Development and validation of a novel large field of view phantom and a software module for the quality assurance of geometric distortion in magnetic resonance imaging

Abstract

ObjectiveTo develop and validate a large field of view phantom and quality assurance software tool for the assessment and characterization of geometric distortion in MRI scanners commissioned for radiation therapy planning. Materials and MethodsA purpose built phantom was developed consisting of 357 rods (6mm in diameter) of polymethyl-methacrylat separated by 20mm intervals, providing a three dimensional array of control points at known spatial locations covering a large field of view up to a diameter of 420mm. An in-house software module was developed to allow automatic geometric distortion assessment. This software module was validated against a virtual dataset of the phantom that reproduced the exact geometry of the physical phantom, but with known translational and rotational displacements and warping. For validation experiments, clinical MRI sequences were acquired with and without the application of a commercial 3D distortion correction algorithm (Gradwarp™). The software module was used to characterize and assess system-related geometric distortion in the sequences relative to a benchmark CT dataset, and the efficacy of the vendor geometric distortion correction algorithms (GDC) was also assessed. ResultsResults issued from the validation of the software against virtual images demonstrate the algorithm's ability to accurately calculate geometric distortion with sub-pixel precision by the extraction of rods and quantization of displacements. Geometric distortion was assessed for the typical sequences used in radiotherapy applications and over a clinically relevant 420mm field of view (FOV). As expected and towards the edges of the field of view (FOV), distortion increased with increasing FOV. For all assessed sequences, the vendor GDC was able to reduce the mean distortion to below 1mm over a field of view of 5, 10, 15 and 20cm radius respectively. ConclusionResults issued from the application of the developed phantoms and algorithms demonstrate a high level of precision. The results indicate that this platform represents an important, robust and objective tool to perform routine quality assurance of MR-guided therapeutic applications, where spatial accuracy is paramount.