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Electrocardiologic and related methods of non-invasive detection and risk stratification in myocardial ischemia: state of the art and perspectives

Identifieur interne : 000704 ( Ncbi/Merge ); précédent : 000703; suivant : 000705

Electrocardiologic and related methods of non-invasive detection and risk stratification in myocardial ischemia: state of the art and perspectives

Auteurs : Thomas Huebner [Autriche] ; Matthias Goernig [Allemagne] ; Michael Schuepbach [France] ; Ernst Sanz [France] ; Roland Pilgram [Autriche] ; Andrea Seeck [Allemagne] ; Andreas Voss [Allemagne]

Source :

RBID : PMC:2975259

Abstract

Background: Electrocardiographic methods still provide the bulk of cardiovascular diagnostics. Cardiac ischemia is associated with typical alterations in cardiac biosignals that have to be measured, analyzed by mathematical algorithms and allegorized for further clinical diagnostics. The fast growing fields of biomedical engineering and applied sciences are intensely focused on generating new approaches to cardiac biosignal analysis for diagnosis and risk stratification in myocardial ischemia.

Objectives: To present and review the state of the art in and new approaches to electrocardiologic methods for non-invasive detection and risk stratification in coronary artery disease (CAD) and myocardial ischemia; secondarily, to explore the future perspectives of these methods.

Methods: In follow-up to the Expert Discussion at the 2008 Workshop on "Biosignal Analysis" of the German Society of Biomedical Engineering in Potsdam, Germany, we comprehensively searched the pertinent literature and databases and compiled the results into this review. Then, we categorized the state-of-the-art methods and selected new approaches based on their applications in detection and risk stratification of myocardial ischemia. Finally, we compared the pros and cons of the methods and explored their future potentials for cardiology.

Results: Resting ECG, particularly suited for detecting ST-elevation myocardial infarctions, and exercise ECG, for the diagnosis of stable CAD, are state-of-the-art methods. New exercise-free methods for detecting stable CAD include cardiogoniometry (CGM); methods for detecting acute coronary syndrome without ST elevation are Body Surface Potential Mapping, functional imaging and CGM. Heart rate variability and blood pressure variability analyses, microvolt T-wave alternans and signal-averaged ECG mainly serve in detecting and stratifying the risk for lethal arrythmias in patients with myocardial ischemia or previous myocardial infarctions. Telemedicine and ambient-assisted living support the electrocardiological monitoring of at-risk patients.

Conclusions: There are many promising methods for the exercise-free, non-invasive detection of CAD and myocardial ischemia in the stable and acute phases. In the coming years, these new methods will help enhance state-of-the-art procedures in routine diagnostics. The future can expect that equally novel methods for risk stratification and telemedicine will transition into clinical routine.


Url:
DOI: 10.3205/000116
PubMed: 21063467
PubMed Central: 2975259

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PMC:2975259

Le document en format XML

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<bold>Background:</bold>
Electrocardiographic methods still provide the bulk of cardiovascular diagnostics. Cardiac ischemia is associated with typical alterations in cardiac biosignals that have to be measured, analyzed by mathematical algorithms and allegorized for further clinical diagnostics. The fast growing fields of biomedical engineering and applied sciences are intensely focused on generating new approaches to cardiac biosignal analysis for diagnosis and risk stratification in myocardial ischemia.</p>
<p>
<bold>Objectives:</bold>
To present and review the state of the art in and new approaches to electrocardiologic methods for non-invasive detection and risk stratification in coronary artery disease (CAD) and myocardial ischemia; secondarily, to explore the future perspectives of these methods. </p>
<p>
<bold>Methods:</bold>
In follow-up to the Expert Discussion at the 2008 Workshop on "Biosignal Analysis" of the German Society of Biomedical Engineering in Potsdam, Germany, we comprehensively searched the pertinent literature and databases and compiled the results into this review. Then, we categorized the state-of-the-art methods and selected new approaches based on their applications in detection and risk stratification of myocardial ischemia. Finally, we compared the pros and cons of the methods and explored their future potentials for cardiology.</p>
<p>
<bold>Results:</bold>
Resting ECG, particularly suited for detecting ST-elevation myocardial infarctions, and exercise ECG, for the diagnosis of stable CAD, are state-of-the-art methods. New exercise-free methods for detecting stable CAD include cardiogoniometry (CGM); methods for detecting acute coronary syndrome without ST elevation are Body Surface Potential Mapping, functional imaging and CGM. Heart rate variability and blood pressure variability analyses, microvolt T-wave alternans and signal-averaged ECG mainly serve in detecting and stratifying the risk for lethal arrythmias in patients with myocardial ischemia or previous myocardial infarctions. Telemedicine and ambient-assisted living support the electrocardiological monitoring of at-risk patients.</p>
<p>
<bold>Conclusions:</bold>
There are many promising methods for the exercise-free, non-invasive detection of CAD and myocardial ischemia in the stable and acute phases. In the coming years, these new methods will help enhance state-of-the-art procedures in routine diagnostics. The future can expect that equally novel methods for risk stratification and telemedicine will transition into clinical routine.</p>
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</TEI>
<pmc article-type="review-article">
<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Ger Med Sci</journal-id>
<journal-id journal-id-type="publisher-id">GMS Ger Med Sci</journal-id>
<journal-title-group>
<journal-title>GMS German Medical Science</journal-title>
</journal-title-group>
<issn pub-type="epub">1612-3174</issn>
<publisher>
<publisher-name>German Medical Science GMS Publishing House</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">21063467</article-id>
<article-id pub-id-type="pmc">2975259</article-id>
<article-id pub-id-type="publisher-id">Doc000116</article-id>
<article-id pub-id-type="doi">10.3205/000116</article-id>
<article-id pub-id-type="pii">27</article-id>
<article-id pub-id-type="other">urn:nbn:de:0183-0001164</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Electrocardiologic and related methods of non-invasive detection and risk stratification in myocardial ischemia: state of the art and perspectives</article-title>
<trans-title-group xml:lang="de">
<trans-title>Elektrokardiologische und angrenzende Methoden zur nichtinvasiven Erkennung von Myokardischämien und Risikostratifizierung: Stand der Technik und Perspektiven</trans-title>
</trans-title-group>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Huebner</surname>
<given-names>Thomas</given-names>
</name>
<xref ref-type="corresp" rid="COR1">*</xref>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Goernig</surname>
<given-names>Matthias</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Schuepbach</surname>
<given-names>Michael</given-names>
</name>
<xref ref-type="aff" rid="A3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Sanz</surname>
<given-names>Ernst</given-names>
</name>
<xref ref-type="aff" rid="A3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pilgram</surname>
<given-names>Roland</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Seeck</surname>
<given-names>Andrea</given-names>
</name>
<xref ref-type="aff" rid="A4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Voss</surname>
<given-names>Andreas</given-names>
</name>
<xref ref-type="aff" rid="A4">4</xref>
</contrib>
</contrib-group>
<aff id="A1">
<label>1</label>
Department for Human and Economic Sciences, University for Health Sciences, Medical Informatics and Technology (UMIT), Hall, Austria</aff>
<aff id="A2">
<label>2</label>
Clinic of Internal Medicine I, University Hospital of Jena, Germany</aff>
<aff id="A3">
<label>3</label>
University Hospital Inselspital, Bern, Switzerland CHU Pitié-Salpêtrière, Paris, France</aff>
<aff id="A4">
<label>4</label>
Departement of Medical Engineering and Biotechnology, University of Applied Sciences Jena, Germany</aff>
<author-notes>
<corresp id="COR1">*To whom correspondence should be addressed: Thomas Huebner, University for Health Sciences, Medical Informatics and Technology (UMIT), Department for Human and Economic Sciences, Eduard-Wallnoefer-Zentrum 1, A-6060 Hall, Austria, T: +49 (0) 171 - 69 852 73, Fax: +49 (0) 36 41- 53 49 019, E-mail:
<email>thomas.huebner@umit.at</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>11</day>
<month>10</month>
<year>2010</year>
</pub-date>
<pub-date pub-type="collection">
<year>2010</year>
</pub-date>
<volume>8</volume>
<elocation-id>Doc27</elocation-id>
<history>
<date date-type="received">
<day>01</day>
<month>5</month>
<year>2010</year>
</date>
<date date-type="rev-recd">
<day>26</day>
<month>8</month>
<year>2010</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright © 2010 Huebner et al.</copyright-statement>
<copyright-year>2010</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc-nd/3.0/">
<license-p>
<pmc-comment>CREATIVE COMMONS</pmc-comment>
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-nc-nd/3.0/deed.en">http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en</ext-link>
). You are free to copy, distribute and transmit the work, provided the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri xlink:type="simple" xlink:href="http://www.egms.de/en/journals/gms/2010-8/000116.shtml">This article is available from http://www.egms.de/en/journals/gms/2010-8/000116.shtml</self-uri>
<abstract>
<p>
<bold>Background:</bold>
Electrocardiographic methods still provide the bulk of cardiovascular diagnostics. Cardiac ischemia is associated with typical alterations in cardiac biosignals that have to be measured, analyzed by mathematical algorithms and allegorized for further clinical diagnostics. The fast growing fields of biomedical engineering and applied sciences are intensely focused on generating new approaches to cardiac biosignal analysis for diagnosis and risk stratification in myocardial ischemia.</p>
<p>
<bold>Objectives:</bold>
To present and review the state of the art in and new approaches to electrocardiologic methods for non-invasive detection and risk stratification in coronary artery disease (CAD) and myocardial ischemia; secondarily, to explore the future perspectives of these methods. </p>
<p>
<bold>Methods:</bold>
In follow-up to the Expert Discussion at the 2008 Workshop on "Biosignal Analysis" of the German Society of Biomedical Engineering in Potsdam, Germany, we comprehensively searched the pertinent literature and databases and compiled the results into this review. Then, we categorized the state-of-the-art methods and selected new approaches based on their applications in detection and risk stratification of myocardial ischemia. Finally, we compared the pros and cons of the methods and explored their future potentials for cardiology.</p>
<p>
<bold>Results:</bold>
Resting ECG, particularly suited for detecting ST-elevation myocardial infarctions, and exercise ECG, for the diagnosis of stable CAD, are state-of-the-art methods. New exercise-free methods for detecting stable CAD include cardiogoniometry (CGM); methods for detecting acute coronary syndrome without ST elevation are Body Surface Potential Mapping, functional imaging and CGM. Heart rate variability and blood pressure variability analyses, microvolt T-wave alternans and signal-averaged ECG mainly serve in detecting and stratifying the risk for lethal arrythmias in patients with myocardial ischemia or previous myocardial infarctions. Telemedicine and ambient-assisted living support the electrocardiological monitoring of at-risk patients.</p>
<p>
<bold>Conclusions:</bold>
There are many promising methods for the exercise-free, non-invasive detection of CAD and myocardial ischemia in the stable and acute phases. In the coming years, these new methods will help enhance state-of-the-art procedures in routine diagnostics. The future can expect that equally novel methods for risk stratification and telemedicine will transition into clinical routine.</p>
</abstract>
<trans-abstract xml:lang="de">
<p>
<bold>Hintergrund:</bold>
Elektrokardiografische Verfahren stellen nach wie vor die primär wichtigsten Methoden zur kardiologischen Diagnostik dar. Eine Herzischämie geht mit typischen Veränderungen kardialer Biosignale einher, die anhand mathematischer Algorithmen analysiert und für den weiteren klinischen Pfad aufbereitet werden müssen. Die rasant wachsende Biomedizintechnik sowie angewandte Wissenschaften beschäftigen sich intensiv mit neuen Ansätzen zur Auswertung kardialer Biosignale zur Ischämiediagnostik und Risikostratifizierung. </p>
<p>
<bold>Ziele:</bold>
Hauptziel dieser Übersichtsarbeit ist es, den gegenwärtigen Stand der Technik sowie neue Ansätze im Bereich elektrokardiologischer Verfahren zur nicht-invasiven Erkennung und Risikostratifizierung von koronarer Herzkrankheit (KHK) und Myokardischämie vorzustellen und zu bewerten. Als Sekundärziel werden die Zukunftsperspektiven dieser Verfahren aufgezeigt. </p>
<p>
<bold>Methoden:</bold>
Beginnend mit Expertendiskussionen während des Workshops „Biosignalverarbeitung“ der Deutschen Gesellschaft für Biomedizinische Technik (2008 in Potsdam) sowie anschließenden intensiven Recherchen der Literatur und Datenbanken wurde dieser Review erstellt. Es erfolgte eine Kategorisierung von Verfahren des Standes der Technik sowie ausgewählter neuer Ansätze entsprechend ihrer Einsatzgebiete zur Ischämiediagnostik und Risikostratifizierung. Die Vor- und Nachteile wurden aufgezeigt und die künftigen Möglichkeiten dieser Verfahren in der Kardiologie untersucht.</p>
<p>
<bold>Ergebnisse:</bold>
Als Stand der Technik anzusehen ist das Ruhe-EKG (insbesondere geeignet für Erkennung von ST-Hebungsinfarkten) und das Belastungs-EKG (Diagnostik von stabiler KHK). Neue belastungsfreie Verfahren zur Erkennung von stabiler KHK sind die Kardiogoniometrie (KGM) sowie zur Erkennung des Akuten Koronarsyndroms ohne ST-Hebung das Body Surface Potential Mapping, Funktionelle Bildgebung sowie die KGM. Analyse von Herzfrequenz- und Blutdruckvariabilität, T-Wellen-Alternans und Spätpotentialen dienen vorrangig der Erkennung und Stratifizierung des Risikos für letale Arrythmien bei Patienten mit Myokardischämie oder nach durchlebtem Myokardinfarkt. Telemedizin und technologieunterstütztes Wohnen (Ambient Assisted Living) unterstützen das elektrokardiologische Monitoring von Risikopatienten.</p>
<p>
<bold>Schlussfolgerungen:</bold>
Es gibt vielversprechende Ansätzen insbesondere zur belastungsfreien nichtinvasiven Erkennung von KHK und Myokardischämie in stabiler Phase und Akutsituation, welche in den nächsten Jahren die Standardverfahren in der Routinediagnostik ergänzen werden. Ebenso neue Verfahren der Risikostratifizierung sowie telemedizinische Techniken werden den Übergang in die Routineanwendung finden.</p>
</trans-abstract>
<kwd-group>
<kwd>resting electrocardiography</kwd>
<kwd>exercise electrocardiography</kwd>
<kwd>cardiogoniometry</kwd>
<kwd>body surface potential mapping</kwd>
<kwd>heart rate variability</kwd>
<kwd>functional imaging</kwd>
</kwd-group>
</article-meta>
</front>
<floats-group>
<fig id="T1" position="float">
<label>Table 1</label>
<caption>
<title>Selected electrocardiography-based methods for the detection of myocardial ischemia and CAD in stable and acute phases</title>
</caption>
<graphic xlink:href="GMS-08-27-t-001"></graphic>
</fig>
<fig id="T2" position="float">
<label>Table 2</label>
<caption>
<title>Selected electrocardiography-based methods for arrhythmic risk detection and stratification for ACD</title>
</caption>
<graphic xlink:href="GMS-08-27-t-002"></graphic>
</fig>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption>
<title>Overview of electrocardiologic and related methods including their intended applications</title>
</caption>
<graphic xlink:href="GMS-08-27-g-001"></graphic>
</fig>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption>
<title>Electrocardiographic phases of STEMI adapted from the Pschyrembel database [13]</title>
</caption>
<graphic xlink:href="GMS-08-27-g-002"></graphic>
</fig>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption>
<title>Nonpathologic (top) and pathologic (bottom) exercise ECG reactions adapted from Pschyrembel database [13]</title>
</caption>
<graphic xlink:href="GMS-08-27-g-003"></graphic>
</fig>
<fig id="F4" position="float">
<label>Figure 4</label>
<caption>
<title>Overview of the guidelines issued by the European Society of Cardiology (ESC) and German Society of Cardiology (DGK) considering electrocardiologic and related methods concerning acute and stable ischemic situations and risk stratification</title>
</caption>
<graphic xlink:href="GMS-08-27-g-004"></graphic>
</fig>
<fig id="F5" position="float">
<label>Figure 5</label>
<caption>
<title>Example for high-resolution ECG </title>
<p>Top: Sum vector, Bottom: 3 dimensional frequency spectrum; Left: Patient with late potentials at high risk for sudden cardiac death with prolonged QRS in sum vector (low-amplitude electrical signal which occurs in the terminal QRS complex or within the ST segment) and enhanced high frequency components in the spectrum. Right: Patient with low risk profile and no late potentials, see also [22].</p>
</caption>
<graphic xlink:href="GMS-08-27-g-005"></graphic>
</fig>
<fig id="F6" position="float">
<label>Figure 6</label>
<caption>
<title>Corrected body surface potential map at the time point 260 ms (cursor position) </title>
<p>Eleven amplitude levels from S11 to S1 in mV are shown (V - front view; H - back of the sphere and the heart). With the kind permission of [28].</p>
</caption>
<graphic xlink:href="GMS-08-27-g-006"></graphic>
</fig>
<fig id="F7" position="float">
<label>Figure 7</label>
<caption>
<title>Principles of cardiogoniometry </title>
<p>A) Four electrodes are placed at four points on the patient’s thorax as follows: Point 1 (green) at point V4 of Wilson, i.e. in the 5
<sup>th</sup>
intercostal space in the mid-clavicular line; point 2 (white) sagittal to electrode 1 on the back (point V8 of Wilson); point 3 (yellow) is located perpendicularly above electrode 1 at 0.7 times the distance between points 1 and 2; point 4 (red) is placed to the right of point 3 at the same distance as between points 1 and 3. The leads are defined as follows: 4-2 D (dorsal), 4-1 A (anterior), 2-1 I (inferior), 4-3 Ho (horizontal), 3-1 Ve (vertical). B) Points 4-2-1 define the oblique sagittal plane OSP (red); points 4-3-1 define the frontal plane (yellow). The third plane (blue) is orthogonal to the two other planes and contains point 3; it is the sagittal plane perpendicular to the OSP. Projection x is oriented in an antero-dorsal direction and lies in the OSP and the sagittal plane perpendicular to the OSP. Projection y is oriented in a baso-apical direction and lies in the OSP (4-2-1) and the frontal plane (4-3-1). Projection z is oriented in a supero-inferior direction relative to the OSP and lies in the frontal plane (4-3-1) and the sagittal plane perpendicular to the OSP. C) Vector loops from projections x, y and z can be calculated within a Cartesian coordinate system. Figure shows R-Loops (blue) and T-loops (green) of 12 heart cycles and maximum vectors of both (red), calculated on median cycle.</p>
</caption>
<graphic xlink:href="GMS-08-27-g-007"></graphic>
</fig>
<fig id="F8" position="float">
<label>Figure 8</label>
<caption>
<title>Poincaré plots calculated from HRV (tachogram, a-c), from BPV (systolic d-f SYS; diastolic g-i DIA) blood pressure time series of a healthy subject (top row), a DCM patient with low risk (middle row) and a DCM patient with high risk (bottom row), see also [83]</title>
</caption>
<graphic xlink:href="GMS-08-27-g-008"></graphic>
</fig>
</floats-group>
</pmc>
<affiliations>
<list>
<country>
<li>Allemagne</li>
<li>Autriche</li>
<li>France</li>
</country>
<region>
<li>Île-de-France</li>
</region>
<settlement>
<li>Paris</li>
</settlement>
</list>
<tree>
<country name="Autriche">
<noRegion>
<name sortKey="Huebner, Thomas" sort="Huebner, Thomas" uniqKey="Huebner T" first="Thomas" last="Huebner">Thomas Huebner</name>
</noRegion>
<name sortKey="Pilgram, Roland" sort="Pilgram, Roland" uniqKey="Pilgram R" first="Roland" last="Pilgram">Roland Pilgram</name>
</country>
<country name="Allemagne">
<noRegion>
<name sortKey="Goernig, Matthias" sort="Goernig, Matthias" uniqKey="Goernig M" first="Matthias" last="Goernig">Matthias Goernig</name>
</noRegion>
<name sortKey="Seeck, Andrea" sort="Seeck, Andrea" uniqKey="Seeck A" first="Andrea" last="Seeck">Andrea Seeck</name>
<name sortKey="Voss, Andreas" sort="Voss, Andreas" uniqKey="Voss A" first="Andreas" last="Voss">Andreas Voss</name>
</country>
<country name="France">
<region name="Île-de-France">
<name sortKey="Schuepbach, Michael" sort="Schuepbach, Michael" uniqKey="Schuepbach M" first="Michael" last="Schuepbach">Michael Schuepbach</name>
</region>
<name sortKey="Sanz, Ernst" sort="Sanz, Ernst" uniqKey="Sanz E" first="Ernst" last="Sanz">Ernst Sanz</name>
</country>
</tree>
</affiliations>
</record>

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