Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning-based filter using convolutional neural network.

OBJECTIVES: To reveal the utility of motion artifact reduction with convolutional neural network (MARC) in gadoxetate disodium-enhanced multi-arterial phase MRI of the liver. METHODS: This retrospective study included 192 patients (131 men, 68.7 ± 10.3 years) receiving gadoxetate disodium-enhanced liver MRI in 2017. Datasets were submitted to a newly developed filter (MARC), consisting of 7 convolutional layers, and trained on 14,190 cropped images generated from abdominal MR images. Motion artifact for training was simulated by adding periodic k-space domain noise to the images. Original and filtered images of pre-contrast and 6 arterial phases (7 image sets per patient resulting in 1344 sets in total) were evaluated regarding motion artifacts on a 4-point scale. Lesion conspicuity in original and filtered images was ranked by side-by-side comparison. RESULTS: Of the 1344 original image sets, motion artifact score was 2 in 597, 3 in 165, and 4 in 54 sets. MARC significantly improved image quality over all phases showing an average motion artifact score of 1.97 ± 0.72 compared to 2.53 ± 0.71 in original MR images (p < 0.001). MARC improved motion scores from 2 to 1 in 177/596 (29.65%), from 3 to 2 in 119/165 (72.12%), and from 4 to 3 in 34/54 sets (62.96%). Lesion conspicuity was significantly improved (p < 0.001) without removing anatomical details. CONCLUSIONS: Motion artifacts and lesion conspicuity of gadoxetate disodium-enhanced arterial phase liver MRI were significantly improved by the MARC filter, especially in cases with substantial artifacts. This method can be of high clinical value in subjects with failing breath-hold in the scan. KEY POINTS: • This study presents a newly developed deep learning-based filter for artifact reduction using convolutional neural network (motion artifact reduction with convolutional neural network, MARC). • MARC significantly improved MR image quality after gadoxetate disodium administration by reducing motion artifacts, especially in cases with severely degraded images. • Postprocessing with MARC led to better lesion conspicuity without removing anatomical details.

Magnetic field shimming of a permanent magnet using a combination of pieces of permanent magnets and a single-channel shim coil for skeletal age assessment of children.

We adopted a combination of pieces of permanent magnets and a single-channel (SC) shim coil to shim the magnetic field in a magnetic resonance imaging system dedicated for skeletal age assessment of children. The target magnet was a 0.3-T open and compact permanent magnet tailored to the hand imaging of young children. The homogeneity of the magnetic field was first improved by shimming using pieces of permanent magnets. The residual local inhomogeneity was then compensated for by shimming using the SC shim coil. The effectiveness of the shimming was measured by imaging the left hands of human subjects and evaluating the image quality. The magnetic resonance images for the child subject clearly visualized anatomical structures of all bones necessary for skeletal age assessment, demonstrating the usefulness of combined shimming.

Development of a temperature-variable magnetic resonance imaging system using a 1.0T yokeless permanent magnet.

A temperature variable magnetic resonance imaging (MRI) system has been developed using a 1.0 T permanent magnet. A permanent magnet, gradient coils, radiofrequency coil, and shim coil were installed in a temperature variable thermostatic bath. First, the variation in the magnetic field inhomogeneity with temperature was measured. The inhomogeneity has a specific spatial symmetry, which scales linearly with temperature, and a single-channel shim coil was designed to compensate for the inhomogeneity. The inhomogeneity was drastically reduced by shimming over a wide range of temperature from -5°C to 45°C. MR images of an okra pod acquired at different temperatures demonstrated the high potential of the system for visualizing thermally sensitive properties.