Literature DB >> 19095847

Electrical noise in the intraoperative magnetic resonance imaging setting.

Roger Dzwonczyk1, Jeffrey T Fujii, Orlando Simonetti, Ricardo Nieves-Ramos, Sergio D Bergese.   

Abstract

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.

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Year:  2009        PMID: 19095847      PMCID: PMC5166575          DOI: 10.1213/ane.0b013e31818f8777

Source DB:  PubMed          Journal:  Anesth Analg        ISSN: 0003-2999            Impact factor:   5.108


  3 in total

1.  Minimizing interference from magnetic resonance imagers during electrocardiography.

Authors:  M K Laudon; J G Webster; R Frayne; T M Grist
Journal:  IEEE Trans Biomed Eng       Date:  1998-02       Impact factor: 4.538

2.  MRI acoustic noise: sound pressure and frequency analysis.

Authors:  S A Counter; A Olofsson; H F Grahn; E Borg
Journal:  J Magn Reson Imaging       Date:  1997 May-Jun       Impact factor: 4.813

3.  Acoustic analysis of gradient-coil noise in MR imaging.

Authors:  R Hurwitz; S R Lane; R A Bell; M N Brant-Zawadzki
Journal:  Radiology       Date:  1989-11       Impact factor: 11.105

  3 in total
  4 in total

1.  Intraoperative MRI electrical noise and monitor ECG filters affect arrhythmia detection and identification.

Authors:  Melissa Bailey; Gwynne Kirchen; Bridget Bonaventura; Kelly Rosborough; Mahmoud Abdel-Rasoul; Roger Dzwonczyk
Journal:  J Clin Monit Comput       Date:  2012-03-03       Impact factor: 2.502

2.  Anesthetic challenges and outcomes for procedures in the intraoperative magnetic resonance imaging suite: A systematic review.

Authors:  Hedwig Schroeck; Tasha L Welch; Michelle S Rovner; Heather A Johnson; Florian R Schroeck
Journal:  J Clin Anesth       Date:  2018-11-08       Impact factor: 9.452

3.  Mesoscopic physiological interactions in the human brain reveal small-world properties.

Authors:  Jiarui Wang; Annabelle Tao; William S Anderson; Joseph R Madsen; Gabriel Kreiman
Journal:  Cell Rep       Date:  2021-08-24       Impact factor: 9.995

Review 4.  Physiological recordings: basic concepts and implementation during functional magnetic resonance imaging.

Authors:  Marcus A Gray; Ludovico Minati; Neil A Harrison; Peter J Gianaros; Vitaly Napadow; Hugo D Critchley
Journal:  Neuroimage       Date:  2009-05-19       Impact factor: 6.556

  4 in total

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