Spatial Precision in Magnetic Resonance Imaging–Guided Radiation Therapy: The Role of Geometric Distortion

Publication date: 15 July 2016
Source:International Journal of Radiation Oncology*Biology*Physics, Volume 95, Issue 4
Author(s): Joseph Weygand, Clifton David Fuller, Geoffrey S. Ibbott, Abdallah S.R. Mohamed, Yao Ding, Jinzhong Yang, Ken-Pin Hwang, Jihong Wang
Because magnetic resonance imaging–guided radiation therapy (MRIgRT) offers exquisite soft tissue contrast and the ability to image tissues in arbitrary planes, the interest in this technology has increased dramatically in recent years. However, intrinsic geometric distortion stemming from both the system hardware and the magnetic properties of the patient affects MR images and compromises the spatial integrity of MRI-based radiation treatment planning, given that for real-time MRIgRT, precision within 2 mm is desired. In this article, we discuss the causes of geometric distortion, describe some well-known distortion correction algorithms, and review geometric distortion measurements from 12 studies, while taking into account relevant imaging parameters. Eleven of the studies reported phantom measurements quantifying system-dependent geometric distortion, while 2 studies reported simulation data quantifying magnetic susceptibility–induced geometric distortion. Of the 11 studies investigating system-dependent geometric distortion, 5 reported maximum measurements less than 2 mm. The simulation studies demonstrated that magnetic susceptibility–induced distortion is typically smaller than system-dependent distortion but still nonnegligible, with maximum distortion ranging from 2.1 to 2.6 mm at a field strength of 1.5 T. As expected, anatomic landmarks containing interfaces between air and soft tissue had the largest distortions. The evidence indicates that geometric distortion reduces the spatial integrity of MRI-based radiation treatment planning and likely diminishes the efficacy of MRIgRT. Better phantom measurement techniques and more effective distortion correction algorithms are needed to achieve the desired spatial precision.



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