Work

A Hybrid RF Coil for Whole‐Brain Imaging in Non‐Human Primates at 7 T

Year: 2026

Type: article

Abstract: PURPOSE: Ultra-high field MRI (≥ 7 T) offers unprecedented potential for mapping non-human primate (NHP) brain function. However, complex electromagnetic systems are required to meet the challenges of UHF imaging and the mechanical demands of awake NHP studies. To address these challenges, we developed a hybrid RF coil system optimized for whole-brain fMRI of macaques at 7 T. METHODS: The hybrid coil system combines a 6-channel preamplifier-decoupled transceive dipole array with a 16-channel loop receive array, housed in a compact structure designed for awake imaging that maintains open visual fields. Key design features include compatibility with sphinx-position monkey chairs and head fixation systems required for awake experiments. Electromagnetic simulations guided dipole design to optimize uniform transmit performance and deep penetration. Phantom and in vivo experiments validated these predictions using anesthetized macaques and evaluated the system's readiness for awake imaging. RESULTS: distribution with phase-shimmed transmission across the brain. It supported robust parallel imaging, enabling up to R = 3 × 2 acceleration factors for high-resolution acquisitions. The achieved whole-brain tSNR in fMRI is comparable to that of an existing 8-TX/24-RX coil designed for imaging anesthetized macaques. Critically, submillimeter (0.75 mm isotropic) resting-state fMRI revealed clear default-mode network connectivity, confirming the system's capability for high-quality functional imaging. CONCLUSION: By effectively addressing both the technical challenges of ultra-high field MRI and the mechanical constraints associated with visual stimulation in awake NHPs, this hybrid coil system provides a powerful tool for advancing our understanding of primate brain function.

Source: Magnetic Resonance in Medicine

DOI: 10.1002/mrm.70361

Authors: Elias Djaballah, Éric Giacomini, Paul‐François Gapais, Michel Luong, Alexis Amadon, Qi Zhu