Advertisement
Original paper| Volume 45, P59-64, January 2018

Download started.

Ok

Assessment of the variation in CT scanner performance (image quality and Hounsfield units) with scan parameters, for image optimisation in radiotherapy treatment planning

  • Anne T. Davis
    Correspondence
    Corresponding author at: Department of Medical Physics, Portsmouth Hospitals NHS Trust, Portsmouth, UK.
    Affiliations
    Department of Physics, Faculty of Engineering and Physical Science, University of Surrey, Guildford, UK

    Department of Medical Physics, Portsmouth Hospitals NHS Trust, Portsmouth, UK
    Search for articles by this author
  • Antony L. Palmer
    Affiliations
    Department of Physics, Faculty of Engineering and Physical Science, University of Surrey, Guildford, UK

    Department of Medical Physics, Portsmouth Hospitals NHS Trust, Portsmouth, UK
    Search for articles by this author
  • Silvia Pani
    Affiliations
    Department of Physics, Faculty of Engineering and Physical Science, University of Surrey, Guildford, UK
    Search for articles by this author
  • Andrew Nisbet
    Affiliations
    Department of Physics, Faculty of Engineering and Physical Science, University of Surrey, Guildford, UK

    Department of Medical Physics, Royal Surrey County Hospital NHS Foundation Trust, Guildford, UK
    Search for articles by this author

      Highlights

      • Test method to assess how CT parameters affect image quality and Hounsfield units.
      • CNR and HCSR varied most with reconstruction algorithm, reconstruction FOV and mAs.
      • Hounsfield units changed with acquisition FOV and reconstruction algorithm selected.
      • The results will enable optimisation of CT protocols used for radiotherapy planning.

      Abstract

      Purpose

      To define a method and investigate how the adjustment of scan parameters affected the image quality and Hounsfield units (HUs) on a CT scanner used for radiotherapy treatment planning. A lack of similar investigations in the literature may be a contributing factor in the apparent reluctance to optimise radiotherapy CT protocols.

      Method

      A Catphan phantom was used to assess how image quality on a Toshiba Aquilion LB scanner changed with scan parameters. Acquisition and reconstruction field-of-view (FOV), collimation, image slice thickness, effective mAs per rotation and reconstruction algorithm were varied. Changes were assessed for HUs of different materials, high contrast spatial resolution (HCSR), contrast-noise ratio (CNR), HU uniformity, scan direction low contrast and CT dose-index.

      Results

      CNR and HCSR varied most with reconstruction algorithm, reconstruction FOV and effective mAs. Collimation, but not image slice width, had a significant effect on CT dose-index with narrower collimation giving higher doses. Dose increased with effective mAs. Highest HU differences were seen when changing reconstruction algorithm: 56 HU for densities close to water and 117 HU for bone-like materials. Acquisition FOV affected the HUs but reconstruction FOV and effective mAs did not.

      Conclusions

      All the scan parameters investigated affected the image quality metrics. Reconstruction algorithm, reconstruction FOV, collimation and effective mAs were most important. Reconstruction algorithm and acquisition FOV had significant effect on HU. The methodology is applicable to radiotherapy CT scanners when investigating image quality optimisation, prior to assessing the impact of scan protocol changes on clinical CT images and treatment plans.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Physica Medica: European Journal of Medical Physics
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Nelms B.E.
        • Tome W.A.
        • Robinson G.
        • Wheeler J.
        Variations in the contouring of organs at risk: test case from a patient with oropharyngeal cancer.
        Int J Radiat Oncol Biol Phys. 2012; 82: 368-378
        • Hurkmans C.
        • Borger J.
        • Pieters B.
        • Russell N.
        • Jansen E.
        • Mijnheer B.
        Variability in target volume delineation on CT scans of the breast.
        Int J Radiat Oncol Biol Phys. 2001; 50: 1366-1372
        • Li X.A.
        • Tai A.
        • Arthur D.W.
        • Buchholz T.A.
        • Macdonald S.
        • Marks L.B.
        • et al.
        Variability of target and normal structure delineation for breast cancer radiotherapy: an RTOG Multi-Institutional and Multiobserver Study.
        Int J Radiat Oncol Biol Phys. 2009; 73: 944-951
        • Brouwer C.L.
        • Steenbakkers R.J.
        • Bourhis J.
        • Budach W.
        • Grau C.
        • Gregoire V.
        • et al.
        CT-based delineation of organs at risk in the head and neck region: DAHANCA, EORTC, GORTEC, HKNPCSG, NCIC CTG, NCRI, NRG Oncology and TROG consensus guidelines.
        Radiother Oncol. 2015; 117: 83-90
        • Fraass B.
        • Doppke K.
        • Hunt M.
        • Kutcher G.
        • Starkschall G.
        • Stern R.
        • et al.
        American Association of Physicists in Medicine Radiation Therapy Committee Task Group 53: quality assurance for clinical radiotherapy treatment planning.
        Med Phys. 1998; 25: 1773-1829
      1. Ionising Radiation (Medical Exposure) Regulations. 2000.

        • Craig T.
        • Brochu D.
        • Van Dyke J.
        A quality assurance phantom for three-dimensional radiation treatment planning.
        Int J Radiat Oncol Biol Phys. 1999; 955–66
        • Cozzi L.
        • Fogliata A.
        • Buffa F.
        • Bieri S.
        Dosimetric impact of computed tomography calibration on a commercial treatment planning system for external beam radiotherapy.
        Radiother Oncol. 1998; 335–8
      2. European guidelines on quality criteria for computed tomography EUR 16262. Luxemburg: European Commission; 1999.

      3. American Association of Physicists in Medicine. The alliance for quality computed tomography. CT protocols.

        • Mutic S.
        • Palta J.R.
        • Butker E.K.
        • Das I.J.
        • Huq M.S.
        • Loo L.N.
        • et al.
        Quality assurance for computed-tomography simulators and the computed-tomography-simulation process: report of the AAPM Radiation Therapy Committee Task Group No. 66.
        Med Phys. 2003; 30: 2762-2792
      4. ESTRO. Quality Assurance of treatment planning systems: Practical examples for non-IMRT photon beams. ESTRO booklet no 72004.

      5. IAEA. IAEA Human Health Series No 19, Quality Assurance for Computed Tomography: Diagnostic and Therapy Applications. 2012.

        • Thomson E.
        • Edyvean S.
        IPEM report 88 – physical aspects of quality control in radiotherapy.
        Institute of Physics and Engineering in Medicine, York, UK1999
        • Bissonnette J.P.
        • Balter P.A.
        • Dong L.
        • Langen K.M.
        • Lovelock D.M.
        • Miften M.
        • et al.
        Quality assurance for image-guided radiation therapy utilizing CT-based technologies: a report of the AAPM TG-179.
        Med Phys. 2012; 39: 1946-1963
        • Davis A.
        • Palmer A.
        • Nisbet A.
        Can CT scan protocols used for radiotherapy treatment planning be adjusted to optimize image quality and patient dose? A systematic review.
        Br J Radiol. 2017; https://doi.org/10.1259/bjr.20160406
        • Kearns D.
        • McJury M.
        Commissioning a new CT simulator I: CT simulator hardware.
        J Radiother Pract. 2007; : 6
        • McCann C.
        • Alasti H.
        Comparative evaluation of image quality from three CT simulation scanners.
        J Appl Clin Med Phys. 2004; 5: 55-70
        • Coolens C.
        • Breen S.
        • Purdie T.G.
        • Owrangi A.
        • Publicover J.
        • Bartolac S.
        • et al.
        Implementation and characterization of a 320-slice volumetric CT scanner for simulation in radiation oncology.
        Med Phys. 2009; 36: 5120
      6. Purchasing and Supply Agency, ImPACT. Report 05071 Siemens Somatom Sensation Open CT scanner technical evaluation. 2005.

      7. ImPACT. MHRA 04045-Toshiba Aquillion 16 CT scanner Technical Evaluation. 2004.

        • Zurl B.
        • Tiefling R.
        • Winkler P.
        • Kindl P.
        • Kapp K.S.
        Hounsfield units variations: impact on CT-density based conversion tables and their effects on dose distribution.
        Strahlenther Onkol. 2014; 190: 88-93
      8. Corporation TMS. Operation manual for Toshiba scanner Aquilion TSX 201A. 2008.

        • Ebert M.
        CT-ED conversion on a GE Lightspeed-RT scanner: influence of scanner settings.
        Austral Phys Eng Sci Med. 2008; 31: 154-159
        • Stock M.
        • Pasler M.
        • Birkfellner W.
        • Homolka P.
        • Poetter R.
        • Georg D.
        Image quality and stability of image-guided radiotherapy (IGRT) devices: a comparative study.
        Radiother Oncol. 2009; 93: 1-7
      9. Edyvean S, Lewis M, Keat N, Jones A. IPEM Report no. 32. Measurement of the performance characteristics of diagnostic X-ray systems used in medicine. Part III Computed tomography X-ray scanners. York, UK.: Institute of Physics and Engineering in Medicine; 2003.

        • Skrzynski W.
        • Zielinska-Dabrowska S.
        • Wachowicz M.
        • Slusarczyk-Kacprzyk W.
        • Kukolowicz P.F.
        • Bulski W.
        Computed tomography as a source of electron density information for radiation treatment planning.
        Strahlenther Onkol. 2010; 186: 327-333
        • Goldman L.W.
        Principles of CT: radiation dose and image quality.
        J Nucl Med Technol. 2007; 35: 213-225
        • Hatton J.
        • McCurdy B.
        • Greer P.B.
        Cone beam computerized tomography: the effect of calibration of the Hounsfield unit number to electron density on dose calculation accuracy for adaptive radiation therapy.
        Phys Med Biol. 2009; 54: N329-N346
        • Guan H.
        • Dong H.
        Dose calculation accuracy using cone-beam CT (CBCT) for pelvic adaptive radiotherapy.
        Phys Med Biol. 2009; 54: 6239-6250
        • Chu J.
        • Ni B.
        • Kriz R.
        • Saxena V.
        Applications of simulator CT number for photon dose calculations during radiotherapy treatment planning.
        Radiother Oncol. 2000; 55: 65-73