Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Merhof, Dorit

Biomedical Engineering / Biomedizinische Technik

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering and the German Society of Biomaterials

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Habibović, Pamela / Haueisen, Jens / Jahnen-Dechent, Wilhelm / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Leonhardt, Steffen / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Boenick, Ulrich / Jaramaz, Branislav / Kraft, Marc / Lenarz, Thomas / Lenthe, Harry / Lo, Benny / Mainardi, Luca / Micera, Silvestro / Penzel, Thomas / Robitzki, Andrea A. / Schaeffter, Tobias / Snedeker, Jess G. / Sörnmo, Leif / Sugano, Nobuhiko / Werner, Jürgen /

IMPACT FACTOR 2018: 1.007
5-year IMPACT FACTOR: 1.390

CiteScore 2018: 1.24

SCImago Journal Rank (SJR) 2018: 0.282
Source Normalized Impact per Paper (SNIP) 2018: 0.831

See all formats and pricing
More options …
Volume 62, Issue 2


Volume 57 (2012)

Parametrization of an in-silico circulatory simulation by clinical datasets – towards prediction of ventricular function following assist device implantation

Ajay Moza / Jonas Gesenhues / Rüdiger Autschbach / Dirk Abel / Rolf Rossaint / Thomas Schmitz-Rode
  • Institute of Applied Medical Engineering, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Andreas Goetzenich
Published Online: 2017-03-06 | DOI: https://doi.org/10.1515/bmt-2016-0078



Left ventricular assist device (LVAD) therapy has revolutionized the way end stage heart failure is treated today. Analysis of LVAD interaction with the whole cardiovascular system and its biological feedback loops is often conducted by means of computer models. Generating real time pressure volume loops (PV-loops) in patients, not using conductance catheters but routine diagnostics to feed an in-silico model could help to predict postoperative complications.


Routinely obtained hemodynamic measurements to evaluate myocardial function prior to LVAD implantation like pressure readings in the aorta, the left atrium and the left ventricle and simultaneous three-dimensional (3D) echocardiography recordings were assessed to parametrize a reduced computational model of the cardiovascular system. An automatic parameter identification procedure has been developed.


The results constitute a patient-individual computational simulation model. An exemplary in-silico study focusing on the effect of different ventricular assist device (VAD) speeds has been conducted. Results allow for estimation of the resulting hemodynamic parameters and changes of the PV-loops.


The model improves understanding and prediction of the interaction between pump and ventricles. Future modifications in exporting and merging routinely assessed real time hemodynamic patient data are necessary to investigate various clinical and pathological conditions of LVAD recipients.

Keywords: assist device; circulatory support; simulation


  • [1]

    Atluri P, Goldstone AB, Fairman AS, et al. Predicting right ventricular failure in the modern, continuous flow left ventricular assist device era. Ann Thorac Surg 2013; 96: 857–863; discussion 863–4.Web of ScienceCrossrefPubMedGoogle Scholar

  • [2]

    Baan J, van der Velde ET, Steendijk P. Ventricular pressure-volume relations in vivo. Eur Heart J 1992; 13(Suppl E): 2–6.CrossrefPubMedGoogle Scholar

  • [3]

    Brunberg A, Heinke S, Spillner J, Autschbach R, Abel D, Leonhardt S. Modeling and simulation of the cardiovascular system: a review of applications, methods, and potentials. Biomed Tech (Berl) 2009; 54: 233–244.CrossrefPubMedGoogle Scholar

  • [4]

    Buccheri S, Costanzo L, Tamburino C, Monte I. Reference values for real time three-dimensional echocardiography-derived left ventricular volumes and ejection fraction: review and meta-analysis of currently available studies. Echocardiography 2015; 32: 1841–1850.CrossrefWeb of SciencePubMedGoogle Scholar

  • [5]

    Chung DC, Niranjan SC, Clark JW, et al. A dynamic model of ventricular interaction and pericardial influence. Am J Physiol-Heart Circ Physiol 1997; 272: H2942–62.CrossrefGoogle Scholar

  • [6]

    Clark JE, Marber MS. Advancements in pressure-volume catheter technology—stress remodelling after infarction. Exp Physiol 2013; 98: 614–621.PubMedCrossrefGoogle Scholar

  • [7]

    Colacino FM, Moscato F, Piedimonte F, Arabia M, Danieli GA. Left ventricle load impedance control by apical VAD can help heart recovery and patient perfusion: a numerical study. ASAIO J 2007; 53: 263–277.Web of ScienceCrossrefPubMedGoogle Scholar

  • [8]

    Gesenhues J, Hein M, Albin T, Rossaint R, Abel D. Cardiac modeling: identification of subject specific left-ventricular isovolumic pressure curves. IFAC-PapersOnLine 2015; 48: 581–586.CrossrefGoogle Scholar

  • [9]

    Gesenhues J, Hein M, Ketelhut M, et al. Benefits of objectoriented models and ModeliChart: modern tools and methods for the interdisciplinary research on smart biomedical technology. Biomed Eng-Biomed Tech 2017; 62: 111–121

  • [10]

    Kaufmann TA, Neidlin M, Büsen M, Sonntag SJ, Steinseifer U. Implementation of intrinsic lumped parameter modeling into computational fluid dynamics studies of cardiopulmonary bypass. J Biomech 2014; 47: 729–735.Web of SciencePubMedCrossrefGoogle Scholar

  • [11]

    Kjørstad KE, Korvald C, Myrmel T. Pressure-volume-based single-beat estimations cannot predict left ventricular contractility in vivo. Am J Physiol Heart Circ Physiol2002; 282: H1739–H1750.Google Scholar

  • [12]

    Kono A, Maughan WL, Sunagawa K, Hamilton K, Sagawa K, Weisfeldt ML. The use of left ventricular end-ejection pressure and peak pressure in the estimation of the end-systolic pressure-volume relationship. Circulation 1984; 70: 1057–65.CrossrefGoogle Scholar

  • [13]

    Kormos RL, Teuteberg JJ, Pagani FD, et al. HeartMate II Clinical Investigators. Right ventricular failure in patients with the HeartMate II continuous-flow left ventricular assist device: incidence, risk factors, and effect on outcomes. J Thorac Cardiovasc Surg 2010; 139: 1316–1324.PubMedCrossrefGoogle Scholar

  • [14]

    Leaning MS, Pullen HE, Carson ER, Finkelstein L. Modelling a complex biological system: the human cardiovascular system1. Methodology and model description. Trans Inst Meas Control 1983; 5: 71–86.CrossrefGoogle Scholar

  • [15]

    Ramakrishna H, Feinglass N, Augoustides JG. Clinical update in cardiac imaging including echocardiography. J Cardiothorac Vasc Anesth 2010; 24: 371–378.CrossrefWeb of SciencePubMedGoogle Scholar

  • [16]

    Roger VL. Epidemiology of heart failure. Circ Res 2013; 113: 646–659.CrossrefPubMedGoogle Scholar

  • [17]

    Saito S, Toda K, Nakamura T, et al. Should destination therapy with implantable left ventricular assist device replace heart transplantation? J Card Failure 2015; 21: S151.Web of ScienceCrossrefGoogle Scholar

  • [18]

    Shimada YJ, Shiota T. A meta-analysis and investigation for the source of bias of left ventricular volumes and function by three-dimensional echocardiography in comparison with magnetic resonance imaging. Am J Cardiol 2011; 107: 126–138.CrossrefWeb of SciencePubMedGoogle Scholar

  • [19]

    Spitzer VM, Whitlock DG. The visible human dataset: the anatomical platform for human simulation. Anatom Rec 1998; 253: 49–57.CrossrefGoogle Scholar

  • [20]

    Takeuchi M, Igarashi Y, Tomimoto S, et al. Single-beat estimation of the slope of the end-systolic pressure-volume relation in the human left ventricle. Circulation 1991; 83: 202–212.CrossrefPubMedGoogle Scholar

  • [21]

    ten Brinke EA, Klautz RJ, Tulner SA, et al. Clinical and functional effects of restrictive mitral annuloplasty at midterm follow-up in heart failure patients. Ann Thorac Surg 2010; 90: 1913–1920.CrossrefWeb of SciencePubMedGoogle Scholar

  • [22]

    Ursino M. Interaction between carotid baroregulation and the pulsating heart: a mathematical model. Am J Physiol 1998; 275: H1733–H1747.Google Scholar

  • [23]

    Vandenberghe S, Segers P, Steendijk P, et al. Modeling ventricular function during cardiac assist: does time-varying elastance work? ASAIO J 2006; 52: 4–8.PubMedCrossrefGoogle Scholar

  • [24]

    Westerhof N, Lankhaar J, Westerhof B. The arterial Windkessel. Med Biol Eng Comput 2009; 47.2: 131–141.Web of ScienceGoogle Scholar

  • [25]

    Yu Y, Porter J. Mathematical modeling of ventricular suction induced by a rotary ventricular assist device. In: American Control Conference. Minneapolis, MN, USA, 2006.Google Scholar

  • [26]

    Zimmermann W-H. Strip and dress the human heart. Circ Res 2016; 118: 12–13.CrossrefPubMedWeb of ScienceGoogle Scholar

About the article

Corresponding author: Andreas Goetzenich, MD, PhD, Department of Thoracic and Cardiovascular Surgery, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany, Phone: +49 241 80 35556, Fax: +49 241 80 333 555 6

aAjay Moza and Jonas Gesenhues: These authors contributed equally to this work.

Received: 2016-03-31

Accepted: 2017-01-12

Published Online: 2017-03-06

Published in Print: 2017-04-01

Citation Information: Biomedical Engineering / Biomedizinische Technik, Volume 62, Issue 2, Pages 123–130, ISSN (Online) 1862-278X, ISSN (Print) 0013-5585, DOI: https://doi.org/10.1515/bmt-2016-0078.

Export Citation

©2017 Walter de Gruyter GmbH, Berlin/Boston.Get Permission

Comments (0)

Please log in or register to comment.
Log in