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A Practice Quality Improvement Project: Reducing Dose of Routine Chest CT Imaging in a Busy Clinical Practice

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Abstract

The purpose of this report is to describe our experience with the implementation of a practice quality improvement (PQI) project in thoracic imaging as part of the American Board of Radiology Maintenance of Certification process. The goal of this PQI project was to reduce the effective radiation dose of routine chest CT imaging in a busy clinical practice by employing the iDose4 (Philips Healthcare) iterative reconstruction technique. The dose reduction strategy was implemented in a stepwise process on a single 64-slice CT scanner with a volume of 1141 chest CT scans during the year. In the first annual quarter, a baseline effective dose was established using the standard filtered back projection (FBP) algorithm protocol and standard parameters such as kVp and mAs. The iDose4 technique was then applied in the second and third annual quarters while keeping all other parameters unchanged. In the fourth quarter, a reduction in kVp was also implemented. Throughout the process, the images were continually evaluated to assure that the image quality was comparable to the standard protocol from multiple other scanners. Utilizing a stepwise approach, the effective radiation dose was reduced by 23.62 and 43.63 % in quarters two and four, respectively, compared to our initial standard protocol with no perceived difference in diagnostic quality. This practice quality improvement project demonstrated a significant reduction in the effective radiation dose of thoracic CT scans in a busy clinical practice.

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References

  1. Hawkins CM, Alsip CN, Pryor RM, et al: Quality improvement and confirmation projects: facilitating rapid, measurable performance improvement. Radiographics 33(7):e225–35, 2013

    Article  PubMed  Google Scholar 

  2. Strife JL, Kun LE, Becker GJ, et al: The American board of radiology perspective on maintenance of certification: part IV—practice quality improvement for diagnostic radiology. Radiology 243(2):309–13, 2007

    Article  PubMed  Google Scholar 

  3. American Board of Radiology. MOC: Maintenance of certification. Available from: http://www.theabr.org/moc-landing. Accessed: May 8, 2014.

  4. Griffith B, Brown ML, Jain R: Improving imaging utilization through practice quality improvement (maintenance of certification part IV): a review of requirements and approach to implementation. AJR Am J Roentgenol 202(4):797–802, 2014

    Article  PubMed  Google Scholar 

  5. Kouo T: Experience with a practice quality improvement system in a university radiology department. J Am Coll Radiol 9(11):814–9, 2012

    Article  PubMed  Google Scholar 

  6. Keegan J, Miglioretti DL, Gould R, et al: Radiation dose metrics in CT: assessing dose using the National Quality Forum CT patient safety measure. J Am Coll Radiol 11(3):309–15, 2014

    Article  PubMed  Google Scholar 

  7. Choudhery S, Richter M, Anene A, et al: Practice quality improvement during residency: where do we stand and where can we improve? Acad Radiol 21(7):851–58, 2014

    Article  PubMed  Google Scholar 

  8. Silva 3rd, E: MOC for dollars. J Am Col Radiol 8(11):746–8, 2011

    Article  Google Scholar 

  9. Tamm EP, Szklaruk J, Puthooran L, et al: Quality initiatives: planning, setting up, and carrying out radiology process improvement projects. Radiographics 32(5):1529–42, 2012

    Article  PubMed  Google Scholar 

  10. Lee CS, Larson DB: Beginner’s guide to practice quality improvement using the model for improvement. J Am Coll Radiol 11(12ptA):1131–6, 2014

    Article  PubMed  Google Scholar 

  11. Hirsch JA, Becker GJ, Derdeyn CP, et al: Maintenance of certification: part 2-continuous certification. J Neurointerv Surg 6(2):156–60, 2014

    Article  PubMed  Google Scholar 

  12. Smith-Bindman R: Is computed tomography safe? N Engl J Med 363(1):1–4, 2010

    Article  CAS  PubMed  Google Scholar 

  13. Brenner DJ, Doll R, Goodhead DT, et al: Cancer risks attributable to low doses of ionizing radiation: assessing what we really know. PNAS 100(24):13761–6, 2003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Takahashi EA, Yoon HC: Four-year cumulative radiation exposure in patients undergoing computed tomography angiography for suspected pulmonary embolism. Radiol Res Pract. 2013:482403, 2013

    PubMed  PubMed Central  Google Scholar 

  15. Beister M, Kolditz D, Kalender WA: Iterative reconstruction methods in X-ray CT. Phys Med 28(2):94–108, 2012

    Article  PubMed  Google Scholar 

  16. Gonzalez-Guindalini FD, Ferreira Botelho MP, Tore HG, et al: MDCT of chest, abdomen, and pelvis using attenuation-based automated tube voltage selection in combination with iterative reconstruction: an intrapatient study of radiation dose and image quality. AJR Am J Roentgenol 201(5):1075–82, 2013

    Article  PubMed  Google Scholar 

  17. Christe A, Heverhagen J, Ozdoba C, et al: CT dose and image quality in the last three scanner generations. World J Radiol 5(11):421–9, 2013

    Article  PubMed  PubMed Central  Google Scholar 

  18. Lee SW, Kim Y, Shim SS, et al: Image quality assessment of ultra low-dose chest CT using sonogram-affirmed iterative reconstruction. Eur Radiol 24(4):817–26, 2014

    Article  PubMed  Google Scholar 

  19. Ning P, Zhu S, Shi D, et al: X-ray dose reduction in abdominal computed tomography using advanced iterative reconstruction algorithms. PLoS One 9(3):e92568, 2014

    Article  PubMed  PubMed Central  Google Scholar 

  20. Matsuki M, Murakami T, Juri H, et al: Impact of adaptive iterative dose reduction (AIDR) 3D on low-dose abdominal CT: comparison with routine-dose CT using filtered back projection. Acta Radiol 54(8):869–75, 2013

    Article  PubMed  Google Scholar 

  21. Kim M, Lee JM, Yoon JH, et al: Adaptive iterative dose reduction algorithm in CT: effect on image quality compared to filtered back projection in body phantoms of different sizes. Korean J Radiol 15(2):195–204, 2014

    Article  PubMed  PubMed Central  Google Scholar 

  22. Prakash P, Kalra MK, Digumarthy SR, et al: Radiation dose reduction with chest computed tomography using adaptive statistical iterative reconstruction technique: initial experience. J Comput Assist Tomogr 34(1):40–5, 2010

    Article  PubMed  Google Scholar 

  23. Noel PB, Renger B, Fiebich M, et al: Does iterative reconstruction lower CT radiation dose: evaluation of 15,000 examinations. PLoS One 8(11):e81141, 2013

    Article  PubMed  PubMed Central  Google Scholar 

  24. Arapakis I, Efstathopoulos E, Tsitsia V, et al: Using “iDose4” iterative reconstruction algorithm in adults’ chest-abdomen-pelvis CT examinations: effect on image quality in relation to patient radiation exposure. Br J Radiol. 87:20130613, 2014

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lagmani A, Buhk JH, Henes FO, et al: Impact of a 4th generation iterative reconstruction technique on image quality in low-dose computed tomography of the chest in immunocompromised patients. Rofo 185(8):749–57, 2013

    Article  Google Scholar 

  26. Li Q, Yu H, Zhang L, et al: Combining low tube voltage and iterative reconstruction for contrast-enhanced CT imaging of the chest—initial clinical experience. Clin Radiol 68(5):e249–53, 2013

    Article  CAS  PubMed  Google Scholar 

  27. Cook TS, Zimmerman S, Maidment AD, et al: Automated extraction of radiation dose information for CT examinations. J Am Coll Radiol 7(11):871–7, 2010

    Article  PubMed  Google Scholar 

  28. Yousem DM, Nidecker A: Maintenance of certification: update on attitudes of members of the American Society of Neuroradiology. AJNR Am J Neuroradiol 31(8):1369–72, 2010

    Article  CAS  PubMed  Google Scholar 

  29. Khawaja RD, Singh S, Gilman M, et al: Computed tomography (CT) of the chest at less than 1 mSv: an ongoing prospective clinical trial of chest CT at submillisievert radiation doses with iterative model image reconstruction and iDose4 technique. J Comput Assist Tomogr 38(4):613–9, 2014

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA

    Edwin A. Takahashi

  2. Department of Radiology, Indiana University, 550 N. University Blvd., Indianapolis, IN, 46202, USA

    Marc D. Kohli

  3. Department of Radiology, National Jewish Health, 1400 Jackson St, Room A368, Denver, CO, 80206, USA

    Shawn D. Teague

Authors
  1. Edwin A. Takahashi
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  2. Marc D. Kohli
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  3. Shawn D. Teague
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Corresponding author

Correspondence to Edwin A. Takahashi.

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The authors declare that they have no competing interests.

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Takahashi, E.A., Kohli, M.D. & Teague, S.D. A Practice Quality Improvement Project: Reducing Dose of Routine Chest CT Imaging in a Busy Clinical Practice. J Digit Imaging 29, 622–626 (2016). https://doi.org/10.1007/s10278-016-9877-x

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  • DOI: https://doi.org/10.1007/s10278-016-9877-x

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