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Adaptive step size LMS improves ECG detection during MRI at 1.5 and 3 T

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Magnetic Resonance Materials in Physics, Biology and Medicine Aims and scope Submit manuscript

Abstract

Objective

We describe a new real-time filter to reduce artefacts on electrocardiogram (ECG) due to magnetic field gradients during MRI. The proposed filter is a least mean square (LMS) filter able to continuously adapt its step size according to the gradient signal of the ongoing MRI acquisition.

Materials and methods

We implemented this filter and compared it, within two databases (at 1.5 and 3 T) with over 6000 QRS complexes, to five real-time filtering strategies (no filter, low pass filter, standard LMS, and two other filters optimized within the databases: optimized LMS, and optimized Kalman filter).

Results

The energy of the remaining noise was significantly reduced (26 vs. 68%, p < 0.001) with the new filter vs. standard LMS. The detection error of our ventricular complex (QRS) detector was: 11% with our method vs. 25% with raw ECG, 35% with low pass filter, 17% with standard LMS, 12% with optimized Kalman filter, and 11% with optimized LMS filter.

Conclusion

The adaptive step size LMS improves ECG denoising during MRI. QRS detection has the same F1 score with this filter than with filters optimized within the database.

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Acknowledgements

Julien Oster contributed to this paper as scientific advisor. Several authors were employed by Schiller SA when this study was designed and conducted.

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Authors and Affiliations

  1. Schiller SA, 4 rue Pasteur, 67160, Wissembourg, France

    André Guillou, Sarah Ménétré & Grégory Petitmangin

  2. INSERM, U947, rue du Morvan, 54511, Vandoeuvre-les-Nancy, France

    André Guillou, Jean-Marc Sellal, Jacques Felblinger & Laurent Bonnemains

  3. Department of Cardiology, CHU Nancy, rue du Morvan, 54511, Vandoeuvre-les-Nancy, France

    Jean-Marc Sellal

  4. CHU Nancy, CIC-IT 801, rue du Morvan, 54511, Vandoeuvre-les-Nancy, France

    Jacques Felblinger

  5. Department of Medical Imaging, CHU Nancy, rue du Morvan, 54511, Vandoeuvre-les-Nancy, France

    Jacques Felblinger

  6. Department of Cardiac surgery, CHU Strasbourg, 1 rue de l’hopital, 67000, Strasbourg, France

    Laurent Bonnemains

  7. University of Strasbourg, 4 rue Kirshleger, 67000, Strasbourg, France

    Laurent Bonnemains

Authors
  1. André Guillou
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  2. Jean-Marc Sellal
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  3. Sarah Ménétré
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  4. Grégory Petitmangin
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  5. Jacques Felblinger
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  6. Laurent Bonnemains
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Corresponding author

Correspondence to Laurent Bonnemains.

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Conflict of interest

Three authors André Guillou, Sarah Ménétré and Grégory Petitmangin are employed by Schiller Medicals, Wissembourg, France and declare this financial link as a potential conflict of interest because the algorithm presented in the manuscript is actually implemented in two schiller commercial devices. The authors Jean-Marc Sellal, Jacques Felblinger and Laurent Bonnemains declare that they have no conflict of interest.

Ethical approval

The study complied with the Declaration of Helsinki regarding medical research on human subjects and was approved by a local ethics committee.

Informed consent

All subjects included in the study gave their informed written consent.

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Guillou, A., Sellal, JM., Ménétré, S. et al. Adaptive step size LMS improves ECG detection during MRI at 1.5 and 3 T. Magn Reson Mater Phy 30, 567–577 (2017). https://doi.org/10.1007/s10334-017-0638-8

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  • DOI: https://doi.org/10.1007/s10334-017-0638-8

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