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Clinical CT Performance Evaluation

  • Nicole LafataEmail author
  • Christopher J. MacLellan
Chapter

Abstract

This chapter focuses on CT performance evaluations from the perspective of the clinical medical physicist. A clinical physicist may need to evaluate a CT system under several different circumstances such as acceptance testing, annual testing, post-service testing, and accreditation testing. Each of these has a slightly different purpose, and the physicist should ensure that the scope of a specific evaluation is appropriate for the situation and regulatory environment. In this chapter we describe a set of procedures that should be considered when designing such an evaluation.

Typically, a thorough evaluation will assess the following: system safety and operation, system geometry, radiation output, and image quality. The safety and operational inspection focuses on radiation safety, quality control measures, and display monitor operation. System geometry testing ensures that the table, lasers, gantry, and collimation are all operating as intended. Radiation output is evaluated based on measurements of beam quality, a validation of computed tomography dose index (CTDI) accuracy, and characterization of tube current modulation. Finally, it is essential to evaluate the image quality of a system, including both traditional metrics (i.e., CT number accuracy and uniformity) and more advanced methods (i.e., noise power spectrum analysis and task-based metrics). These components collectively aid in ensuring the scanner is capable of safe high-quality imaging.

Keywords

Clinical physics Compliance testing Image quality Dosimetry 

References

  1. 1.
    Samei E, Bakalyar D, Boedeker K, Brady S, Fan J, Leng S, et al. Performance Evaluation of Computed Tomography Systems. American Association of Physicists in Medicine; Under Review. Report No.: 233.Google Scholar
  2. 2.
    Performance Standard for Ionizing Radiation Emitting Products. 21CFR. Sect. 1020.Google Scholar
  3. 3.
    Archer BR, Gray JE, Dixon R, Elde Jr. W, Hubbard L, Kearsely E, et al. Structural shielding design for diagnostic imaging facilities. NCRP; Report No.: 147.Google Scholar
  4. 4.
    Standard attributes on CT equipment related to dose optimization and management. NEMA. 2013. Report No.: XR-29.Google Scholar
  5. 5.
    Dillon C, Breeden III W, Clements J, Cody D, Gress D, Kanal K, et al. ACR CT quality control manual 2017. American College of Radiology; 2017.Google Scholar
  6. 6.
    Polacin A, Kalender WA, Brink J, Vannier MA. Measurement of slice sensitivity profiles in spiral CT. Med Phys. 1994;21(1):133–40.CrossRefGoogle Scholar
  7. 7.
    Wang G, Vannier MW. Stair-step artifacts in three-dimensional helical CT: an experimental study. Radiology. 1994;191(1):79–83.CrossRefGoogle Scholar
  8. 8.
    Greene TC, Rong XJ. Evaluation of techniques for slice sensitivity profile measurement and analysis. J Appl Clin Med Phys. 2014;15(2):4042.CrossRefGoogle Scholar
  9. 9.
    Quality Assurance Programme for Computed Tomography: Diagnostic and Therapy Applications. International Atomic Energy Agency. 2016. (IAEA Human Health Series). Report No.: 19.Google Scholar
  10. 10.
    Evaluation and routine testing in medical imaging departments – part 3–5: acceptance tests – imaging performance of computed tomography X-ray equipment. International Electrotechnical Comission; 2004. (IEC Standards). Report No.: 61223–3.Google Scholar
  11. 11.
    Liu H-L, Liu RR, Reeve DM, Shepard SJ, Willis CE. Measurement of CT radiation profile width using CR imaging plates. Med Phys. 2005;32(9):2881–7.CrossRefGoogle Scholar
  12. 12.
    Jackson SR, Ahmad S, Hu Y, Ruan C. Evaluation of different techniques for CT radiation profile width measurement. J Appl Clin Med Phys. 2013;14(4):4122.CrossRefGoogle Scholar
  13. 13.
    Bjarnason TA, Yang CJ. CT radiation profile width measurement using CR imaging plate raw data. J Appl Clin Med Phys. 2015;16(6):501–7.CrossRefGoogle Scholar
  14. 14.
    Computed tomography (CT) x-ray systems. NCAC. Sect. 15.0611.Google Scholar
  15. 15.
    Kruger RL, McCollough CH, Zink FE. Measurement of half-value layer in x-ray CT: a comparison of two noninvasive techniques. Med Phys. 2000;27(8):1915–9.CrossRefGoogle Scholar
  16. 16.
    O’Daniel JC, Stevens DM, Cody DD. Reducing radiation exposure from survey CT scans. Am J Roentgenol. 2005;185(2):509–15.CrossRefGoogle Scholar
  17. 17.
    International Commission on Radiation Units and Measurements. ICRU report no. 87: radiation dose and image-quality assessment in computed tomography. J ICRU. 2012;12(1):1–149.Google Scholar
  18. 18.
    Wilson JM, Christianson OI, Richard S, Samei E. A methodology for image quality evaluation of advanced CT systems. Med Phys. 2013;40(3):031908.CrossRefGoogle Scholar
  19. 19.
    TG233 Resources [Internet]. [cited 2019 May 8]. Available from: http://deckard.mc.duke.edu/~samei/tg233.html.
  20. 20.
    Cruz-Bastida JP, Gomez-Cardona D, Li K, Sun H, Hsieh J, Szczykutowicz TP, et al. Hi-res scan mode in clinical MDCT systems: experimental assessment of spatial resolution performance. Med Phys. 2016;43(5):2399–409.CrossRefGoogle Scholar
  21. 21.
    Chen B, Christianson O, Wilson JM, Samei E. Assessment of volumetric noise and resolution performance for linear and nonlinear CT reconstruction methods. Med Phys. 2014;41(7):071909.CrossRefGoogle Scholar
  22. 22.
    Friedman SN, Fung GSK, Siewerdsen JH, Tsui BMW. A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise-power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom. Med Phys. 2013;40(5):051907.CrossRefGoogle Scholar
  23. 23.
    Cunningham IA, Fenster A. A method for modulation transfer function determination from edge profiles with correction for finite-element differentiation. Med Phys. 1987;14(4):533–7.CrossRefGoogle Scholar
  24. 24.
    Boone JM. Determination of the presampled MTF in computed tomography. Med Phys. 2001;28(3):356–60.CrossRefGoogle Scholar
  25. 25.
    Judy PF. The line spread function and modulation transfer function of a computed tomographic scanner. Med Phys. 1976;3(4):233–6.CrossRefGoogle Scholar
  26. 26.
    Richard S, Husarik DB, Yadava G, Murphy SN, Samei E. Towards task-based assessment of CT performance: system and object MTF across different reconstruction algorithms. Med Phys. 2012;39(7):4115–22.CrossRefGoogle Scholar
  27. 27.
    Robins M, Solomon J, Richards T, Samei E. 3D task-transfer function representation of the signal transfer properties of low-contrast lesions in FBP- and iterative-reconstructed CT. Med Phys. 2018;45(11):4977–85.CrossRefGoogle Scholar
  28. 28.
    Monnin P, Marshall NW, Bosmans H, Bochud FO, Verdun FR. Image quality assessment in digital mammography: part II. NPWE as a validated alternative for contrast detail analysis. Phys Med Biol. 2011;56(14):4221–38.CrossRefGoogle Scholar
  29. 29.
    Ott JG, Becce F, Monnin P, Schmidt S, Bochud FO, Verdun FR. Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms. Phys Med Biol. 2014;59(15):4047–64.CrossRefGoogle Scholar
  30. 30.
    Verdun FR, Racine D, Ott JG, Tapiovaara MJ, Toroi P, Bochud FO, et al. Image quality in CT: from physical measurements to model observers. Phys Med. 2015;31(8):823–43.CrossRefGoogle Scholar
  31. 31.
    Nonparametric signal detectability evaluation using an exponential transformation of the FROC curve – Popescu – 2011 – Medical Physics – Wiley Online Library [Internet]. [cited 2019 May 5]. Available from: https://aapm.onlinelibrary.wiley.com/doi/full/10.1118/1.3633938.
  32. 32.
    Primak AN, Fletcher JG, Vrtiska TJ, Dzyubak OP, Lieske JC, Jackson ME, et al. Noninvasive differentiation of uric acid versus non–uric acid kidney stones using dual-energy CT. Acad Radiol. 2007;14(12):1441–7.CrossRefGoogle Scholar
  33. 33.
    Eiber M, Holzapfel K, Frimberger M, Straub M, Schneider H, Rummeny EJ, et al. Targeted dual-energy single-source CT for characterisation of urinary calculi: experimental and clinical experience. Eur Radiol. 2012;22(1):251–8.CrossRefGoogle Scholar
  34. 34.
    Boll DT, Patil NA, Paulson EK, Merkle EM, Simmons WN, Pierre SA, et al. Renal stone assessment with dual-energy multidetector CT and advanced postprocessing techniques: improved characterization of renal stone composition—pilot study. Radiology. 2009;250(3):813–20.CrossRefGoogle Scholar
  35. 35.
    Mileto A, Marin D, Alfaro-Cordoba M, Ramirez-Giraldo JC, Eusemann CD, Scribano E, et al. Iodine quantification to distinguish clear cell from papillary renal cell carcinoma at dual-energy multidetector CT: a multireader diagnostic performance study. Radiology. 2014;273(3):813–20.CrossRefGoogle Scholar
  36. 36.
    Zarzour JG, Milner D, Valentin R, Jackson BE, Gordetsky J, West J, et al. Quantitative iodine content threshold for discrimination of renal cell carcinomas using rapid kV-switching dual-energy CT. Abdom Radiol. 2017;42(3):727–34.CrossRefGoogle Scholar
  37. 37.
    Kaza RK, Caoili EM, Cohan RH, Platt JF. Distinguishing enhancing from nonenhancing renal lesions with fast kilovoltage-switching dual-energy CT. Am J Roentgenol. 2011;197(6):1375–81.CrossRefGoogle Scholar
  38. 38.
    Pomerantz SR, Kamalian S, Zhang D, Gupta R, Rapalino O, Sahani DV, et al. Virtual monochromatic reconstruction of dual-energy unenhanced head CT at 65–75 keV maximizes image quality compared with conventional polychromatic CT. Radiology. 2013;266(1):318–25.CrossRefGoogle Scholar
  39. 39.
    Wichmann JL, Nöske E-M, Kraft J, Burck I, Wagenblast J, Eckardt A, et al. Virtual monoenergetic dual-energy computed tomography: optimization of kiloelectron volt settings in head and neck cancer. Investig Radiol. 2014;49(11):735–41.CrossRefGoogle Scholar
  40. 40.
    Schneider D, Apfaltrer P, Sudarski S, Nance JW, Haubenreisser H, Fink C, et al. Optimization of kiloelectron volt settings in cerebral and cervical dual-energy CT angiography determined with virtual monoenergetic imaging. Acad Radiol. 2014;21(4):431–6.CrossRefGoogle Scholar
  41. 41.
    Yu L, Leng S, McCollough CH. Dual-energy CT–based monochromatic imaging. Am J Roentgenol. 2012;199(5_supplement):S9–15.CrossRefGoogle Scholar
  42. 42.
    Graser A, Johnson TRC, Hecht EM, Becker CR, Leidecker C, Staehler M, et al. Dual-energy CT in patients suspected of having renal masses: can virtual nonenhanced images replace true nonenhanced images? Radiology. 2009;252(2):433–40.CrossRefGoogle Scholar
  43. 43.
    Ferda J, Novák M, Mírka H, Baxa J, Ferdová E, Bednářová A, et al. The assessment of intracranial bleeding with virtual unenhanced imaging by means of dual-energy CT angiography. Eur Radiol. 2009;19(10):2518–22.CrossRefGoogle Scholar
  44. 44.
    Yu L, Christner JA, Leng S, Wang J, Fletcher JG, McCollough CH. Virtual monochromatic imaging in dual-source dual-energy CT: radiation dose and image quality. Med Phys. 2011;38(12):6371–9.CrossRefGoogle Scholar
  45. 45.
    Jacobsen MC, Schellingerhout D, Wood CA, Tamm EP, Godoy MC, Sun J, et al. Intermanufacturer comparison of dual-energy CT iodine quantification and monochromatic attenuation: a phantom study. Radiology. 2017;287(1):224–34.CrossRefGoogle Scholar
  46. 46.
    Nute JL, Jacobsen MC, Stefan W, Wei W, Cody DD. Development of a dual-energy computed tomography quality control program: characterization of scanner response and definition of relevant parameters for a fast-kVp switching dual-energy computed tomography system. Med Phys. 2018;45(4):1444–58.CrossRefGoogle Scholar
  47. 47.
    Jacobsen MC, Cresssman EN, Tamm EP, Baluya D, Duan X, Cody DD, et al. Dual-energy CT: lower limits of iodine detection and quantification. Radiology. 2019;292:414–9.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Clinical Imaging Physics GroupDuke University Health SystemDurhamUSA

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