Why buy an expensive ($7 million) 7T MRI system for biomedical research?

Self-supervised anatomical continuity enhancement network for 7T SWI synthesis from 3T SWI

Synthesizing 7T Susceptibility Weighted Imaging (SWI) from 3T SWI could offer significant clinical benefits by combining the high sensitivity of 7T SWI for neurological disorders with the widespread availability of 3T SWI in diagnostic routines. Although methods exist for synthesizing 7T Magnetic Resonance Imaging (MRI), they primarily focus on traditional MRI modalities like T1-weighted imaging, rather than SWI. SWI poses unique challenges, including limited data availability and the invisibility of certain tissues in individual 3T SWI slices. To address these challenges, we propose a Self-supervised Anatomical Continuity Enhancement (SACE) network to synthesize 7T SWI from 3T SWI using plentiful 3T SWI data and limited 3T-7T paired data. The SACE employs two specifically designed pretext tasks to utilize low-level representations from abundant 3T SWI data for assisting 7T SWI synthesis in a downstream task with limited paired data. One pretext task emphasizes input-specific morphology by balancing the elimination of redundant patterns with the preservation of essential morphology, preventing the blurring of synthetic 7T SWI images. The other task improves the synthesis of tissues that are invisible in a single 3T SWI slice by aligning adjacent slices with the current slice and predicting their difference fields. The downstream task innovatively combines clinical knowledge with brain substructure diagrams to selectively enhance clinically relevant features. When evaluated on a dataset comprising 97 cases (5495 slices), the proposed method achieved a Peak Signal-to-Noise Ratio (PSNR) of 23.05 dB and a Structural Similarity Index (SSIM) of 0.688. Due to the absence of specific methods for 7T SWI, our method was compared with existing enhancement techniques for general 7T MRI synthesis, outperforming these techniques in the context of 7T SWI synthesis. Clinical evaluations have shown that our synthetic 7T SWI is clinically effective, demonstrating its potential as a clinical tool.

New insights into intrinsic foot muscle morphology and composition using ultra-high-field (7-Tesla) magnetic resonance imaging

Background

The intrinsic muscles of the foot are key contributors to foot function and are important to evaluate in lower limb disorders. Magnetic resonance imaging (MRI), provides a non-invasive option to measure muscle morphology and composition, which are primary determinants of muscle function. Ultra-high-field (7-T) magnetic resonance imaging provides sufficient signal to evaluate the morphology of the intrinsic foot muscles, and, when combined with chemical-shift sequences, measures of muscle composition can be obtained. Here we aim to provide a proof-of-concept method for measuring intrinsic foot muscle morphology and composition with high-field MRI.

Methods

One healthy female (age 39 years, mass 65 kg, height 1.73 m) underwent MRI. A T1-weighted VIBE – radio-frequency spoiled 3D steady state GRE – sequence of the whole foot was acquired on a Siemens 7T MAGNETOM scanner, as well as a 3T MAGNETOM Prisma scanner for comparison. A high-resolution fat/water separation image was also acquired using a 3D 2-point DIXON sequence at 7T. Coronal plane images from 3T and 7T scanners were compared. Using 3D Slicer software, regions of interest were manually contoured for each muscle on 7T images. Muscle volumes and percentage of muscle fat infiltration were calculated (muscle fat infiltration % = Fat/(Fat + Water) x100) for each muscle.

Results

Compared to the 3T images, the 7T images provided superior resolution, particularly at the forefoot, to facilitate segmentation of individual muscles. Muscle volumes ranged from 1.5 cm³ and 19.8 cm³, and percentage muscle fat infiltration ranged from 9.2–15.0%.

Conclusions

This proof-of-concept study demonstrates a feasible method of quantifying muscle morphology and composition for individual intrinsic foot muscles using advanced high-field MRI techniques. This method can be used in future studies to better understand intrinsic foot muscle morphology and composition in healthy individuals, as well as those with lower disorders.