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TECHNOLOGY, COMPUTING, AND SIMULATION

Electrical Noise in the Intraoperative Magnetic Resonance Imaging Setting

Roger Dzwonczyk, MSBME^*, Jeffrey T. Fujii, BS^*, Orlando Simonetti, PhD, Ricardo Nieves-Ramos, MD^*, and Sergio D. Bergese, MD^*

From the Departments of *Anesthesiology, and Cardiovascular Medicine, The Ohio State University, Columbus, Ohio.

Address correspondence and reprint requests to Roger Dzwonczyk, MSBME, The Ohio State University, 410 West 10th Ave., Columbus, OH 43214. Address e-mail to dzwonczyk.1{at}osu.edu.

BACKGROUND: Intraoperative magnetic resonance imaging (iMRI) is a tool now commonly used in neurosurgery. Safe and reliable patient care in this (or any other) operating room setting depends on an environment, where electrical noise (EN) does not interfere with the operation of the electronic monitoring or imaging equipment. In this investigation, we evaluated the EN generated by the iMRI system and the anesthesia patient monitor used at this institution that impacts the performance of these two devices.

METHODS: We measured the EN generated by our iMRI-compatible anesthesia patient monitor as detected by the EN analysis algorithm in our iMRI system. We measured the EN generated by our iMRI system during scanning as detected in the electrocardiogram (ECG) waveform of our patient monitor. We analyzed the effects on EN reduction and signal quality of the ECG noise filters provided in our iMRI-compatible anesthesia patient monitor.

RESULTS: Our patient monitor generated EN that was detectable by the iMRI EN analysis algorithm; however, this interference was within the iMRI manufacturer’s acceptable limits for an iMRI scan (<10% more than background system-level noise). In the clinical case analyzed, the iMRI generated a narrow-band low-frequency (20 Hz) relatively high-energy EN that interfered with the ECG signal of our patient monitor during an iMRI scan. This EN was correlated with the acoustic noise from the iMRI system during the scan and was associated with the radio frequency (RF) and magnetic gradient pulsations of the iMRI system. The integrity of the ECG waveform was nearly entirely lost during a scan. The filters of the ECG monitor diminished but did not entirely eliminate this 20 Hz interference. We found that the filters alter the morphology of the ECG signal, which may make it difficult to identify clinically relevant ECG changes.

CONCLUSION: The EN generated by our anesthesia patient monitor is within acceptable limits for the iMRI system. The iMRI generates EN which renders the ECG unreadable in the most commonly used filter mode. The monitor’s filters diminish this noise but also alter the morphology of the ECG waveform. The anesthesiologist must be cognizant of these technical compromises and recognize that adjusting the ECG filters on the monitor is required to obtain a useful ECG signal for patient monitoring during the iMRI scan but that the diagnostic value of the ECG will be reduced.