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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Improved ECG based gating in ultra high field cardiac MRI using an independent component analysis approach</title><author><name sortKey="Krug, Jw" sort="Krug, Jw" uniqKey="Krug J" first="Jw" last="Krug">Jw Krug</name><affiliation><nlm:aff id="I1">Chair for Healthcare Telematics and Medical Engineering, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany</nlm:aff></affiliation></author><author><name sortKey="Rose, G" sort="Rose, G" uniqKey="Rose G" first="G" last="Rose">G. Rose</name><affiliation><nlm:aff id="I1">Chair for Healthcare Telematics and Medical Engineering, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany</nlm:aff></affiliation></author><author><name sortKey="Clifford, G" sort="Clifford, G" uniqKey="Clifford G" first="G" last="Clifford">G. Clifford</name><affiliation><nlm:aff id="I2">Department of Engineering Science, University of Oxford, Oxford, UK</nlm:aff></affiliation></author><author><name sortKey="Oster, J" sort="Oster, J" uniqKey="Oster J" first="J" last="Oster">J. Oster</name><affiliation><nlm:aff id="I2">Department of Engineering Science, University of Oxford, Oxford, UK</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmc">3560069</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3560069</idno><idno type="RBID">PMC:3560069</idno><idno type="doi">10.1186/1532-429X-15-S1-W33</idno><idno type="pmid">NONE</idno><date when="2013">2013</date><idno type="wicri:Area/Pmc/Corpus">000352</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000352</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Improved ECG based gating in ultra high field cardiac MRI using an independent component analysis approach</title><author><name sortKey="Krug, Jw" sort="Krug, Jw" uniqKey="Krug J" first="Jw" last="Krug">Jw Krug</name><affiliation><nlm:aff id="I1">Chair for Healthcare Telematics and Medical Engineering, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany</nlm:aff></affiliation></author><author><name sortKey="Rose, G" sort="Rose, G" uniqKey="Rose G" first="G" last="Rose">G. Rose</name><affiliation><nlm:aff id="I1">Chair for Healthcare Telematics and Medical Engineering, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany</nlm:aff></affiliation></author><author><name sortKey="Clifford, G" sort="Clifford, G" uniqKey="Clifford G" first="G" last="Clifford">G. Clifford</name><affiliation><nlm:aff id="I2">Department of Engineering Science, University of Oxford, Oxford, UK</nlm:aff></affiliation></author><author><name sortKey="Oster, J" sort="Oster, J" uniqKey="Oster J" first="J" last="Oster">J. Oster</name><affiliation><nlm:aff id="I2">Department of Engineering Science, University of Oxford, Oxford, UK</nlm:aff></affiliation></author></analytic><series><title level="j">Journal of Cardiovascular Magnetic Resonance</title><idno type="ISSN">1097-6647</idno><idno type="eISSN">1532-429X</idno><imprint><date when="2013">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Lamb" uniqKey="Lamb">Lamb</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Fischer" uniqKey="Fischer">Fischer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Hyvarinen" uniqKey="Hyvarinen">Hyvarinen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Pan" uniqKey="Pan">Pan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Tse" uniqKey="Tse">Tse</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article" xml:lang="en"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Cardiovasc Magn Reson</journal-id><journal-id journal-id-type="iso-abbrev">J Cardiovasc Magn Reson</journal-id><journal-title-group><journal-title>Journal of Cardiovascular Magnetic Resonance</journal-title></journal-title-group><issn pub-type="ppub">1097-6647</issn><issn pub-type="epub">1532-429X</issn><publisher><publisher-name>BioMed Central</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmc">3560069</article-id><article-id pub-id-type="publisher-id">1532-429X-15-S1-W33</article-id><article-id pub-id-type="doi">10.1186/1532-429X-15-S1-W33</article-id><article-categories><subj-group subj-group-type="heading"><subject>Workshop Presentation</subject></subj-group></article-categories><title-group><article-title>Improved ECG based gating in ultra high field cardiac MRI using an independent component analysis approach</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Krug</surname><given-names>JW</given-names></name><xref ref-type="aff" rid="I1">1</xref></contrib><contrib contrib-type="author" id="A2"><name><surname>Rose</surname><given-names>G</given-names></name><xref ref-type="aff" rid="I1">1</xref></contrib><contrib contrib-type="author" id="A3"><name><surname>Clifford</surname><given-names>G</given-names></name><xref ref-type="aff" rid="I2">2</xref></contrib><contrib contrib-type="author" id="A4"><name><surname>Oster</surname><given-names>J</given-names></name><xref ref-type="aff" rid="I2">2</xref></contrib></contrib-group><aff id="I1"><label>1</label>Chair for Healthcare Telematics and Medical Engineering, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany</aff><aff id="I2"><label>2</label>Department of Engineering Science, University of Oxford, Oxford, UK</aff><pub-date pub-type="collection"><year>2013</year></pub-date><pub-date pub-type="epub"><day>30</day><month>1</month><year>2013</year></pub-date><volume>15</volume><issue>Suppl 1</issue><supplement><named-content content-type="supplement-title">Abstracts of the 16th Annual SCMR Scientific Sessions</named-content><named-content content-type="supplement-sponsor">Publication of this supplement is fully supported by the Society for Cardiovascular Magnetic Resonance.</named-content></supplement><fpage>W33</fpage><lpage>W33</lpage><permissions><copyright-statement>Copyright ©2013 Krug et al; licensee BioMed Central Ltd.</copyright-statement><copyright-year>2013</copyright-year><copyright-holder>Krug et al; licensee BioMed Central Ltd.</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0">http://creativecommons.org/licenses/by/2.0</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><self-uri xlink:href="http://www.jcmr-online.com/content/15/S1/W33"></self-uri><conference><conf-date>31 January-3 February 2013</conf-date><conf-name>16th Annual SCMR Scientific Sessions</conf-name><conf-loc>San Francisco, CA, USA</conf-loc></conference></article-meta></front><body><sec><title>Background</title><p>Cardiac gating in ultra high field (UHF) MRI is a challenging task due to the magnetohydrodynamic (MHD) effect [<xref ref-type="bibr" rid="B1">1</xref>]. The MHD effect is particularly severe at such field strengths and severely distorts the electrocardiogram (ECG). State-of-the-art ECG based gating methods which use the vectorcardiogram (VCG) [<xref ref-type="bibr" rid="B2">2</xref>] are thus prone to errors [<xref ref-type="bibr" rid="B1">1</xref>]. This work presents an approach which separates the ECG and the MHD signal using Independent Component Analysis (ICA).</p></sec><sec sec-type="methods"><title>Methods</title><p>ECGs were recorded inside a 7T MR scanner (Siemens Magnetom) using a standard 12-lead Holter ECG (Getemed, Germany). Ten data sets were acquired by measuring the ECGs from five healthy volunteers in a head first and feet first position without MR imaging. Each measurement was between 4-5min long, so a total of 2766 QRS complexes were available for analysis. Examples are given in Fig. <xref ref-type="fig" rid="F1">1(a)-(c)</xref>. A FastICA algorithm was applied to the ECG signals in order to separate the ECG and MHD signals [<xref ref-type="bibr" rid="B3">3</xref>]. The independent component (IC) which minimizes the MHD contribution was identified using an automatic approach based on a kurtosis measurement. A QRS detection algorithm was applied to the identified IC [<xref ref-type="bibr" rid="B4">4</xref>]. The proposed method was compared with the VCG technique [<xref ref-type="bibr" rid="B2">2</xref>]. Quality was assessed in terms of sensitivity (Se) and positive prediction value (+P) of the QRS detection.</p><fig id="F1" position="float"><label>Figure 1</label><caption><p>(a)-(c) ECG leads I-III recorded inside the 7T MR scanner. (d)-(e) Three ICs obtained from the 12-lead ECG. The IC shown in (d) which is dominated by the R peak is used for gating. The R peaks in (a)-(f) are aligned at 150ms.</p></caption><graphic xlink:href="1532-429X-15-S1-W33-1"></graphic></fig></sec><sec sec-type="results"><title>Results</title><p>Examples for the different ICs obtained by the FastICA algorithm are depicted in Figs. <xref ref-type="fig" rid="F1">1(d)-(f)</xref>. The automatic identification of the IC representing the R wave was possible in nine of the ten data sets while the 10th data set required manual identification. Regarding the QRS detection, Se and +P of 97% was achieved for all ten data sets, respectively. For the VCG based method, Se was 90% and +P reached only 48%.</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>An ICA-based gating method has been shown to outperform the state-of-the-art VCG based gating technique for UHF MRI. As with the VCG method, the proposed ICA based method can be applied in real time, since it can be shown that the computation of the demixing matrix does not need to be updated for each new sample. Recent developments of MR safe 12-lead ECG recorders could make this method applicable in clinical practice [<xref ref-type="bibr" rid="B5">5</xref>].</p></sec><sec><title>Funding</title><p>This work was founded by the Federal Ministry of Education (Germany, BMBF, 03IP710) and by the Royal Academy of Engineering (UK).</p></sec></body><back><ref-list><ref id="B1"><mixed-citation publication-type="other"><name><surname>Lamb</surname></name><source>J Cardiovasc Magn Reson</source><year>2012</year><volume>14</volume><issue>Suppl 1</issue></mixed-citation></ref><ref id="B2"><mixed-citation publication-type="other"><name><surname>Fischer</surname></name><source>Magnet Reson Med</source><year>1999</year><volume>42</volume></mixed-citation></ref><ref id="B3"><mixed-citation publication-type="other"><name><surname>Hyvarinen</surname></name><source>IEEE Trans Neural Netw</source><year>1999</year><volume>10</volume></mixed-citation></ref><ref id="B4"><mixed-citation publication-type="other"><name><surname>Pan</surname></name><source>IEEE Trans Biomed Eng</source><year>1985</year><volume>32</volume></mixed-citation></ref><ref id="B5"><mixed-citation publication-type="other"><name><surname>Tse</surname></name><source>ISMRM</source><year>2012</year><volume>18</volume></mixed-citation></ref></ref-list></back></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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