Volume 18 Supplement 1

19th Annual SCMR Scientific Sessions

Open Access

Intra-MRI extraction of diagnostic electrocardiograms using dynamic feedback from carotidal magnetohydrodynamic voltages

  • Thomas S Gregory1,
  • Kevin J Wu1,
  • Ehud J Schmidt2,
  • John Oshinski3 and
  • Zion T Tse1
Journal of Cardiovascular Magnetic Resonance201618(Suppl 1):P214


Published: 27 January 2016


During Cardiac Magnetic Resonance Imaging (CMR), blood plasma electrolytes ejected into the aorta during early systole interact with the static magnetic field of the MR scanner (B0) to produce a Magnetohydrodynamic (MHD) Effect [1]. Electrocardiograms (ECGs) recorded in the presence of B0 are overlaid with induced MHD voltages (VMHD), leading to non-robustly synchronized imaging [2], and preventing reliable physiological monitoring inside the MRI [3]. Previous methods have sought to separate between VMHD and the true ECG (ECGreal) through adaptive filtering [3], independent component analysis [4], and advanced computational models [5]. However, these methods are based on a static model, which has limited accuracy during varying-rate heart-beats. We aim to develop accurate ECGreal extraction, as well as real-time Stroke Volume (SV) estimation (proportional to the integral of MHD over systole) [6], with the advantage of physiological feedback through the real-time monitoring of common carotidal MHD, through which the previously static MHD template can be dynamically updated, providing an increased level of accuracy during variations in heart rate, and a continuous estimation of VMHD and ECGreal, for the patient's entire duration inside the MRI.


12-lead ECGs were acquired in two (n = 2) healthy volunteers during 20-second breath-holds in a 3T MRI (Figure 1ab) with the heart at isocenter. A secondary monitor was used to acquire a single anterior-posterior bipolar lead placed approximately on the left common carotid artery (Figure 1c). ECGs were acquired inside (ECGreal + VMHD) and outside (ECGreal) the MRI bore during an initial phase in which a static MHD template was extracted, based on lead subtraction. Carotidal MHD was extracted from the single bipolar lead and phase-compensated to match VMHD obtained from the 12-lead ECG. Carotid MHD was subsequently used to adaptively train a Least Mean Squares filter (Figure 1d) to update the MHD template and produce: (1) clean 12-lead ECGs; and (2) an accurate SV estimate [6] (Figure 1e).
Figure 1

Active removal of induced Magnetohydrodynamic voltages in ECGs recorded inside a 3T MRI using adaptive filtering.


The adaptive filtering method was shown to reduce VMHD in the acquired 12-lead ECGs, with residual noise forming <5% of the R-wave amplitude. The method preserved the true S-T segment, while requiring only a short training phase for the 12-lead ECG (10-15 seconds). The Pearson's Correlation Coefficient between Aortic and Carotid MHD increased from 0.51 to 0.88 after the adaptive filtering routine was applied. Figure 1f shows the extracted 12-lead ECG acquired inside the MRI bore after the training phase.


A method to extract true sinus rhythm beats from intra-MRI 12-lead ECGs was presented and shown to provide accurate dynamic measurements of induced VMHD using Carotid artery MHD and ECGreal to allow for advanced physiological monitoring inside the MRI.

Authors’ Affiliations

College of Engineering, University of Georgia
Radiology, Brigham and Women's Hospital
Radiology, Emory University Hospital


  1. Gupta : IEEE Trans BioMed Eng. 2008Google Scholar
  2. Gregory : MRM. 2014Google Scholar
  3. Tse : MRM. 2013Google Scholar
  4. Krug : Comp Card. 2012Google Scholar
  5. Oster : Comp Method Biomed. 2014Google Scholar
  6. Gregory : JCMR. 2015Google Scholar


© Gregory et al. 2016

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.