2097. DOI: 10.1007/s00330-018-5709-3. View

19.

Pontone G, Guaricci A, Palmer S, Andreini D, Verdecchia M, Fusini L . Diagnostic performance of non-invasive imaging for stable coronary artery disease: A meta-analysis. Int J Cardiol. 2019; 300:276-281. DOI: 10.1016/j.ijcard.2019.10.046. View

20.

Li X, Ni Q, Schoepf U, Wichmann J, Felmly L, Qi L . 70-kVp High-pitch Computed Tomography Pulmonary Angiography with 40 mL Contrast Agent: Initial Experience. Acad Radiol. 2015; 22(12):1562-70. DOI: 10.1016/j.acra.2015.08.026. View