Spiral MRI on a 9.4T Vertical-bore Superconducting Magnet Using Unshielded and Self-shielded Gradient Coils

MR Imaging in the 21st Century: Technical Innovation over the First Two Decades

Clinical MRI systems have continually improved over the years since their introduction in the 1980s. In MRI technical development, the developments in each MRI system component, including data acquisition, image reconstruction, and hardware systems, have impacted the others. Progress in each component has induced new technology development opportunities in other components. New technologies outside of the MRI field, for example, computer science, data processing, and semiconductors, have been immediately incorporated into MRI development, which resulted in innovative applications. With high performance computing and MR technology innovations, MRI can now provide large volumes of functional and anatomical image datasets, which are important tools in various research fields. MRI systems are now combined with other modalities, such as positron emission tomography (PET) or therapeutic devices. These hybrid systems provide additional capabilities.

In this review, MRI advances in the last two decades will be considered. We will discuss the progress of MRI systems, the enabling technology, established applications, current trends, and the future outlook.

3D Cones Acquisition of Human Extremity Imaging Using a 1.5T Superconducting Magnet and an Unshielded Gradient Coil Set

We developed ultrashort echo-time (UTE) imaging sequences with 3D Cones trajectories for a home-built compact MRI system using a 1.5T superconducting magnet and an unshielded gradient coil set. We achieved less than 7 min imaging time and obtained clear in vivo images of a human forearm with a TE of 0.4 ms. We concluded that UTE imaging using 3D Cones acquisition was successfully implemented in our 1.5T MRI system.

A Fast GPU-optimized 3D MRI Simulator for Arbitrary k-space Sampling

Purpose:

To develop a fast 3D MRI simulator for arbitrary k-space sampling using a graphical processing unit (GPU) and demonstrate its performance by comparing simulation and experimental results in a real MRI system.

Materials and Methods:

A fast 3D MRI simulator using a GeForce GTX 1080 GPU (NVIDIA Corporation, Santa Clara, CA, USA) was developed using C++ and the CUDA 8.0 platform (NVIDIA Corporation). The unique advantage of this simulator was that it could use the same pulse sequence as used in the experiment. The performance of the MRI simulator was measured using two GTX 1080 GPUs and 3D Cones sequences. The MRI simulation results for 3D non-Cartesian sampling trajectories like 3D Cones sequences using a numerical 3D phantom were compared with the experimental results obtained with a real MRI system and a real 3D phantom.

Results:

The performance of the MRI simulator was about 3800–4900 gigaflops for 128- to 4-shot 3D Cones sequences with 256³ voxels, which was about 60% of the performance of the previous MRI simulator optimized for Cartesian sampling calculated for a Cartesian sampling gradient-echo sequence with 256³ voxels. The effects of the static magnetic field inhomogeneity, radio-frequency field inhomogeneity, gradient field nonlinearity, and fast repetition times on the MR images were reproduced in the simulated images as observed in the experimental images.

Conclusion:

The 3D MRI simulator developed for arbitrary k-space sampling optimized using GPUs is a powerful tool for the development and evaluation of advanced imaging sequences including both Cartesian and non-Cartesian k-space sampling.