Cardiac ischemia—insights from computational models

  • Axel Loewe
  • Eike Moritz Wülfers
  • Gunnar SeemannEmail author



Complementary to clinical and experimental studies, computational cardiac modeling serves to obtain a comprehensive understanding of the cardiovascular system in order to analyze dysfunction, evaluate existing, and develop novel treatment strategies.


We describe the basics of multiscale computational modeling of cardiac electrophysiology from the molecular ion channel to the whole body scale. By modeling cardiac ischemia, we illustrate how in silico experiments can contribute to our understanding of how the pathophysiological mechanisms translate into changes observed in diagnostic tools such as the electrocardiogram (ECG).

Materials and methods

Quantitative in silico modeling spans a wide range of scales from ion channel biophysics to ECG signals. For each of the scales, a set of mathematical equations describes electrophysiology in relation to the other scales. Integration of ischemia-induced changes is performed on the ion channel, single-cell, and tissue level. This approach allows us to study how effects simulated at molecular scales translate to changes in the ECG.


Ischemia induces action potential shortening and conduction slowing. Hence, ischemic myocardium has distinct and significant effects on propagation and repolarization of excitation, depending on the intramural extent of the ischemic region. For transmural and subendocardial ischemic regions, ST segment elevation and depression, respectively, were observed, whereas intermediate ischemic regions were found to be electrically silent (NSTEMI).


In silico modeling contributes quantitative and mechanistic insight into fundamental ischemia-related arrhythmogenic mechanisms. In addition, computational modeling can help to translate experimental findings at the (sub-)cellular level to the organ and body context (e. g., ECG), thereby providing a thorough understanding of this routinely used diagnostic tool that may translate into optimized applications.


Electrocardiography Electrophysiology Review Mathematical models Cardiology 

Kardiale Ischämie – Erkenntnisse aus Computermodellen



Das mechanistische Verständnis des Herz-Kreislauf-Systems ist von grundlegender Bedeutung, wenn man Fehlfunktionen verstehen, Behandlungsmöglichkeiten bewerten und neue Therapien entwickeln will. Die quantitative In-silico-Modellierung kann klinische und experimentelle Studien ergänzen.


Wir beschreiben die Grundlagen einer computergestützten Multiskalenmodellierung der kardialen Elektrophysiologie und des Elektrokardiogramms (EKG) – von Ionenkanälen auf molekularer Ebene bis hin zur Ebene des Gesamtorganismus. Am Beispiel der Modellierung der kardialen Ischämie veranschaulichen wir, wie In-silico-Experimente zum Verständnis der Zusammenhänge zwischen fundamentalen pathophysiologischen Mechanismen und Diagnosewerkzeugen wie dem EKG beitragen können.

Material und Methoden

Die numerische Herzmodellierung integriert viele zeitlich-räumliche Skalen: Von der Ionenkanalbiophysik bis hin zu EKG-Signalen. Für jede der Skalen beschreiben mathematische Gleichungen die elektrophysiologische Funktion in Beziehung zu den anderen Skalen. Die Integration von ischämieinduzierten Veränderungen erfolgt auf Ionenkanal‑, Einzelzell- und Gewebeebene. Mit diesem Ansatz lässt sich untersuchen, wie sich aus simulierten Effekten auf molekularer Ebene Änderungen im simulierten EKG ergeben.


Aufgrund der Verkürzung des Aktionspotenzials und der Leitungsverlangsamung haben ischämische Bereiche unterschiedlicher transmuraler Ausdehnung einen deutlichen Effekt auf die Erregungsausbreitung und die Repolarisation. Eine ST-Segment-Hebung bzw. -Senkung zeigte sich für transmurale bzw. subendokardiale ischämische Regionen. Ischämische Regionen mittlerer Ausdehnung waren elektrisch unauffällig (NSTEMI).


Die In-silico-Modellierung kann quantitative und mechanistische Erkenntnisse zu fundamentalen ischämiebezogenen arrhythmogenen Mechanismen liefern. Darüber hinaus erlaubt die computergestützte Modellierung, experimentelle Ergebnisse von der (sub-)zellulären Ebene auf die Organ- und EKG-Ebene zu übertragen. Somit trägt sie zu einem tieferen Verständnis des routinemäßig eingesetzten EKGs und zu einer Optimierung dieses Werkzeugs bei.


Elektrokardiographie Elektrophysiologie Übersicht Mathematische Modelle Kardiologie 


Compliance with ethical guidelines

Conflict of interest

A. Loewe, E.M. Wülfers and G. Seemann declare that they have no competing interests.

This article does not contain any studies with human participants or animals performed by any of the authors. The ethical guidelines of the studies cited are provided within those studies.


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Copyright information

© Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2018

Authors and Affiliations

  • Axel Loewe
    • 1
  • Eike Moritz Wülfers
    • 2
    • 3
  • Gunnar Seemann
    • 1
    • 2
    • 3
    Email author
  1. 1.Institute of Biomedical EngineeringKarlsruhe Institute of Technology (KIT)KarlsruheGermany
  2. 2.Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg, Bad Krozingen, Medical Center, Computational Modeling GroupAlbert-Ludwigs University of FreiburgFreiburgGermany
  3. 3.Faculty of MedicineUniversity of FreiburgFreiburgGermany

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