title: Acoustic FMRI noise: linear time-invariant system model.
abstract: Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For auditory system studies, however, the acoustic noise generated by the scanner tends to interfere with the assessments of this activation. Understanding and modeling fMRI acoustic noise is a useful step to its reduction. To study acoustic noise, the MR scanner is modeled as a linear electroacoustical system generating sound pressure signals proportional to the time derivative of the input gradient currents. The transfer function of one MR scanner is determined for two different input specifications: 1) by using the gradient waveform calculated by the scanner software and 2) by using a recording of the gradient current. Up to 4 kHz, the first method is shown as reliable as the second one, and its use is encouraged when direct measurements of gradient currents are not possible. Additionally, the linear order and average damping properties of the gradient coil system are determined by impulse response analysis. Since fMRI is often based on echo planar imaging (EPI) sequences, a useful validation of the transfer function prediction ability can be obtained by calculating the acoustic output for the EPI sequence. We found a predicted sound pressure level (SPL) for the EPI sequence of 104 dB SPL compared to a measured value of 102 dB SPL. As yet, the predicted EPI pressure waveform shows similarity as well as some differences with the directly measured EPI pressure waveform.
authors: Department of Biomedical Engineering, Faculty of Mathematics and Natural Sciences, University of Groningen, NL 9747 AG Groningen, The Netherlands. c.rizzo@med.umcg.nl
authors: Carlos V
authors: CV
authors: Rizzo Sierra
authors: Maarten J
authors: MJ
authors: Versluis
authors: Johannes M
authors: JM
authors: Hoogduin
authors: Hendrikus Diek
authors: HD
authors: Duifhuis
mesh_terms: D000162:Acoustics / Q000295:instrumentation*; D016477:Artifacts; D003198:Computer Simulation; D004867:Equipment Design; D019544:Equipment Failure Analysis; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000295:instrumentation* / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity