Optimizing Oscillating Diffusion Gradients to Reduce Mechanical Vibration and Acoustic Noise on Ultra‐High Gradient Scanners

PURPOSE: The deployment of oscillating gradient spin echo (OGSE) diffusion encoding sequences on ultra-high gradient scanners enables advanced microstructure imaging but induces intense acoustic noise and mechanical vibrations, causing subject discomfort and compromising imaging stability and quantitative accuracy. This study implements Acoustic noise and Vibration Optimized dIffusion gradient Design (AVOID) to mitigate these side effects, facilitating the high-performance OGSE applications in demanding hardware environments. METHODS: System transfer functions were measured on a 3.0T ultra-high gradient NeuroFrontier MRI system to characterize hardware responses. The optimization algorithm reshaped OGSE waveforms by redistributing spectral energy away from resonant frequencies while maintaining multiple constraints including hardware limits and desired diffusion encoding spectrum. The optimization was validated by comparing non-optimized and optimized waveforms through physical measurements, phantom scans, and in vivo human brain scans. RESULTS: Reductions of up to 10 dBA in predicted sound pressure level and 3.4 dB in vibration power spectral intensity were achieved. In phantom experiments, vibration-induced artifacts were significantly mitigated, resulting in superior repeatability and lower coefficients of variation in ADC maps, approaching the minimum-vibration reference by pulsed gradient sequences. In vivo validation demonstrated enhanced acquisition stability and consistent frequency-dependent ADC trends from 0 to 120 Hz. CONCLUSION: The AVOID framework effectively suppressed intense acoustic noise and mechanical vibration induced by strong oscillating gradients on ultra-high gradient scanners, ensuring a stable and comfortable environment for advanced microstructural imaging.