OBJECTIVE: To develop a quantitative set of methods for testing the functional magnetic resonance imaging (fMRI) compatibility of an electrically-active mechatronic device developed to support sensorimotor protocols during fMRI. METHODS: The set of methods includes phantom and in vivo experiments to measure the effect of a progressively broader set of noise sources potentially introduced by the device. Phantom experiments measure the radio-frequency (RF) noise and temporal noise-to-signal ratio (tNSR) introduced by the device. The in vivo experiment assesses the effect of the device on measured brain activation for a human subject performing a representative sensorimotor task. The proposed protocol was validated via experiments using a 3T MRI scanner operated under nominal conditions and with the inclusion of an electrically-active mechatronic device - the MR-SoftWrist - as the equipment under test (EUT). RESULTS: Quantitative analysis of RF noise data allows detection of active RF noise sources both in controlled RF noise conditions, and in conditions resembling improper filtering of the EUT's electrical signals. In conditions where no RF noise was detectable, the presence and operation of the EUT did not introduce any significant increase in tNSR. A quantitative analysis conducted on in vivo measurements of the number of active voxels in visual and motor areas further showed no significant difference between EUT and baseline conditions. CONCLUSION AND SIGNIFICANCE: The proposed set of quantitative methods supports the development and troubleshooting of electrically-active mechatronic devices for use in sensorimotor protocols with fMRI, and may be used for future testing of such devices.
OBJECTIVE: To develop a quantitative set of methods for testing the functional magnetic resonance imaging (fMRI) compatibility of an electrically-active mechatronic device developed to support sensorimotor protocols during fMRI. METHODS: The set of methods includes phantom and in vivo experiments to measure the effect of a progressively broader set of noise sources potentially introduced by the device. Phantom experiments measure the radio-frequency (RF) noise and temporal noise-to-signal ratio (tNSR) introduced by the device. The in vivo experiment assesses the effect of the device on measured brain activation for a human subject performing a representative sensorimotor task. The proposed protocol was validated via experiments using a 3T MRI scanner operated under nominal conditions and with the inclusion of an electrically-active mechatronic device - the MR-SoftWrist - as the equipment under test (EUT). RESULTS: Quantitative analysis of RF noise data allows detection of active RF noise sources both in controlled RF noise conditions, and in conditions resembling improper filtering of the EUT's electrical signals. In conditions where no RF noise was detectable, the presence and operation of the EUT did not introduce any significant increase in tNSR. A quantitative analysis conducted on in vivo measurements of the number of active voxels in visual and motor areas further showed no significant difference between EUT and baseline conditions. CONCLUSION AND SIGNIFICANCE: The proposed set of quantitative methods supports the development and troubleshooting of electrically-active mechatronic devices for use in sensorimotor protocols with fMRI, and may be used for future testing of such devices.