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Current and Future Post-Processing and Reconstruction Methods for Improved Image Quality in Coronary Computed Tomographic Angiography

  • Cardiac Computed Tomography (TC Villines and S Achenbach, Section Editors)
  • Published:
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Abstract

While coronary computed tomographic angiography (CCTA) has high diagnostic performance to identify and exclude obstructive coronary artery disease, it is susceptible to false-positive results and non-interpretable studies, and requires the use of ionizing radiation. New methods of image reconstruction and post-processing have the potential to significantly improve image quality, reduce the number of non-interpretable studies, and improve the diagnostic accuracy of CCTA. In this manuscript, we will review current and novel technologies for image reconstruction and post-processing that may improve the image quality of CCTA.

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References

Papers of particular interest, published recently, have been highlighted as: •• Of major importance

  1. Budoff MJ, Dowe D, Jollis JG, Gitter M, Sutherland J, Halamert E, et al. Diagnostic performance of 64-multidetector row coronary computed tomographic angiography for evaluation of coronary artery stenosis in individuals without known coronary artery disease: results from the prospective multicenter accuracy (assessment by coronary computed tomographic angiography of individuals undergoing invasive coronary angiography) trial. J Am Coll Cardiol. 2008;52:1724–32.

    Article  PubMed  Google Scholar 

  2. Miller JM, Rochitte CE, Dewey M, Arbab-Zadeh A, Niinuma H, Gottlieb I, et al. Diagnostic performance of coronary angiography by 64-row CT. N Engl J Med. 2008;359:2324–36.

    Article  PubMed  CAS  Google Scholar 

  3. Meijboom WB, Meijs MF, Schuijf JD, Cramer MJ, Mollet NR, van Mieghem CA, et al. Diagnostic accuracy of 64-slice computed tomography coronary angiography: a prospective, multicenter, multivendor study. J Am Coll Cardiol. 2008;52:2135–44.

    Article  PubMed  Google Scholar 

  4. Redberg RF. Computed tomographic angiography: more than just a pretty picture? J Am Coll Cardiol. 2007;49:1827–9.

    Article  PubMed  Google Scholar 

  5. Raff GL, Abidov A, Achenbach S, Berman DS, Boxt LM, Budoff MJ, et al. SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography. J Cardiovasc Comput Tomogr. 2009;3:122–36.

    Article  PubMed  Google Scholar 

  6. Einstein AJ. Radiation protection of patients undergoing cardiac computed tomographic angiography. JAMA. 2009;301:545–7.

    Article  PubMed  CAS  Google Scholar 

  7. Raff GL, Chinnaiyan KM, Share DA, Goraya TY, Kazerooni EA, Moscucci M, et al. Radiation dose from cardiac computed tomography before and after implementation of radiation dose-reduction techniques. JAMA. 2009;301:2340–8.

    Article  PubMed  CAS  Google Scholar 

  8. Hausleiter J, Meyer T, Hadamitzky M, Huber E, Zankl M, Martinoff S, et al. Radiation dose estimates from cardiac multislice computed tomography in daily practice: impact of different scanning protocols on effective dose estimates. Circulation. 2006;113:1305–10.

    Article  PubMed  Google Scholar 

  9. Hausleiter J, Meyer T, Hermann F, Hadamitzky M, Krebs M, Gerber TC, et al. Estimated radiation dose associated with cardiac CT angiography. JAMA. 2009;301:500–7.

    Article  PubMed  CAS  Google Scholar 

  10. Nelson RC, Feuerlein S, Boll DT. New iterative reconstruction techniques for cardiovascular computed tomography: how do they work, and what are the advantages and disadvantages? J Cardiovasc Comput Tomogr. 2011;5:286–92.

    Article  PubMed  Google Scholar 

  11. Hudson HM, Larkin RS. Accelerated image reconstruction using ordered subsets of projection data. IEEE Trans Med Imaging. 1994;13:601–9.

    Article  PubMed  CAS  Google Scholar 

  12. •• Park EA, Lee W, Kim KW, Kim KG, Thomas A, Chung JW, et al. Iterative reconstruction of dual-source coronary ct angiography: assessment of image quality and radiation dose. Int J Cardiovasc Imaging. 2011; doi:10.1007/s10554-011-0004-2. This paper evaluated the effect of iterative reconstruction on image quality and radiation dose.

  13. •• Bittencourt MS, Schmidt B, Seltmann M, Muschiol G, Ropers D, Daniel WG, et al. Iterative reconstruction in image space (iris) in cardiac computed tomography: initial experience. Int J Cardiovasc Imaging. 2011;27:1081–7. This study examined the effect of iterative reconstruction on image quality and the number of interpretable segments.

    Article  PubMed  Google Scholar 

  14. •• Renker M, Nance Jr JW, 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;260:390–9. This study evaluated the effect of iterative reconstruction on image noise and calcium blooming artifact.

    Article  PubMed  Google Scholar 

  15. Min JK, Swaminathan RV, Vass M, Gallagher S, Weinsaft JW. High-definition multidetector computed tomography for evaluation of coronary artery stents: comparison to standard-definition 64-detector row computed tomography. J Cardiovasc Comput Tomogr. 2009;3:246–51.

    Article  PubMed  Google Scholar 

  16. •• Leipsic J, Labounty TM, Heilbron B, Min JK, Mancini GB, Lin FY, et al. Adaptive statistical iterative reconstruction: assessment of image noise and image quality in coronary ct angiography. AJR Am J Roentgenol. 2010;195:649–54. This manuscript evaluated the effect of iterative reconstruction on image noise, signal, and image quality.

    Article  PubMed  Google Scholar 

  17. Leipsic J, Labounty TM, Heilbron B, Min JK, Mancini GB, Lin FY, et al. Estimated radiation dose reduction using adaptive statistical iterative reconstruction in coronary CT angiography: the ERASIR study. AJR Am J Roentgenol. 2010;195:655–60.

    Article  PubMed  Google Scholar 

  18. Singh S, Kalra MK, Shenoy-Bhangle AS, Saini A, Gervais DA, Westra SJ, et al. Radiation dose reduction with hybrid iterative reconstruction for pediatric CT. Radiology. 2012;263:537–46.

    Article  PubMed  Google Scholar 

  19. Sato J, Akahane M, Inano S, Terasaki M, Akai H, Katsura M, et al. Effect of radiation dose and adaptive statistical iterative reconstruction on image quality of pulmonary computed tomography. Jpn J Radiol. 2012;30:146–53.

    Article  PubMed  Google Scholar 

  20. Rapalino O, Kamalian S, Payabvash S, Souza LC, Zhang D, Mukta J, et al. Cranial CT with adaptive statistical iterative reconstruction: improved image quality with concomitant radiation dose reduction. AJNR Am J Neuroradiol. 2012;33:609–15.

    Article  PubMed  CAS  Google Scholar 

  21. Noel PB, Fingerle AA, Renger B, Munzel D, Rummeny EJ, Dobritz M. Initial performance characterization of a clinical noise-suppressing reconstruction algorithm for MDCT. AJR Am J Roentgenol. 2011;197:1404–9.

    Article  PubMed  Google Scholar 

  22. Utsunomiya D, Weigold WG, Weissman G, Taylor AJ. Effect of hybrid iterative reconstruction technique on quantitative and qualitative image analysis at 256-slice prospective gating cardiac CT. Eur Radiol. 2011;22:1287–94

    Google Scholar 

  23. Moscariello A, Takx RA, Schoepf UJ, Renker M, Zwerner PL, O'Brien TX, et al. Coronary CT angiography: image quality, diagnostic accuracy, and potential for radiation dose reduction using a novel iterative image reconstruction technique-comparison with traditional filtered back projection. Eur Radiol. 2011;21:2130–8.

    Article  PubMed  Google Scholar 

  24. Gervaise A, Osemont B, Lecocq S, Noel A, Micard E, Felblinger J, et al. CT image quality improvement using adaptive iterative dose reduction with wide-volume acquisition on 320-detector CT. Eur Radiol. 2012;22:295–301.

    Article  PubMed  Google Scholar 

  25. Yu Z, Thibault JB, Bouman CA, Sauer KD, Hsieh J. Fast model-based X-ray CT reconstruction using spatially nonhomogeneous icd optimization. IEEE Trans Image Process. 2011;20:161–75.

    Article  PubMed  Google Scholar 

  26. Thibault JB, Sauer KD, Bouman CA, Hsieh J. A three-dimensional statistical approach to improved image quality for multislice helical CT. Med Phys. 2007;34:4526–44.

    Article  PubMed  Google Scholar 

  27. Scheffel H, Stolzmann P, Schlett CL, Engel LC, Major GP, Karolyi M, et al. Coronary artery plaques: cardiac CT with model-based and adaptive-statistical iterative reconstruction technique. Eur J Radiol. 2012;81:e363–9.

    Article  PubMed  Google Scholar 

  28. Suzuki S, Machida H, Tanaka I, Ueno E. Measurement of vascular wall attenuation: comparison of ct angiography using model-based iterative reconstruction with standard filtered back-projection algorithm CT in vitro. Eur J Radiol. 2012; doi:10.1016/j.ejrad.2012.02.009

  29. Cohen A, Yadava G, Sainath P, Fan J, Madhav P, Hsieh J. How much CT radiation dose can model based iterative reconstruction (Veo) save? A physical evaluation of the image quality using standard phantoms. Med Phys. 2011;38:3798.

    Article  Google Scholar 

  30. Do S, Karl WC, Liang Z, Kalra M, Brady TJ, Pien HH. A decomposition-based CT reconstruction formulation for reducing blooming artifacts. Phys Med Biol. 2011;56:7109–25.

    Article  PubMed  Google Scholar 

  31. LaBounty TM, Earls JP, Leipsic J, Heilbron B, Mancini GB, Lin FY, et al. Effect of a standardized quality-improvement protocol on radiation dose in coronary computed tomographic angiography. Am J Cardiol. 2010;106:1663–7.

    Article  PubMed  Google Scholar 

  32. Abbara S, Arbab-Zadeh A, Callister TQ, Desai MY, Mamuya W, Thomson L, et al. SCCT guidelines for performance of coronary computed tomographic angiography: a report of the society of cardiovascular computed tomography guidelines committee. J Cardiovasc Comput Tomogr. 2009;3:190–204.

    Article  PubMed  Google Scholar 

  33. Achenbach S, Manolopoulos M, Schuhback A, Ropers D, Rixe J, Schneider C, et al. Influence of heart rate and phase of the cardiac cycle on the occurrence of motion artifact in dual-source CT angiography of the coronary arteries. J Cardiovasc Comput Tomogr. 2012;6:91–8.

    Article  PubMed  Google Scholar 

  34. Isola AA, Grass M, Niessen WJ. Fully automatic nonrigid registration-based local motion estimation for motion-corrected iterative cardiac ct reconstruction. Med Phys. 2010;37:1093–109.

    Article  PubMed  Google Scholar 

  35. Isola AA, Ziegler A, Schafer D, Kohler T, Niessen WJ, Grass M. Motion compensated iterative reconstruction of a region of interest in cardiac cone-beam CT. Comput Med Imaging Graph. 2010;34:149–59.

    Article  PubMed  CAS  Google Scholar 

  36. Isola AA, Ziegler A, Koehler T, Niessen WJ, Grass M. Motion-compensated iterative cone-beam ct image reconstruction with adapted blobs as basis functions. Phys Med Biol. 2008;53:6777–97.

    Article  PubMed  CAS  Google Scholar 

  37. Isola AA, Metz CT, Schaap M, Klein S, Grass M, Niessen WJ. Cardiac motion-corrected iterative cone-beam ct reconstruction using a semi-automatic minimum cost path-based coronary centerline extraction. Comput Med Imaging Graph. 2012;36:215–26.

    Article  PubMed  CAS  Google Scholar 

  38. •• Leipsic J, Labounty T, Hague CJ, Mancini GBJ, O'brien JM, Wood DA, et al. Effect of a novel vendor-specific motion-correction algorithm on image quality and diagnostic accuracy in persons undergoing coronary CT angiography without rate-control medications. J Cardiovasc Comput Tomogr. 2012;[in press]. This paper examined the effect of a motion-correction algorithm on interpretability, image quality, and diagnostic accuracy of CCTA.

  39. Maintz D, Seifarth H, Raupach R, Flohr T, Rink M, Sommer T, et al. 64-slice multidetector coronary CT angiography: in vitro evaluation of 68 different stents. Eur Radiol. 2006;16:818–26.

    Article  PubMed  Google Scholar 

  40. Rodriguez-Granillo GA, Rosales MA, Degrossi E, Rodriguez AE. Signal density of left ventricular myocardial segments and impact of beam hardening artifact: Implications for myocardial perfusion assessment by multidetector CT coronary angiography. Int J Cardiovasc Imaging. 2010;26:345–54.

    Article  PubMed  Google Scholar 

  41. Kitagawa K, George RT, Arbab-Zadeh A, Lima JA, Lardo AC. Characterization and correction of beam-hardening artifacts during dynamic volume ct assessment of myocardial perfusion. Radiology. 2010;256:111–8.

    Article  PubMed  Google Scholar 

  42. Karlsberg DW, Elad Y, Kass RM, Karlsberg RP. Quadricuspid aortic valve defined by echocardiography and cardiac computed tomography. Clin Med Insights Cardiol. 2012;6:41–4.

    Article  PubMed  Google Scholar 

  43. Meyer E, Raupach R, Lell M, Schmidt B, Kachelriess M. Frequency split metal artifact reduction (FSMAR) in computed tomography. Med Phys. 2012;39:1904–16.

    Article  PubMed  Google Scholar 

  44. Habets J, Symersky P, Leiner T, de Mol BA, Mali WP, Budde RP. Artifact reduction strategies for prosthetic heart valve CT imaging. Int J Cardiovasc Imaging. 2012; doi:10.1007/s10554-012-0041-5.

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Authors and Affiliations

  1. Cedars-Sinai Heart Institute and Department of Imaging, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Mark Taper Suite 1258, Los Angeles, CA, 90048, USA

    Ryo Nakazato

  2. Departments of Imaging, Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building Room A238, Los Angeles, CA, 90048, USA

    Damini Dey

  3. Department of Medicine, Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, 147 Robertson Boulevard #203, Los Angeles, CA, 90048, USA

    Troy M. LaBounty

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  1. Ryo Nakazato
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Correspondence to Troy M. LaBounty.

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Nakazato, R., Dey, D. & LaBounty, T.M. Current and Future Post-Processing and Reconstruction Methods for Improved Image Quality in Coronary Computed Tomographic Angiography. Curr Cardiovasc Imaging Rep 5, 360–366 (2012). https://doi.org/10.1007/s12410-012-9151-7

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