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MRI distortion: considerations for MRI based radiotherapy treatment planning

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Abstract

Distortion in magnetic resonance images needs to be taken into account for the purposes of radiotherapy treatment planning (RTP). A commercial MRI grid phantom was scanned on four different MRI scanners with multiple sequences to assess variations in the geometric distortion. The distortions present across the field of view were then determined. The effect of varying bandwidth on image distortion and signal to noise was also investigated. Distortion maps were created and these were compared to the location of patient anatomy within the scanner bore to estimate the magnitude and distribution of distortions located within specific clinical regions. Distortion magnitude and patterns varied between MRI sequence protocols and scanners. The magnitude of the distortions increased with increasing distance from the isocentre of the scanner within a 2D imaging plane. Average distortion across the phantom generally remained below 2.0 mm, although towards the edge of the phantom for a turbo spin echo sequence, the distortion increased to a maximum value of 4.1 mm. Application of correction algorithms supplied by each vendor reduced but did not completely remove distortions. Increasing the bandwidth of the acquisition sequence decreased the amount of distortion at the expense of a reduction in signal-to-noise ratio of 13.5 across measured bandwidths. Imaging protocol parameters including bandwidth, slice thickness and phase encoding direction, should be noted for distortion investigations in RTP since each can influence the distortion. The magnitude of distortion varies across different clinical sites.

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References

  1. Khoo VS, Dearnaley DP, Finnigan DJ, Padhani A, Tanner SF, Leach MO (1997) Magnetic resonance imaging (MRI): considerations and applications in radiotherapy treatment planning. Radiother Oncol 42(1):1–15. doi:10.1016/s0167-8140(96)01866-x

    CAS  PubMed  Google Scholar 

  2. Chen L, Price JRA, Wang L, Li J, Qin L, McNeeley S, Ma CMC, Freedman GM, Pollack A (2004) MRI-based treatment planning for radiotherapy: dosimetric verification for prostate IMRT. Int J Radiat Oncol Biol Phys 60(2):636–647. doi:10.1016/j.ijrobp.2004.05.068

    PubMed  Google Scholar 

  3. Prabhakar R, Julka PK, Ganesh T, Munshi A, Joshi RC, Rath GK (2007) Feasibility of using MRI alone for 3D radiation treatment planning in brain tumors. Jpn J Clin Oncol 37(6):405–411

    CAS  PubMed  Google Scholar 

  4. Baldwin LN, Wachowicz K, Thomas SD, Rivest R, Fallone BG (2007) Characterization, prediction, and correction of geometric distortion in 3 T MR images. Med Phys 34(2):388–399. doi:10.1118/1.2402331

    PubMed  Google Scholar 

  5. Jezzard P (2009) The physical basis of spatial distortions in magnetic resonance images. In: Bankman IN (ed) Handbook of medical image processing and analysis, 2nd edn. Elsevier, Amsterdam, pp 499–514

    Google Scholar 

  6. Chang H, Fitzpatrick JM (1992) A technique for accurate magnetic resonance imaging in the presence of field inhomogeneities. IEEE Trans Med Imaging 11(3):319–329

    CAS  PubMed  Google Scholar 

  7. Doran SJ, Charles-Edwards L, Reinsberg SA, Leach MO (2005) A complete distortion correction for MR images: I. Gradient warp correction. Phys Med Biol 50(7):1343

    PubMed  Google Scholar 

  8. Crijns SPM, Raaymakers BW, Lagendijk JJW (2011) Real-time correction of magnetic field inhomogeneity-induced image distortions for MRI-guided conventional and proton radiotherapy. Phys Med Biol 56(1):289–297

    CAS  PubMed  Google Scholar 

  9. Wang D, Doddrell DM, Cowin G (2004) A novel phantom and method for comprehensive 3-dimensional measurement and correction of geometric distortion in magnetic resonance imaging. Magn Reson Imaging 22(4):529–542. doi:10.1016/j.mri.2004.01.008

    PubMed  Google Scholar 

  10. Mizowaki T, Nagata Y, Okajima K, Kokubo M, Negoro Y, Araki N, Hiraoka M (2000) Reproducibility of geometric distortion in magnetic resonance imaging based on phantom studies. Radiother Oncol 57(2):237–242. doi:10.1016/s0167-8140(00)00234-6

    CAS  PubMed  Google Scholar 

  11. Karger CP, Höss A, Bendl R, Canda V, Schad L (2006) Accuracy of device-specific 2D and 3D image distortion correction algorithms for magnetic resonance imaging of the head provided by a manufacturer. Phys Med Biol 51(12):N253

    PubMed  Google Scholar 

  12. Antolak JA, Rosen II (1999) Planning target volumes for radiotherapy: how much margin is needed? Int J Radiat Oncol Biol Phys 44(5):1165–1170

    CAS  PubMed  Google Scholar 

  13. Janke A, Zhao H, Cowin GJ, Galloway GJ, Doddrell DM (2004) Use of spherical harmonic deconvolution methods to compensate for nonlinear gradient effects on MRI images. Magn Reson Med 52(1):115–122. doi:10.1002/mrm.20122

    PubMed  Google Scholar 

  14. Baldwin LN, Wachowicz K, Fallone BG (2009) A two-step scheme for distortion rectification of magnetic resonance images. Med Phys 36(9):3917–3926

    PubMed  Google Scholar 

  15. Bakker CJG, Moerland MA, Bhawandien R, Beersma R (1992) Analysis of machine-dependent and object-induced geometric distortion in 2DFT MR imaging. Magn Reson Imaging 10(4):597–608. doi:10.1016/0730-725x(92)90011-n

    CAS  PubMed  Google Scholar 

  16. Petersch B, Bogner J, Fransson A, Lorang T, Pötter R (2004) Effects of geometric distortion in 0.2 T MRI on radiotherapy treatment planning of prostate cancer. Radiother Oncol 71(1):55–64. doi:10.1016/j.radonc.2003.12.012

    PubMed  Google Scholar 

  17. Stanescu T, Jans HS, Wachowicz K, Fallone BG (2010) Investigation of a 3D system distortion correction method for MR images. J Appl Clin Med Phys 11(1):2961

    Google Scholar 

  18. Stanescu T, Hans-Sonke J, Stavrev P, Fallone BG (2006) 3T MR-based treatment planning for radiotherapy of brain lesions. Radiol Oncol 40(2):125–132

    Google Scholar 

  19. Crijns SPM, Bakker CJG, Seevinck PR, de Leeuw H, Lagendijk JJW, Raaymakers BW (2012) Towards inherently distortion-free MR images for image-guided radiotherapy on an MRI accelerator. Phys Med Biol 57(5):1349

    CAS  PubMed  Google Scholar 

  20. Zhang B, MacFadden D, Damyanovich AZ, Rieker M, Stainsby J, Bernstein M, Jaffray DA, Mikulis D, Menard C (2010) Development of a geometrically accurate imaging protocol at 3 Tesla MRI for stereotactic radiosurgery treatment planning. Phys Med Biol 55(1):6601–6615. doi:10.1088/0031-9155/55/22/002

    CAS  PubMed  Google Scholar 

  21. Chen H–H, Boykin RD, Clarke GD, Gao JHT, Roby JW III (2006) Routine testing of magnetic field homogeneity on clinical MRI systems. Med Phys 33(11):4299–4306

    PubMed  Google Scholar 

  22. AAPM (1990) Quality assurance methods and phantoms for magnetic resonance imaging: report of AAPM nuclear magnetic resonance Task Group No 1. Med Phys 17(2):287–295. doi:10.1118/1.596566

    Google Scholar 

  23. Moerland MA (1996) Magnetic resonance imaging in radiotherapy treatment planning. University Utrecht, Utrecht

    Google Scholar 

  24. Devic S (2012) MRI simulation for radiotherapy treatment planning. Med Phys 39(11):6701–6711. doi:10.1118/1.4758068

    PubMed  Google Scholar 

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Acknowledgments

The authors would like to thank Michael Jameson from Liverpool Cancer Therapy Centre for useful discussions and access to some in-house code utilised in part of this project, as well as Peter Greer from the Calvary Mater Hospital Newcastle for access to the phantom. Special thanks to Matthew Hundy (Wollongong hospital), Joseph Turner (Campbelltown hospital) and Michael Serratore (Liverpool hospital) for their time in allowing access to the clinical MRI scanners to conduct this study.

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Authors and Affiliations

  1. Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, 2522, Australia

    Amy Walker, Gary Liney, Peter Metcalfe & Lois Holloway

  2. Liverpool and Macarthur Cancer Therapy Centres, Ingham Institute, Liverpool, NSW, 2170, Australia

    Amy Walker, Gary Liney, Peter Metcalfe & Lois Holloway

  3. South West Clinical School, University of New South Wales, Sydney, NSW, 2052, Australia

    Gary Liney & Lois Holloway

  4. Institute of Medical Physics, School of Physics, University of Sydney, Sydney, NSW, 2006, Australia

    Lois Holloway

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  1. Amy Walker
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  2. Gary Liney
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  4. Lois Holloway
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Correspondence to Amy Walker.

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Walker, A., Liney, G., Metcalfe, P. et al. MRI distortion: considerations for MRI based radiotherapy treatment planning. Australas Phys Eng Sci Med 37, 103–113 (2014). https://doi.org/10.1007/s13246-014-0252-2

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  • DOI: https://doi.org/10.1007/s13246-014-0252-2

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