Abstract

ObjectiveTo develop a method for the assessment and characterization of 3D geometric distortion as part of routine quality assurance for MRI scanners commissioned for Radiation Therapy planning. Materials and methodsIn this study, the in-plane and through-plane geometric distortions on a 1.5T GE MRI-SIM unit are characterized and the 2D and 3D correction algorithms provided by the vendor are evaluated. We used a phantom developed by GE Healthcare that covers a large field of view of 500mm, and consists of layers of foam embedded with a matrix of ellipsoidal markers. An in-house Java-based software module was developed to automatically assess the geometric distortion by calculating the center of each marker using the center of mass method, correcting of gross rotation errors and comparing the corrected positions with a CT gold standard data set. Spatial accuracy of typical pulse sequences used in RT planning was assessed (2D T1/T2 FSE, 3D CUBE, T1 SPGR) using the software. The accuracy of vendor specific geometric distortion correction (GDC) algorithms was quantified by measuring distortions before and after the application of the 2D and 3D correction algorithms. ResultsOur algorithm was able to accurately calculate geometric distortion with sub-pixel precision. For all typical MR sequences used in Radiotherapy, the vendor’s GDC was able to substantially reduce the distortions. Our results showed also that the impact of the acquisition produced a maximum variation of 0.2mm over a radial distance of 200mm. It has been shown that while the 2D correction algorithm remarkably reduces the in-plane geometric distortion, 3D geometric distortion further reduced the geometric distortion by correcting both in-plane and through-plane distortions in all acquisitions. ConclusionThe presented methods represent a valuable tool for routine quality assurance of MR applications that require stringent spatial accuracy assessment such as radiotherapy. The phantom used in this study provides three dimensional arrays of control points. These tools and the detailed results can be also used for developing new geometric distortion correction algorithms or improving the existing ones.

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