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Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection

  • Yoon, Hyun Jung (Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Chung, Myung Jin (Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Hwang, Hye Sun (Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Moon, Jung Won (Department of Radiology, Kangbuk Samsung Hospital) ;
  • Lee, Kyung Soo (Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine)
  • Received : 2015.01.06
  • Accepted : 2015.06.02
  • Published : 2015.09.01

Abstract

Objective: To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules. Materials and Methods: Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically. Results: Converted effective doses in SCT and ULDCT were $2.81{\pm}0.92$ and $0.17{\pm}0.02mSv$, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00). Conclusion: Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT.

Keywords

References

  1. Greenlee RT, Murray T, Bolden S, Wingo PA. Cancer statistics, 2000. CA Cancer J Clin 2000;50:7-33 https://doi.org/10.3322/canjclin.50.1.7
  2. Fry WA, Menck HR, Winchester DP. The National Cancer Data Base report on lung cancer. Cancer 1996;77:1947-1955 https://doi.org/10.1002/(SICI)1097-0142(19960501)77:9<1947::AID-CNCR27>3.0.CO;2-Z
  3. Flehinger BJ, Kimmel M, Melamed MR. The effect of surgical treatment on survival from early lung cancer. Implications for screening. Chest 1992;101:1013-1018 https://doi.org/10.1378/chest.101.4.1013
  4. Melamed MR, Flehinger BJ, Zaman MB. Impact of early detection on the clinical course of lung cancer. Surg Clin North Am 1987;67:909-924 https://doi.org/10.1016/S0039-6109(16)44329-X
  5. Nesbitt JC, Putnam JB Jr, Walsh GL, Roth JA, Mountain CF. Survival in early-stage non-small cell lung cancer. Ann Thorac Surg 1995;60:466-472 https://doi.org/10.1016/0003-4975(95)00169-L
  6. Shah R, Sabanathan S, Richardson J, Mearns AJ, Goulden C. Results of surgical treatment of stage I and II lung cancer. J Cardiovasc Surg (Torino) 1996;37:169-172
  7. Evans SH, Davis R, Cooke J, Anderson W. A comparison of radiation doses to the breast in computed tomographic chest examinations for two scanning protocols. Clin Radiol 1989;40:45-46 https://doi.org/10.1016/S0009-9260(89)80021-2
  8. Lenzen H, Roos N, Diederich S, Meier N. [Radiation exposure in low dose computerized tomography of the thorax]. Radiologe 1996;36:483-488 https://doi.org/10.1007/s001170050101
  9. Parry RA, Glaze SA, Archer BR. The AAPM/RSNA physics tutorial for residents. Typical patient radiation doses in diagnostic radiology. Radiographics 1999;19:1289-1302 https://doi.org/10.1148/radiographics.19.5.g99se211289
  10. Van Unnik JG, Broerse JJ, Geleijns J, Jansen JT, Zoetelief J, Zweers D. Survey of CT techniques and absorbed dose in various Dutch hospitals. Br J Radiol 1997;70:367-371 https://doi.org/10.1259/bjr.70.832.9166072
  11. Wall BF, Hart D. Revised radiation doses for typical X-ray examinations. Report on a recent review of doses to patients from medical X-ray examinations in the UK by NRPB. National Radiological Protection Board. Br J Radiol 1997;70:437-439 https://doi.org/10.1259/bjr.70.833.9227222
  12. Gartenschläger M, Schweden F, Gast K, Westermeier T, Kauczor H, von Zitzewitz H, et al. Pulmonary nodules: detection with low-dose vs conventional-dose spiral CT. Eur Radiol 1998;8:609-614 https://doi.org/10.1007/s003300050445
  13. Henschke CI, Yankelevitz DF, McCauley DI, Libby DM, Pasmantier MW, Smith JP. Guidelines for the use of spiral computed tomography in screening for lung cancer. Eur Respir J Suppl 2003;39:45s-51s
  14. Rusinek H, Naidich DP, McGuinness G, Leitman BS, McCauley DI, Krinsky GA, et al. Pulmonary nodule detection: low-dose versus conventional CT. Radiology 1998;209:243-249 https://doi.org/10.1148/radiology.209.1.9769838
  15. Diederich S, Lenzen H, Windmann R, Puskas Z, Yelbuz TM, Henneken S, et al. Pulmonary nodules: experimental and clinical studies at low-dose CT. Radiology 1999;213:289-298 https://doi.org/10.1148/radiology.213.1.r99oc29289
  16. National Lung Screening Trial Research Team, Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365:395-409 https://doi.org/10.1056/NEJMoa1102873
  17. Brenner DJ, Elliston CD. Estimated radiation risks potentially associated with full-body CT screening. Radiology 2004;232:735-738 https://doi.org/10.1148/radiol.2323031095
  18. 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
  19. 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
  20. Kalra MK, Maher MM, Sahani DV, Blake MA, Hahn PF, Avinash GB, et al. Low-dose CT of the abdomen: evaluation of image improvement with use of noise reduction filters pilot study. Radiology 2003;228:251-256 https://doi.org/10.1148/radiol.2281020693
  21. 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
  22. 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
  23. Prakash P, Kalra MK, Digumarthy SR, Hsieh J, Pien H, Singh S, et al. Radiation dose reduction with chest computed tomography using adaptive statistical iterative reconstruction technique: initial experience. J Comput Assist Tomogr 2010;34:40-45 https://doi.org/10.1097/RCT.0b013e3181b26c67
  24. 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
  25. Yanagawa M, Honda O, Yoshida S, Kikuyama A, Inoue A, Sumikawa H, et al. Adaptive statistical iterative reconstruction technique for pulmonary CT: image quality of the cadaveric lung on standard- and reduced-dose CT. Acad Radiol 2010;17:1259-1266 https://doi.org/10.1016/j.acra.2010.05.014
  26. Leipsic J, Nguyen G, Brown J, Sin D, Mayo JR. A prospective evaluation of dose reduction and image quality in chest CT using adaptive statistical iterative reconstruction. AJR Am J Roentgenol 2010;195:1095-1099 https://doi.org/10.2214/AJR.09.4050
  27. 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. Eur Radiol 2013;23:1623-1631 https://doi.org/10.1007/s00330-012-2765-y
  28. Willemink MJ, Leiner T, de Jong PA, de Heer LM, Nievelstein RA, Schilham AM, et al. Iterative reconstruction techniques for computed tomography part 2: initial results in dose reduction and image quality. Eur Radiol 2013;23:1632-1642 https://doi.org/10.1007/s00330-012-2764-z
  29. Naidich DP, Marshall CH, Gribbin C, Arams RS, McCauley DI. Low-dose CT of the lungs: preliminary observations. Radiology 1990;175:729-731 https://doi.org/10.1148/radiology.175.3.2343122
  30. Chakraborty DP, Berbaum KS. Observer studies involving detection and localization: modeling, analysis, and validation. Med Phys 2004;31:2313-2330 https://doi.org/10.1118/1.1769352
  31. Chakraborty DP. Analysis of location specific observer performance data: validated extensions of the jackknife free-response (JAFROC) method. Acad Radiol 2006;13:1187-1193 https://doi.org/10.1016/j.acra.2006.06.016
  32. Vikgren J, Zachrisson S, Svalkvist A, Johnsson AA, Boijsen M, Flinck A, et al. Comparison of chest tomosynthesis and chest radiography for detection of pulmonary nodules: human observer study of clinical cases. Radiology 2008;249:1034-1041 https://doi.org/10.1148/radiol.2492080304
  33. Hirose T, Nitta N, Shiraishi J, Nagatani Y, Takahashi M, Murata K. Evaluation of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector row computed tomography (MDCT): JAFROC study for the improvement in radiologists’ diagnostic accuracy. Acad Radiol 2008;15:1505-1512 https://doi.org/10.1016/j.acra.2008.06.009
  34. Zachrisson S, Vikgren J, Svalkvist A, Johnsson AA, Boijsen M, Flinck A, et al. Effect of clinical experience of chest tomosynthesis on detection of pulmonary nodules. Acta Radiol 2009;50:884-891 https://doi.org/10.1080/02841850903085584
  35. Yanagawa M, Honda O, Yoshida S, Ono Y, Inoue A, Daimon T, et al. Commercially available computer-aided detection system for pulmonary nodules on thin-section images using 64 detectors-row CT: preliminary study of 48 cases. Acad Radiol 2009;16:924-933 https://doi.org/10.1016/j.acra.2009.01.030
  36. Larke FJ, Kruger RL, Cagnon CH, Flynn MJ, McNitt-Gray MM, Wu X, et al. Estimated radiation dose associated with low-dose chest CT of average-size participants in the National Lung Screening Trial. AJR Am J Roentgenol 2011;197:1165-1169 https://doi.org/10.2214/AJR.11.6533
  37. Boone JM, Strauss KJ, Cody DD, McCollough CH, McNitt-Gray MF, Toth TL, et al. Size-specific dose estimates (SSDE) in pediatric and adult body CT examinations. Report of AAPM Task Group 204. College Park: American Association of Physicists in Medicine, 2011
  38. Katsura M, Matsuda I, Akahane M, Yasaka K, Hanaoka S, Akai H, et al. Model-based iterative reconstruction technique for ultralow-dose chest CT: comparison of pulmonary nodule detectability with the adaptive statistical iterative reconstruction technique. Invest Radiol 2013;48:206-212
  39. Neroladaki A, Botsikas D, Boudabbous S, Becker CD, Montet X. Computed tomography of the chest with model-based iterative reconstruction using a radiation exposure similar to chest X-ray examination: preliminary observations. Eur Radiol 2013;23:360-366 https://doi.org/10.1007/s00330-012-2627-7
  40. Wormanns D, Ludwig K, Beyer F, Heindel W, Diederich S. Detection of pulmonary nodules at multirow-detector CT: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest CT. Eur Radiol 2005;15:14-22 https://doi.org/10.1007/s00330-004-2527-6
  41. Seltzer SE, Judy PF, Adams DF, Jacobson FL, Stark P, Kikinis R, et al. Spiral CT of the chest: comparison of cine and film-based viewing. Radiology 1995;197:73-78 https://doi.org/10.1148/radiology.197.1.7568857
  42. Diederich S, Semik M, Lentschig MG, Winter F, Scheld HH, Roos N, et al. Helical CT of pulmonary nodules in patients with extrathoracic malignancy: CT-surgical correlation. AJR Am J Roentgenol 1999;172:353-360 https://doi.org/10.2214/ajr.172.2.9930781

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