Sequence optimization for MRI acoustic noise reduction

Abstract

The large acoustic noise of 80-110 dB during magnetic resonance imaging (MRI) scanning harms patients’ comfort and health. The noise can be reduced by hardware modification or active noise control, but these methods are expensive, difficult, or not very effective. In this study, a sequence optimization method is used to mitigate the acoustic noise problem while maintaining image quality. The 4th order polynomial function is applied to design the new quiet pulse sequences, decreasing the gradient slew rate and higher time derivatives of the original trapezoidal lobes. A sound pressure level (SPL) estimation method is proposed to predict the acoustic noise loudness from the gradient and is used for genetic algorithm sequence optimization. The original and quiet gradient recalled echo (GRE) sequences are applied on a 1.5 T MRI scanner. The average SPL is reduced by 18.6 dBA, and the images show small differences and have similar SNR values. This method is also applied for the scouting and shimming GRE sequences in common clinical applications with significant noise reduction.