Diagnostic performance and image quality of iterative model-based reconstruction of coronary CT angiography using 100 kVp for heavily calcified coronary vessels

English version

Autoři: Junwoo Kim ^aff001; Bon Seung Goo ^aff001; Young-Seok Cho ^aff002; Tae-Jin Youn ^aff002; Dong Jun Choi ^aff001; Amar Dhanantwari ^aff003; Mani Vembar ^aff003; Eun Ju Chun ^aff001
Působiště autorů: Department of Radiology, Seoul National University Bundang Hospital, Sungnam, Korea ^aff001; Department of Internal Medicine, Seoul National University Bundang Hospital, Sungnam, Korea ^aff002; CT/AMI Clinical Science, Philips Healthcare, Highland Heights, OH, United States of America ^aff003
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0222315

Souhrn

Objectives

To evaluate the diagnostic performance and image quality of an iterative model-based reconstruction (IMR) using a 100-kVp protocol for the assessment of heavily calcified coronary vessels, compared to those of filtered back projection (FBP) and hybrid iterative technique (iDose⁴), and also compared to those of IMR with standard 120 kVp protocol.

Methods

Among patients with Agatston scores ≥ 400 who had undergone both coronary CT angiography (CCTA) and invasive coronary angiography (ICA), age- and sex-matched patients with body mass index < 30 were retrospectively enrolled from CCTA with low-kVp protocol (100 kVp, n = 30) and with standard-kVp protocol (120 kVp, n = 30). Image data were all reconstructed with FBP, iDose⁴, and IMR. In each dataset, the objective and subjective image quality, and diagnostic accuracy (> 50% in luminal reduction as compared with ICA) were assessed.

Results

IMR showed better objective and subjective image quality than FBP and iDose⁴ in both 100 kVp and 120 kVp groups (all p < 0.05). IMR showed a significantly improved all diagnostic performance compared with FBP (p < 0.05). Compared with iDose⁴, IMR significantly improved positive predictive value (85.0% vs. 80.5%; p < 0.05). There was no significant difference in image quality and diagnostic performance using IMR between the 100 kVp and 120 kVp groups.

Conclusions

100 kVp IMR may be useful for the assessment of heavily calcified coronary vessels, providing better diagnostic performance than FBP or iDose⁴ at the same dose, while maintaining similar diagnostic accuracy to 120 kVp IMR.

Klíčová slova:

Biology and life sciences – Research and analysis methods – Neuroscience – Anatomy – Medicine and health sciences – Pathology and laboratory medicine – Diagnostic medicine – Signs and symptoms – Vascular medicine – Imaging techniques – Cardiology – Neuroimaging – Diagnostic radiology – Radiology and imaging – Pulmonary imaging – Tomography – Computed axial tomography – Cardiovascular anatomy – Coronary heart disease – Stenosis – Blood vessels – Arteries – Coronary arteries – Aorta

Zdroje

1. Abdulla J, Abildstrom SZ, Gotzsche O, Christensen E, Kober L, Torp-Pedersen C. 64-multislice detector computed tomography coronary angiography as potential alternative to conventional coronary angiography: a systematic review and meta-analysis. Eur Heart J. 2007;28(24):3042–50. Epub 2007/11/06. doi: 10.1093/eurheartj/ehm466 17981829.

2. Vanhoenacker PK, Heijenbrok-Kal MH, Van Heste R, Decramer I, Van Hoe LR, Wijns W, et al. Diagnostic Performance of Multidetector CT Angiography for Assessment of Coronary Artery Disease: Meta-analysis 1. Radiology. 2007;244(2):419–28. doi: 10.1148/radiol.2442061218 17641365

3. Meijs MF, Meijboom WB, Prokop M, Mollet NR, van Mieghem CA, Doevendans PA, et al. Is there a role for CT coronary angiography in patients with symptomatic angina? Effect of coronary calcium score on identification of stenosis. The international journal of cardiovascular imaging. 2009;25(8):847–54. doi: 10.1007/s10554-009-9485-7 19649721

4. Kalisz K, Buethe J, Saboo SS, Abbara S, Halliburton S, Rajiah P. Artifacts at Cardiac CT: Physics and Solutions. Radiographics. 2016;36(7):2064–83. Epub 2016/10/22. doi: 10.1148/rg.2016160079 27768543.

5. Raff GL, Gallagher MJ, O'Neill WW, Goldstein JA. Diagnostic accuracy of noninvasive coronary angiography using 64-slice spiral computed tomography. Journal of the American College of Cardiology. 2005;46(3):552–7. Epub 2005/08/02. doi: 10.1016/j.jacc.2005.05.056 16053973.

6. Hecht HS, Bhatti T. How much calcium is too much calcium for coronary computerized tomographic angiography? J Cardiovasc Comput Tomogr. 2008;2(3):183–7. Epub 2008/12/17. doi: 10.1016/j.jcct.2008.04.003 19083944.

7. Hou Y, Liu X, Xv S, Guo W, Guo Q. Comparisons of image quality and radiation dose between iterative reconstruction and filtered back projection reconstruction algorithms in 256-MDCT coronary angiography. American journal of roentgenology. 2012;199(3):588–94. doi: 10.2214/AJR.11.7557 22915398

8. Leipsic J, LaBounty TM, Heilbron B, Min JK, Mancini GJ, Lin FY, et al. Adaptive statistical iterative reconstruction: assessment of image noise and image quality in coronary CT angiography. American Journal of Roentgenology. 2010;195(3):649–54. doi: 10.2214/AJR.10.4285 20729442

9. Renker M, Nance JW Jr, Schoepf UJ, O’Brien TX, Zwerner PL, Meyer M, et al. Evaluation of heavily calcified vessels with coronary CT angiography: comparison of iterative and filtered back projection image reconstruction. Radiology. 2011;260(2):390–9. doi: 10.1148/radiol.11103574 21693660

10. Willemink MJ, de Jong PA, Leiner T, de Heer LM, Nievelstein RA, Budde RP, et al. Iterative reconstruction techniques for computed tomography Part 1: technical principles. European radiology. 2013;23(6):1623–31. doi: 10.1007/s00330-012-2765-y 23314600.

11. Boudabbous S, Arditi D, Paulin E, Syrogiannopoulou A, Becker C, Montet X. Model-Based Iterative Reconstruction (MBIR) for the Reduction of Metal Artifacts on CT. AJR Am J Roentgenol. 2015;205(2):380–5. Epub 2015/07/24. doi: 10.2214/AJR.14.13334 26204291.

12. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. Journal of the American College of Cardiology. 1990;15(4):827–32. doi: 10.1016/0735-1097(90)90282-t 2407762

13. Chun EJ, Lee W, Choi YH, Koo BK, Choi SI, Jae HJ, et al. Effects of nitroglycerin on the diagnostic accuracy of electrocardiogram-gated coronary computed tomography angiography. J Comput Assist Tomogr. 2008;32(1):86–92. Epub 2008/02/28. doi: 10.1097/rct.0b013e318059befa 18303294.

14. Austen WG, Edwards J, Frye R, Gensini G, Gott V, Griffith L, et al. A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular Surgery, American Heart Association. Circulation. 1975;51(4):5–40.

15. Oda S, Weissman G, Vembar M, Weigold WG. Iterative model reconstruction: improved image quality of low-tube-voltage prospective ECG-gated coronary CT angiography images at 256-slice CT. Eur J Radiol. 2014;83(8):1408–15. Epub 2014/05/31. doi: 10.1016/j.ejrad.2014.04.027 24873832.

16. Yuki H, Utsunomiya D, Funama Y, Tokuyasu S, Namimoto T, Hirai T, et al. Value of knowledge-based iterative model reconstruction in low-kV 256-slice coronary CT angiography. Journal of cardiovascular computed tomography. 2014;8(2):115–23. doi: 10.1016/j.jcct.2013.12.010 24661824

17. Stein PD, Beemath A, Kayali F, Skaf E, Sanchez J, Olson RE. Multidetector computed tomography for the diagnosis of coronary artery disease: a systematic review. Am J Med. 2006;119(3):203–16. Epub 2006/02/24. doi: 10.1016/j.amjmed.2005.06.071 16490463.

18. Kruk M, Noll D, Achenbach S, Mintz GS, Pregowski J, Kaczmarska E, et al. Impact of coronary artery calcium characteristics on accuracy of CT angiography. JACC Cardiovasc Imaging. 2014;7(1):49–58. Epub 2013/12/03. doi: 10.1016/j.jcmg.2013.07.013 24290567.

19. Yu L, Leng S, McCollough CH. Dual-energy CT-based monochromatic imaging. AJR Am J Roentgenol. 2012;199(5 Suppl):S9–S15. Epub 2012/11/01. doi: 10.2214/AJR.12.9121 23097173.

20. Hara AK, Paden RG, Silva AC, Kujak JL, Lawder HJ, Pavlicek W. Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study. American Journal of Roentgenology. 2009;193(3):764–71. doi: 10.2214/AJR.09.2397 19696291

21. Thibault J-B, Sauer KD, Bouman CA, Hsieh J. A three-dimensional statistical approach to improved image quality for multislice helical CT. Medical physics. 2007;34(11):4526–44. doi: 10.1118/1.2789499 18072519

22. Karolyi M, Szilveszter B, Kolossvary M, Takx RA, Celeng C, Bartykowszki A, et al. Iterative model reconstruction reduces calcified plaque volume in coronary CT angiography. Eur J Radiol. 2017;87:83–9. Epub 2017/01/10. doi: 10.1016/j.ejrad.2016.12.012 28065380.