Hairpin RF resonators for MR imaging transceiver arrays with high inter-channel isolation and B1 efficiency at ultrahigh field 7 T.

Electromagnetic decoupling among a close-fitting or high-density transceiver RF array elements is required to maintain the integrity of the magnetic flux density from individual channel for enhanced performance in detection sensitivity and parallel imaging. High-impedance RF coils have demonstrated to be a prominent design method to circumvent these coupling issues. Yet, inherent characteristics of these coils have ramification on the B1 field efficiency and SNR. In this work, we propose a hairpin high impedance RF resonator design for highly decoupled multichannel transceiver arrays at ultrahigh magnetic fields. Due to the high impedance property of the hairpin resonators, the proposed transceiver array can provide high decoupling performance without using any dedicated decoupling circuit among the resonant elements. Because of elimination of lumped inductors in the resonator circuit, higher B1 field efficiency in imaging subjects can be expected. In order to validate the feasibility of the proposed hairpin RF coils, systematical studies on decoupling performance, field distribution, and SNR are performed, and the results are compared with those obtained from existing high-impedance RF coil, e.g., "self-decoupled RF coil". To further investigate its performance, an 8-channel head coil array using the proposed hairpin resonators loaded with a cylindrical phantom is designed, demonstrating a 19 % increase of the B1+ field intensity compared to the self-decoupled coils at 7 T. Furthermore, the characteristics of the hairpin RF coils are evaluated using a more realistic human head voxel model numerically. The proposed hairpin RF coil provides excellent decoupling performance and superior RF magnetic field efficiency compared to the "self-decoupled" high impedance coils. Bench test of a pair of fabricated hairpin coils prove to be in good accordance with numerical results.

Minimizing Molecular Misidentification in Imaging Low-Abundance Protein Interactions Using Spectroscopic Single-Molecule Localization Microscopy.

Super-resolution microscopy can capture spatiotemporal organizations of protein interactions with resolution down to 10 nm; however, the analyses of more than two proteins involving low-abundance protein are challenging because spectral crosstalk and heterogeneities of individual fluorescent labels result in molecular misidentification. Here we developed a deep learning-based imaging analysis method for spectroscopic single-molecule localization microscopy to minimize molecular misidentification in three-color super-resolution imaging. We characterized the 3-fold reduction of molecular misidentification in the new imaging method using pure samples of different photoswitchable fluorophores and visualized three distinct subcellular proteins in U2-OS cell lines. We further validated the protein counts and interactions of TOMM20, DRP1, and SUMO1 in a well-studied biological process, Staurosporine-induced apoptosis, by comparing the imaging results with Western-blot analyses of different subcellular portions.