Geometric distortion in magnetic resonance imaging systems assessed using an open-source plugin for scientific image analysis
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Tumor locations are commonly delineated by referring to magnetic resonance (MR) images. However, MR images have geometric distortions that cannot be completely corrected. This study aimed to investigate quantitatively uncorrectable error [residual error (RE)] with the use of an open-source plugin for scientific image analysis. The RE values were calculated by Fiji, which was enhanced by Image J image processing software. The results obtained with the open-source plugin for scientific image analysis agreed with the results obtained with the commercially available software. Obtaining detailed geometric distortion data for each facility and device could facilitate safe treatment because the homogeneous magnetic field in MR imaging varies across devices and over time. Therefore, using an open-source plugin for scientific image analysis may be an accurate and effective technique for evaluating the RE of MR imaging systems.
KeywordsImage distortion Magnetic resonance imaging Open-source plugin for scientific image analysis Residual error Stereotactic radiation therapy
We are grateful to Mr Yoshito Ichiba of Siemens Healthineers, Japan K.K., for his useful suggestions. We thank Mr Masamiti Hojo of QualitA, Ltd., for his helpful advice. Additionally, we thank the Japan Association of Radiological Technologists. Furthermore, the authors would like to thank Enago (http://www.enago.jp) for the English language review.
Compliance with ethical standards
Conflict of interest
The authors have no conflicts of interest to declare.
Statement of human and animal rights
There is no animal or humans involved in this study.
There are no human subjects involved in this work.
- 3.Wang D, Strugnell W, Cowin G, Doddrell DM, Slaughter R. Geometric distortion in clinical MRI systems: part I: evaluation using a 3D phantom. J Magn Reson. 2004;22:1211–21.Google Scholar
- 4.Watanabe Y, Lee CK, Gerbi BJ. Geometrical accuracy of a 3-tesla magnetic resonance imaging unit in Gamma Knife surgery. Spec Suppl. 2006;105:190–3.Google Scholar
- 6.Wang D, Strugnell W, Cowin G, Doddrell DM, Slaughter R. Geometric distortion in clinical MRI systems: part II: correction using a 3D phantom. Magn Reson Med. 2004;29:1223–32.Google Scholar
- 11.Sun J, Dowling J, Pichler P, Menk F, Rivest-Henault D, Lambert J, et al. MRI simulation: end-to-end testing for prostate radiation therapy using geometric pelvic MRI phantoms. Int J Radiat Oncol Biol Phys. 2015;60:3097–109.Google Scholar
- 13.Takemura A, Sasamoto K, Nakamura K, Kuroda T, Shoji S, Matsuura Y, et al. Comparison of image distortion between three magnetic resonance imaging systems of different magnetic field strengths for use in stereotactic irradiation of brain. Nihon Hoshasen Gijutsu Gakkaizasshi Zasshi. 2013;69:641–7.CrossRefGoogle Scholar
- 17.Rasband WS. ImageJ US. National Institutes of Health, Bethesda, Maryland, USA. http://imagej.nih.gov/ij/. 1997–2012.
- 19.NEMA-MS-2. Determination of two-dimensional geometric distortion in diagnostic magnetic resonance images: MS 2–2008 (R2014). Rosslyn: National Electrical Manufacturers Association; 2003.Google Scholar
- 20.Chudler EH. Brain facts and figures. University of Washington. 2017. http://faculty.washington.edu/chudler/ehceduc.html. Accessed 17 Oct 2017.