Assessment and mitigation of geometric distortions in Cartesian MR images at 15.2T for preclinical radiation research

Abstract

Background: Ultra-high field (UHF) magnetic resonance (MR) systems are advancing in preclinical imaging offering the potential to enhance radiation research. However, system-dependent factors, such as magnetic field inhomogeneities ((Formula presented.)) and gradient non-linearity (GNL), induce geometric distortions compromising the sub-millimeter accuracy required for radiation research. Purpose: This study tackles system-dependent distortions in 15.2T MR images by prospective shimming strategies optimization and comparing two imaging methods for voxel displacement correction. The methods were evaluated on a 3D-printed grid phantom and validated on in vivo mouse brain MR images. Additionally, a phantom-based displacement map was tested for GNL correction in mouse brain images. Methods: Phantom MR and CT images were acquired with 200 (Formula presented.) resolution. In vivo mouse brain MR and CT images had 140 (Formula presented.) and 200 (Formula presented.) resolutions, respectively. Three shimming strategies were established to assess (Formula presented.) displacements ((Formula presented.)) in phantom MR images. (Formula presented.) was calculated using the acquired static field maps in three volumes of interest (VOIs) via Python script. A one-step distortion correction (1SDC) method, which simultaneously corrects (Formula presented.) and GNL distortions via non-rigid registration with CT, and a two-step distortion correction (2SDC) method, which corrects separately in two consecutive steps (Formula presented.) and GNL displacements, were assessed on phantom and in vivo images. For in vivo 2SDC validation, a phantom displacement map generated by MR to CT non-rigid registration was applied to correct GNL on the mouse brain. Total displacements ((Formula presented.)) were quantified in phantom VOIs and the in vivo skull region by measuring landmarks' positions. Results: The (Formula presented.) in the phantom increased with distance from the VOI center and magnet isocenter. Shimming scenario-2 showed the lowest maximum displacement (0.26 mm) for the largest VOI but required a longer acquisition time. Distortion correction methods were necessary for large VOIs (13–25 mm, along the z-axis) in the phantom where (Formula presented.) (Formula presented.) 0.2 mm. The 2SDC method outperformed 1SDC by achieving a (Formula presented.) 0.2 mm accuracy in 100%, 92.1%, and 59.3% of the landmarks from the smallest to the largest VOI. Phantom dice scores confirmed the improvement in geometric precision after each correction step. In vivo results showed that 1SDC correction overcorrected MR images, increasing voxel displacements. The 2SDC exceeded the 1SDC, reducing (Formula presented.) by 85%, in accordance with the dice score analysis (0.97 2SDC vs. 0.84 1SDC). Conclusions: At 15.2T, in vivo MR images of even small regions (e.g., mouse brain) require geometric distortion correction for radiation research. The 2SDC method outperformed the 1SDC, emphasizing the need for separate (Formula presented.) and GNL corrections. Moreover, a phantom-based displacement map shows promise for in vivo GNL correction.