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Journal of Cardiovascular Magnetic Resonance

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Open AcceOral presentation12-lead ECG in a 1.5 Tesla MRI: Separation of real ECG and MHD voltages with adaptive filtering for gating and non-invasive cardiac outputZion Tsz Ho Tse*1, Charles L Dumoulin2, Gari Clifford3, Michael Jerosch-Herold1, Daniel Kacher1, Raymond Kwong4, William Gregory Stevenson4 and Ehud Jeruham Schmidt1

Address: 1Radiology, Brigham and Women's Hospital, Boston, MA, USA, 2University of Cincinnati College of Medicine, Cincinnati, OH, USA, 3Health Sciences and Techology, Massachusetts Institute of Technology, Boston, MA, USA and 4Cardiology, Brigham and Women's Hospital, Boston, MA, USA

* Corresponding author

IntroductionThe Magneto-Hydro-Dynamic (MHD) effect arises whenconductive blood flows in the MRI magnetic field (B0).MHD generates a voltage which distorts the real electro-cardiogram (ECGreal), especially during the S-T segmentwhere flow from the left ventricle (LV) into the aorta con-tributes to a large MHD voltage [1]. A dominant QRS andundistorted S-T segment are important for MRI gating andphysiological monitoring for ischemia during cardiacimaging/interventions [2].

PurposeWe hypothesized that adaptive filtering could separatebetween MHD and ECGreal, and that the MHD signalcould non-invasively estimate cardiac output.

MethodsMRI-compatible 12-lead ECGs were acquired with a mod-ified ECG-recording system [3] from three healthy volun-teers and one patient with idiopathic outflow tractPremature Ventricle Contractions (PVCs) (Ejection Frac-tion 20-25%, LV wall thickening, mitral regurgitation).Three sets of 20-sec breath-held ECGs (Fig. 1), were meas-ured in a 1.5 scanner with subjects placed (i) outside thescanner with their head-in (ECG = ECGreal), (ii) at iso-cen-

tre with their head-in (ECG = ECGreal+MHDhead-in), and(iii) at iso-centre with their feet-in (ECG = ECGreal+MHD-

feet-in), which reverses B0 polarity (MHDfeet-in~-1 × MHD-

head-in). Data processing (Fig. 2) involved application of anadaptive Least-Mean-Square filter to (ii) and (iii), whilst(i) was used to train the filter to decouple the MHD signalfrom ECGreal.

ResultsFig. 3(a-d) show processing of the patient's V6 ECGs inpositions (ii) and (iii). MHD signals are effectively

from 13th Annual SCMR Scientific SessionsPhoenix, AZ, USA. 21-24 January 2010

Published: 21 January 2010

Journal of Cardiovascular Magnetic Resonance 2010, 12(Suppl 1):O95 doi:10.1186/1532-429X-12-S1-O95

Abstracts of the 13th Annual SCMR Scientific Sessions - 2010

Meeting abstracts - A single PDF containing all abstracts in this Supplement is available here. http://www.biomedcentral.com/content/files/pdf/1532-429X-11-S1-info

This abstract is available from: http://jcmr-online.com/content/12/S1/O95

© 2010 Tse et al; licensee BioMed Central Ltd.

Unprocessed PVC patient ECGsFigure 1Unprocessed PVC patient ECGs.

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Adaptive filtering procedureFigure 2Adaptive filtering procedure.

(a-h) PVC patient ECGs at iso-centreFigure 3(a-h) PVC patient ECGs at iso-centre. (i) Cardiac outputs of healthy volunteers versus the patient.

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removed in Fig. 3(c-d), showing ECGreal with the S-T seg-

Journal of Cardiovascular Magnetic Resonance 2010, 12(Suppl 1):O95 http://jcmr-online.com/content/12/S1/O95

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ment preserved. The MHD signals, Fig. 3(e-f), are maxi-mal during the S-T segment. Oscillating positive andnegative MHD voltages during systole in each PVC cyclecan be explained by flow eddies, consistent with thepatient's mitral regurgitation. Fig. 3(g-h) show the cardiacoutput, calculated from the systolic time-integrated MHD.Cardiac output during PVC cycles is much smaller thanduring normal beats. Fig. 3(i) indicates that the PVCpatient's average cardiac output is 44-54% of the healthyvolunteers', due to less effective PVC beats.

ConclusionThe filtering procedure separates the ECGreal and MHDsignals in 12-lead ECGs acquired within the MRI. The QRScomplex becomes dominant, as required for good MRIgating, while preserving S-T segment fidelity for physio-logical monitoring during imaging/interventions. MHDsignals allow for non-invasive monitoring of beat-to-beatcardiac output.

References1. Gupta : IEEE Trans BioMed Eng 2008.2. Haberl : ECG pocket, Borm Bruckmeier Publishing; 2006. 3. Dukkipati : Circulation 2008.

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IntroductionPurposeMethodsResultsConclusionReferences