Purpose: To evaluate an independent linear model for gradient acoustic noise on a conventional MRI scanner, and to explore implications for acoustic noise reduction in routine imaging.
Methods: Acoustic noise generated from each physical gradient axis was modeled as the prescribed gradient waveform passed through a linear time-invariant system. Homogeneity and superposition properties were experimentally determined. We also developed a new method to correct relative time shifts between the measured impulse responses for different physical gradient axes. Model accuracy was determined by comparing predicted and measured sound using normalized energy difference. Transfer functions were also measured in subjects with different body habitus and at multiple microphone locations.
Results: Both superposition and homogeneity held for each physical gradient axis with errors less than 3%. When all gradients were on simultaneous sound prediction, error was reduced from 32% to 4% after time-shift correction. Transfer functions also showed high sensitivity to body habitus and microphone location.
Conclusion: The independent linear model predicts MRI acoustic noise with less than 4% error. Acoustic transfer functions are highly sensitive to body habitus and position within the bore, making it challenging to produce a general approach to acoustic noise reduction based on avoiding system resonance peaks.
Keywords: MRI; acoustic noise; frequency response; noise reduction; transfer function.
Copyright © 2013 Wiley Periodicals, Inc.