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 () 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 resolution. In vivo mouse brain MR and CT images had 140 and 200 resolutions, respectively. Three shimming strategies were established to assess displacements () in phantom MR images. 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 and GNL distortions via non‐rigid registration with CT, and a two‐step distortion correction (2SDC) method, which corrects separately in two consecutive steps 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 () were quantified in phantom VOIs and the in vivo skull region by measuring landmarks' positions. Results The 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 0.2 mm. The 2SDC method outperformed 1SDC by achieving a 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 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 and GNL corrections. Moreover, a phantom‐based displacement map shows promise for in vivo GNL correction.