Homogeneous B1 + for bilateral breast imaging at 7 T using a five dipole transmit array merged with a high density receive loop array.
Erwin KrikkenBart R SteensmaIngmar J VoogtPeter R LuijtenDennis W J KlompAlexander J E RaaijmakersJannie P WijnenPublished in: NMR in biomedicine (2018)
To explore the use of five meandering dipole antennas in a multi-transmit setup, combined with a high density receive array for breast imaging at 7 T for improved penetration depth and more homogeneous B1 field. Five meandering dipole antennas and 30 receiver loops were positioned on two cups around the breasts. Finite difference time domain simulations were performed to evaluate RF safety limits of the transmit setup. Scattering parameters of the transmit setup and coupling between the antennas and the detuned loops were measured. In vivo parallel imaging performance was investigated for various acceleration factors. After RF shimming, a B1 map, a T1 -weighted image, and a T2 -weighted image were acquired to assess B1 efficiency, uniformity in contrast weighting, and imaging performance in clinical applications. The maximum achievable local SAR10g value was 7.0 W/kg for 5 × 1 W accepted power. The dipoles were tuned and matched to a maximum reflection of -11.8 dB, and a maximum inter-element coupling of -14.2 dB. The maximum coupling between the antennas and the receive loops was -18.2 dB and the mean noise correlation for the 30 receive loops 7.83 ± 8.69%. In vivo measurements showed an increased field of view, which reached to the axilla, and a high transmit efficiency. This coil enabled the acquisition of T1 -weighted images with a high spatial resolution of 0.7 mm3 isotropic and T2 -weighted spin echo images with uniformly weighted contrast.
Keyphrases
- molecular dynamics
- high density
- magnetic resonance
- high resolution
- contrast enhanced
- deep learning
- network analysis
- room temperature
- magnetic resonance imaging
- diffusion weighted
- optical coherence tomography
- squamous cell carcinoma
- single molecule
- mass spectrometry
- machine learning
- case report
- diffusion weighted imaging
- ionic liquid
- high speed