MRI Recording Physiology Data | Recommended Readings

BIOPAC offers a series of magnetic resonance imaging compatible electrodes, electrode leads, transducers, and stimulus options for safe data acquisition of physiological signals in the MRI environment. Specialized cable systems provide isolated and RF filtered interfacing between the subject/chamber panel and the control room. These selected readings provide safety and recording information to consider in addition to specific hardware setup and use notes.

MRI Recommended Readings (PDF)

  • Safety Guidelines: Recording Biopotential Measurements in the MRI Environment—MRI Smart Amplifiers
  • CalTech Notes – SCR Recording During fMRI Acquisition
    Antoine Bruguier, R. McKell Carter, Christof Koch and Steven Quartz.
    Abstract: Investigative methods in neuroscience increasingly combine functional magnetic resonance imaging (fMRI) with other
    measurement and stimulus-delivery systems. Many of these, such as electroencephalography (EEG),
    electrocardiography (ECG) and skin conductance response (SCR) measurements, attach electrodes to subjects inside
    the strong variable magnetic field of the scanner. This may induce dangerous voltages on the leads that often go
    unassessed. While burn injuries and electric shocks have been reported, there is surprisingly little available research
    describing these risks. This paper presents a simple model of the human body and a filtering system that aims to
    assess these burn risks and prevent electrical shocks. The electrical properties of this setup and the induced voltages
    on the leads as measured in a variety of configurations, including the effect of fMRI transmitting and receiving coils and
    lead composition, are presented. Since these combined methods introduce noise that requires additional filtering, we
    also studied the safety constraints of various filters. Even though the design methods and measurements are applied to
    a skin-conductance/shock delivery setup, they can be generalized to other systems for assessing and preventing risks
    associated with similar combined methods.
  • Safety Awareness Notes when using Cables and Electrodes during MRI
    Susan Lange, Arrt, MPH, and Quynh Nhu Nguyen, BS, Nursing 2006, Volume 36, Number 11, P. 18
    Excerpt: The radiofrequency fields that occur during an MRI can heat ECG cables and electrodes, seriously burning skin
    under the electrodes, so the following precautions should be considered for any MRI research protocols.
  • Neuropsychophysiological mapping: Concurrent psychophysiological recording and fMRI at 7T
    Jennifer L. Robinson, Ph.D., Matthew Miller, Ph.D., Keith Lohse, Ph.D., Ronald Beyers, Ph.D., Kirk Grand, Lauren A. J. Kirby,
    Ashley C. Hill, Jerry E. Murphy, Alan Macy, M.S.E.E., Ken Graap, M.Ed.
    Presented at: Organization for Human Brain Mapping (OHBM) Annual Meeting 2015 (E-paper)
    Overview: The presentation reviews data acquired using BIOPAC MR-compatible modules, leads, and electrodes during
    simultaneous ultra-high field, high-resolution functional neuroimaging; fMRI scanning was carried out on a whole body
    7T Siemens MAGNETOM scanner, outfitted with a 32-channel Nova Medical head coil. The poster clearly explains
    setup and shows neural correlates paired with ECG, EMG, EDA, and Grip, with results of EMG, EDA, and basic
    cardiovascular measures derived after signal processing to remove scanning artifacts. BIOPAC hardware included
    Electrocardiograph (ECG): ECG100C-MRI Smart Amplifier with EL509 electrodes, LEAD108, and GEL100;
    Electromyograph (EMG): EMG100C-MRI Smart Amplifier; Respiration: RSP100C Amplifier with TSD201 respiratory
    effort transducer; Electrodermal activity (EDA): EDA100C-MRI Smart Amplifier with EL509 electrodes, LEAD108, and
    isotonic GEL101.
  • ICG & ECG in MRI
    • Quantifying rapid changes in cardiovascular state with a moving ensemble average
      Cieslak M, Ryan WS, Babenko V, Erro H, Rathbun ZM, Meiring W, Kelsey RM, Blascovich J, Grafton ST.
      Psychophysiology. 2018 Apr;55(4). doi: 10.1111/psyp.13018. Epub 2017 Oct 3.
      Abstract: MEAP, the moving ensemble analysis pipeline, is a new open‐source tool designed to perform multisubject
      preprocessing and analysis of cardiovascular data, including electrocardiogram (ECG), impedance cardiogram
      (ICG), and continuous blood pressure (BP). In addition to traditional ensemble averaging, MEAP implements a
      moving ensemble averaging method that allows for the continuous estimation of indices related to cardiovascular
      state, including cardiac output, pre-ejection period, heart rate variability, and total peripheral resistance, among
      others. Here, we define the moving ensemble technique mathematically, highlighting its differences from
      fixed‐window ensemble averaging. We describe MEAP’s interface and features for signal processing, artifact
      correction, and cardiovascular‐based fMRI analysis. We demonstrate the accuracy of MEAP’s novel B point
      detection algorithm on a large collection of hand‐labeled ICG waveforms. As a proof of concept, two subjects
      completed a series of four physical and cognitive tasks (cold pressor, Valsalva maneuver, video game, random
      dot kinetogram) on 3 separate days while ECG, ICG, and BP were recorded. Critically, the moving ensemble
      method reliably captures the rapid cyclical cardiovascular changes related to the baroreflex during the Valsalva
      maneuver and the classic cold pressor response. Cardiovascular measures were seen to vary considerably
      within repetitions of the same cognitive task for each individual, suggesting that a carefully designed paradigm
      could be used to capture fast‐acting event‐related changes in cardiovascular state.
    • Dynamics of the central and autonomic nervous systems preceding action and cognition
      Matthew J. Cieslak, dissertation, Psychological & Brain Sciences, University of California Santa Barbara, June 2016
      www.biopac.com Recommended Reading: MRI—Recording Physiology Data info@biopac.com
      Excerpt: …changes in systolic time intervals, cardiac output and vascular resistivity are regularly used as cardiovascular
      indexes of the psychological processes occurring during motivated and stressful tasks. Moving ensemble
      analysis, a new method for characterizing these indexes, is introduced here. Its major innovation is the ability to
      detect both state and change of cardiovascular indexes during individual experimental trials. This technique is
      robust to radio frequency and magnetic field artifact present in an MRI environment (chapter 6) as well as
      respiratory and movement-related artifact normally present in noninvasive recordings.
  • Electrocardiogram in an MRI Environment: Clinical Needs, Practical Considerations, Safety Implications,
    Technical Solutions and Future Directions
    Thoralf Niendorf, Lukas Winter and Tobias Frauenrath (2012). Advances in Electrocardiograms – Methods and Analysis, PhD.
    Richard Millis (Ed.), ISBN: 978-953-307-923-3, InTech, DOI: 10.5772/24340.
    Excerpt: ECG waveform acquisitions, ECG co-registration and ECG monitoring during MRI pose technical challenges and
    requires safety measures that will not be familiar to users of other conventional ECG technologies. For all those
    reasons, the basic principles of using ECG in an MRI environment and their implications for clinical MRI and MRI
    research are provided in this chapter. Key concepts, technical solutions, practical considerations and safety implications
    for cardiac gated MRI using electrocardiograms are outlined.
  • Magnetohydrodynamic distortions of the ECG in different MR scanner configurations
    Johannes Krug, Georg Rose, Chair for Healthcare Telematics and Medical Engineering, University of Magdeburg, Germany
    Abstract: Diagnostic electrocardiograms (ECG) are required to ensure patient safety during minimal invasive interventions and
    cardiac stress testings. The ECG is corrupted by several other signals when performing these interventions under
    magnetic resonance (MR) guidance which makes it impossible to use the ECG as a diagnostic tool in MR guided
    interventions. The interfering signal that is caused by the static magnetic field of the MR scanner – namely due to the
    magnetohydrodynamic (MHD) effect – is investigated within this work. The MHD effect is measured regarding different
    aspects like the strength and orientation of the static magnetic field as well as the patient’s position and heart rate.
  • Magnetic Field Threshold for Accurate Electrocardiography in the MRI Environment
    Mihaela Jekic,Yu Ding, Roger Dzwonczyk, Patrick Burns, Subha V. Raman, and Orlando P. Simonetti, Magn Reson Med.
    2010 December ; 64(6): 1586–1591. doi:10.1002/mrm.22419.
    Abstract: Although the electrocardiogram is known to be nondiagnostic within the bore of any high-field magnet due to the
    magnetohydrodynamic effect, there are an increasing number of applications that require accurate electrocardiogram
    monitoring of a patient inside the MRI room but outside of the magnet bore. Magnetohydrodynamic effects on the ST
    segment of the electrocardiogram waveform were investigated in six subjects at magnetic field strengths ranging from
    6.4 mT to 652 mT at the aortic midarch, and the electrocardiogram was found to be accurate at magnetic fields below
    70 mT. This corresponds to a distance of 160 cm from the isocenter and 80 cm from the bore entrance for the 1.5-T
    MRI system used in this study. These results can be translated to any MRI system, with knowledge of the fringe field.
    Accurate electrocardiogram monitoring is feasible in close proximity to the MRI magnet, such as during and after
    pharmacologic or exercise stress, or interventional or surgical procedures performed in the MRI room.
  • Integration of motion correction and physiological noise regression in fMRI
    Tyler B. Jones, Peter A. Bandettini, and Rasmus M. Birn
    Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, MD, USA
    Abstract: Physiological fluctuations resulting from the heartbeat and respiration are a dominant source of noise in fMRI,
    particularly at high field strengths. Commonly used physiological noise correction techniques, such as RETROspective
    Image CORection (RETROICOR), rely critically on the timing of the image acquisition relative to the heartbeat, but do
    not account for the effects of subject motion. Such motion affects the fluctuation amplitude, yet volume registration can
    distort the timing information. In this study, we aimed to systematically determine the optimal order of volume
    registration, slice-time correction and RETROICOR in their traditional forms. In addition, we evaluate the sensitivity of
    RETROICOR to timing errors introduced by the slice acquisition, and we develop a new method of accounting for timing
    errors introduced by volume registration into physiological correction (motion-modified RETROICOR). Both simulation
    and resting data indicate that the temporal standard deviation is reduced most by performing volume registration before
    RETROICOR and slice-time correction after RETROCIOR. While simulations indicate that physiological noise
    correction with regressors constructed on a slice-by-slice basis more accurately modeled physiological noise compared
    to using the same regressors for the entire volume, the difference between these regression techniques in subject data
    was minimal. The motion-modified RETROICOR showed marked improvement in simulations with varying amounts of
    subject motion, reducing the temporal standard deviation by up to 36% over the traditional RETROICOR. Though to a
    lesser degree than in simulation, the motion-modified RETROICOR performed better in nearly every voxel in the brain
    in both high- and low-resolution subject data.
  • Detection of facial mimicry by electromyography during fMRI scanning
    Gustav Nilsonne, Sandra Tamm, Paolo d’Onofrio, Johanna Schwarz, Göran Kecklund, Mats Lekander, Torbjörn Åkerstedt,
    Håkan Fischer
    Presented at: 19th Annual Meeting of the Organization for Human Brain Mapping (OHBM) 2013, 16 – 20 Jun 2013, 3203
    Background / Purpose: We investigated whether electromyography (EMG) could be used to detect facial mimicry during
    fMRI scanning.
    Main conclusion: EMG activity in the superciliary corrugator muscle increased when participants viewed angry faces.
  • Simultaneous acquisition of corrugator electromyography and functional magnetic resonance imaging: A new method for objectively measuring affect and neural activity concurrently
    Aaron S. Heller, Lawrence L Greischar, Ann Honor, Michael J Anderle, and Richard J. Davidson
    Abstract: The development of functional neuroimaging of emotion holds the promise to enhance our understanding of the
    biological bases of affect and improve our knowledge of psychiatric diseases. However, up to this point, researchers
    have been unable to objectively, continuously and unobtrusively measure the intensity and dynamics of affect
    concurrently with functional magnetic resonance imaging (fMRI). This has hindered the development and
    generalizability of our field. Facial electromyography (EMG) is an objective, reliable, valid, sensitive, and unobtrusive
    measure of emotion. Here, we report the successful development of a method for simultaneously acquiring fMRI and
    facial EMG. The ability to simultaneously acquire brain activity and facial physiology will allow affective neuroscientists
    to address theoretical, psychiatric, and individual difference questions in a more rigorous and generalizable.

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