Korean Journal of Radiology

  • 제15권2호
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  • Pages.195-204
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  • 2014
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  • 1229-6929(pISSN)
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  • 2005-8330(eISSN)
대한영상의학회 (The Korean Society of Radiology)
권호 표지
DOI QR코드

DOI QR Code

Adaptive Iterative Dose Reduction Algorithm in CT: Effect on Image Quality Compared with Filtered Back Projection in Body Phantoms of Different Sizes

  • Kim, Milim (College of Medicine, Seoul National University) ;
  • Lee, Jeong Min (Department of Radiology, Seoul National University Hospital) ;
  • Yoon, Jeong Hee (Department of Radiology, Seoul National University Hospital) ;
  • Son, Hyoshin (College of Medicine, Seoul National University) ;
  • Choi, Jin Woo (Department of Radiology, Seoul National University Hospital) ;
  • Han, Joon Koo (Department of Radiology, Seoul National University Hospital) ;
  • Choi, Byung Ihn (Department of Radiology, Seoul National University Hospital)
  • 투고 : 2012.12.11
  • 심사 : 2014.01.14
  • 발행 : 2014.04.01
⟨ 이전 논문 다음 논문 ⟩

초록

Objective: To evaluate the impact of the adaptive iterative dose reduction (AIDR) three-dimensional (3D) algorithm in CT on noise reduction and the image quality compared to the filtered back projection (FBP) algorithm and to compare the effectiveness of AIDR 3D on noise reduction according to the body habitus using phantoms with different sizes. Materials and Methods: Three different-sized phantoms with diameters of 24 cm, 30 cm, and 40 cm were built up using the American College of Radiology CT accreditation phantom and layers of pork belly fat. Each phantom was scanned eight times using different mAs. Images were reconstructed using the FBP and three different strengths of the AIDR 3D. The image noise, the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) of the phantom were assessed. Two radiologists assessed the image quality of the 4 image sets in consensus. The effectiveness of AIDR 3D on noise reduction compared with FBP were also compared according to the phantom sizes. Results: Adaptive iterative dose reduction 3D significantly reduced the image noise compared with FBP and enhanced the SNR and CNR (p < 0.05) with improved image quality (p < 0.05). When a stronger reconstruction algorithm was used, greater increase of SNR and CNR as well as noise reduction was achieved (p < 0.05). The noise reduction effect of AIDR 3D was significantly greater in the 40-cm phantom than in the 24-cm or 30-cm phantoms (p < 0.05). Conclusion: The AIDR 3D algorithm is effective to reduce the image noise as well as to improve the image-quality parameters compared by FBP algorithm, and its effectiveness may increase as the phantom size increases.

키워드

과제정보

연구 과제 주관 기관 : Man Chung Han

참고문헌

  1. Brenner DJ, Hall EJ. Computed tomography--an increasing source of radiation exposure. N Engl J Med 2007;357:2277-2284 https://doi.org/10.1056/NEJMra072149
  2. Mahesh M. Medical radiation exposure with focus on CT. Rev Environ Health 2010;25:69-74
  3. Berrington de Gonzalez A, Mahesh M, Kim KP, Bhargavan M, Lewis R, Mettler F, et al. Projected cancer risks from computed tomographic scans performed in the United States in 2007. Arch Intern Med 2009;169:2071-2077 https://doi.org/10.1001/archinternmed.2009.440
  4. Smith-Bindman R, Lipson J, Marcus R, Kim KP, Mahesh M, Gould R, et al. Radiation dose associated with common computed tomography examinations and the associated lifetime attributable risk of cancer. Arch Intern Med 2009;169:2078-2086 https://doi.org/10.1001/archinternmed.2009.427
  5. Voress M. The increasing use of CT and its risks. Radiol Technol 2007;79:186-190
  6. Sagara Y, Hara AK, Pavlicek W, Silva AC, Paden RG, Wu Q. Abdominal CT: comparison of low-dose CT with adaptive statistical iterative reconstruction and routine-dose CT with filtered back projection in 53 patients. AJR Am J Roentgenol 2010;195:713-719 https://doi.org/10.2214/AJR.09.2989
  7. McCollough CH, Primak AN, Braun N, Kofler J, Yu L, Christner J. Strategies for reducing radiation dose in CT. Radiol Clin North Am 2009;47:27-40 https://doi.org/10.1016/j.rcl.2008.10.006
  8. Marin D, Nelson RC, Rubin GD, Schindera ST. Body CT: technical advances for improving safety. AJR Am J Roentgenol 2011;197:33-41 https://doi.org/10.2214/AJR.11.6755
  9. McCollough CH, Guimaraes L, Fletcher JG. In defense of body CT. AJR Am J Roentgenol 2009;193:28-39 https://doi.org/10.2214/AJR.09.2754
  10. Halliburton SS, Abbara S, Chen MY, Gentry R, Mahesh M, Raff GL, et al. SCCT guidelines on radiation dose and doseoptimization strategies in cardiovascular CT. J Cardiovasc Comput Tomogr 2011;5:198-224 https://doi.org/10.1016/j.jcct.2011.06.001
  11. Koshy S, Thompson RC. Review of radiation reduction strategies in clinical cardiovascular imaging. Cardiol Rev 2012;20:139-144 https://doi.org/10.1097/CRD.0b013e3182464c6f
  12. Hara AK, Paden RG, Silva AC, Kujak JL, Lawder HJ, Pavlicek W. Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study. AJR Am J Roentgenol 2009;193:764-771 https://doi.org/10.2214/AJR.09.2397
  13. Rogalla P, Kloeters C, Hein PA. CT technology overview: 64-slice and beyond. Radiol Clin North Am 2009;47:1-11 https://doi.org/10.1016/j.rcl.2008.10.004
  14. Kalender WA, Buchenau S, Deak P, Kellermeier M, Langner O, van Straten M, et al. Technical approaches to the optimisation of CT. Phys Med 2008;24:71-79 https://doi.org/10.1016/j.ejmp.2008.01.012
  15. Yamada Y, Jinzaki M, Tanami Y, Shiomi E, Sugiura H, Abe T, et al. Model-based iterative reconstruction technique for ultralow-dose computed tomography of the lung: a pilot study. Invest Radiol 2012;47:482-489 https://doi.org/10.1097/RLI.0b013e3182562a89
  16. Xu J, Mahesh M, Tsui BM. Is iterative reconstruction ready for MDCT? J Am Coll Radiol 2009;6:274-276 https://doi.org/10.1016/j.jacr.2008.12.014
  17. Hwang HJ, Seo JB, Lee JS, Song JW, Kim SS, Lee HJ, et al. Radiation dose reduction of chest CT with iterative reconstruction in image space - Part I: studies on image quality using dual source CT. Korean J Radiol 2012;13:711-719 https://doi.org/10.3348/kjr.2012.13.6.711
  18. Hwang HJ, Seo JB, Lee JS, Song JW, Kim SS, Lee HJ, et al. Radiation dose reduction of chest CT with iterative reconstruction in image space - Part II: assessment of radiologists' preferences using dual source CT. Korean J Radiol 2012;13:720-727 https://doi.org/10.3348/kjr.2012.13.6.720
  19. Goo HW. CT radiation dose optimization and estimation: an update for radiologists. Korean J Radiol 2012;13:1-11 https://doi.org/10.3348/kjr.2012.13.1.1
  20. 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 https://doi.org/10.1007/s00330-011-2271-7
  21. 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 2012;22:1287-1294 https://doi.org/10.1007/s00330-011-2361-6
  22. Yu L, Bruesewitz MR, Thomas KB, Fletcher JG, Kofler JM, McCollough CH. Optimal tube potential for radiation dose reduction in pediatric CT: principles, clinical implementations, and pitfalls. Radiographics 2011;31:835-848 https://doi.org/10.1148/rg.313105079
  23. Pontana F, Pagniez J, Flohr T, Faivre JB, Duhamel A, Remy J, et al. Chest computed tomography using iterative reconstruction vs filtered back projection (Part 1): evaluation of image noise reduction in 32 patients. Eur Radiol 2011;21:627-635 https://doi.org/10.1007/s00330-010-1990-5
  24. Gupta AK, Nelson RC, Johnson GA, Paulson EK, Delong DM, Yoshizumi TT. Optimization of eight-element multi-detector row helical CT technology for evaluation of the abdomen. Radiology 2003;227:739-745 https://doi.org/10.1148/radiol.2273020591
  25. Desai GS, Uppot RN, Yu EW, Kambadakone AR, Sahani DV. Impact of iterative reconstruction on image quality and radiation dose in multidetector CT of large body size adults. Eur Radiol 2012;22:1631-1640 https://doi.org/10.1007/s00330-012-2424-3
  26. Kalra MK, Maher MM, Blake MA, Lucey BC, Karau K, Toth TL, et al. Detection and characterization of lesions on low-radiationdose abdominal CT images postprocessed with noise reduction filters. Radiology 2004;232:791-797 https://doi.org/10.1148/radiol.2323031563
  27. Kanal KM, Stewart BK, Kolokythas O, Shuman WP. Impact of operator-selected image noise index and reconstruction slice thickness on patient radiation dose in 64-MDCT. AJR Am J Roentgenol 2007;189:219-225 https://doi.org/10.2214/AJR.06.1524
  28. Tatsugami F, Matsuki M, Nakai G, Inada Y, Kanazawa S, Takeda Y, et al. The effect of adaptive iterative dose reduction on image quality in 320-detector row CT coronary angiography. Br J Radiol 2012;85:e378-e382 https://doi.org/10.1259/bjr/10084599
  29. Martinsen AC, Saether HK, Hol PK, Olsen DR, Skaane P. Iterative reconstruction reduces abdominal CT dose. Eur J Radiol 2012;81:1483-1487 https://doi.org/10.1016/j.ejrad.2011.04.021
  30. Prakash P, Kalra MK, Ackman JB, Digumarthy SR, Hsieh J, Do S, et al. Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique. Radiology 2010;256:261-269 https://doi.org/10.1148/radiol.10091487
  31. Silva AC, Lawder HJ, Hara A, Kujak J, Pavlicek W. Innovations in CT dose reduction strategy: application of the adaptive statistical iterative reconstruction algorithm. AJR Am J Roentgenol 2010;194:191-199 https://doi.org/10.2214/AJR.09.2953
  32. Pontana F, Duhamel A, Pagniez J, Flohr T, Faivre JB, Hachulla AL, et al. Chest computed tomography using iterative reconstruction vs filtered back projection (Part 2): image quality of low-dose CT examinations in 80 patients. Eur Radiol 2011;21:636-643 https://doi.org/10.1007/s00330-010-1991-4
  33. Mitsumori LM, Shuman WP, Busey JM, Kolokythas O, Koprowicz KM. Adaptive statistical iterative reconstruction versus filtered back projection in the same patient: 64 channel liver CT image quality and patient radiation dose. Eur Radiol 2012;22:138-143 https://doi.org/10.1007/s00330-011-2186-3
  34. Thibault JB, Sauer KD, Bouman CA, Hsieh J. A threedimensional statistical approach to improved image quality for multislice helical CT. Med Phys 2007;34:4526-4544 https://doi.org/10.1118/1.2789499

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