Literature DB >> 28502795

Multi-scale, tailor-made heart simulation can predict the effect of cardiac resynchronization therapy.

Jun-Ichi Okada1, Takumi Washio2, Machiko Nakagawa3, Masahiro Watanabe3, Yoshimasa Kadooka3, Taro Kariya4, Hiroshi Yamashita4, Yoko Yamada5, Shin-Ichi Momomura5, Ryozo Nagai4, Toshiaki Hisada6, Seiryo Sugiura2.   

Abstract

BACKGROUND: The currently proposed criteria for identifying patients who would benefit from cardiac resynchronization therapy (CRT) still need to be optimized. A multi-scale heart simulation capable of reproducing the electrophysiology and mechanics of a beating heart may help resolve this problem. The objective of this retrospective study was to test the capability of patient-specific simulation models to reproduce the response to CRT by applying the latest multi-scale heart simulation technology. METHODS AND
RESULTS: We created patient-specific heart models with realistic three-dimensional morphology based on the clinical data recorded before treatment in nine patients with heart failure and conduction block treated by biventricular pacing. Each model was tailored to reproduce the surface electrocardiogram and hemodynamics of each patient in formats similar to those used in clinical practice, including electrocardiography (ECG), echocardiography, and hemodynamic measurements. We then performed CRT simulation on each heart model according to the actual pacing protocol and compared the results with the clinical data. CRT simulation improved the ECG index and diminished wall motion dyssynchrony in each patient. These results, however, did not correlate with the actual response. The best correlation was obtained between the maximum value of the time derivative of ventricular pressure (dP/dtmax) and the clinically observed improvement in the ejection fraction (EF) (r=0.94, p<0.01).
CONCLUSIONS: By integrating the complex pathophysiology of the heart, patient-specific, multi-scale heart simulation could successfully reproduce the response to CRT. With further verification, this technique could be a useful tool in clinical decision making.
Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Conduction; Heart failure; Hemodynamics; Pacemakers

Mesh:

Substances:

Year:  2017        PMID: 28502795     DOI: 10.1016/j.yjmcc.2017.05.006

Source DB:  PubMed          Journal:  J Mol Cell Cardiol        ISSN: 0022-2828            Impact factor:   5.000


  14 in total

1.  Regional Left Ventricular Fiber Stress Analysis for Cardiac Resynchronization Therapy Response.

Authors:  Mohammad Albatat; Henrik Nicolay Finsberg; Hermenegild Arevalo; Joakim Sundnes; Jacob Bergsland; Ilangko Balasingham; Hans Henrik Odland
Journal:  Ann Biomed Eng       Date:  2022-07-27       Impact factor: 4.219

2.  A rapid electromechanical model to predict reverse remodeling following cardiac resynchronization therapy.

Authors:  Pim J A Oomen; Thien-Khoi N Phung; Seth H Weinberg; Kenneth C Bilchick; Jeffrey W Holmes
Journal:  Biomech Model Mechanobiol       Date:  2021-11-24

3.  Absence of Rapid Propagation through the Purkinje Network as a Potential Cause of Line Block in the Human Heart with Left Bundle Branch Block.

Authors:  Jun-Ichi Okada; Takumi Washio; Machiko Nakagawa; Masahiro Watanabe; Yoshimasa Kadooka; Taro Kariya; Hiroshi Yamashita; Yoko Yamada; Shin-Ichi Momomura; Ryozo Nagai; Toshiaki Hisada; Seiryo Sugiura
Journal:  Front Physiol       Date:  2018-02-06       Impact factor: 4.566

Review 4.  Computational Modeling for Cardiac Resynchronization Therapy.

Authors:  Angela W C Lee; Caroline Mendonca Costa; Marina Strocchi; Christopher A Rinaldi; Steven A Niederer
Journal:  J Cardiovasc Transl Res       Date:  2018-01-11       Impact factor: 4.132

5.  Patient-specific heart simulation can identify non-responders to cardiac resynchronization therapy.

Authors:  Akihiro Isotani; Kazunori Yoneda; Takashi Iwamura; Masahiro Watanabe; Jun-Ichi Okada; Takumi Washio; Seiryo Sugiura; Toshiaki Hisada; Kenji Ando
Journal:  Heart Vessels       Date:  2020-03-12       Impact factor: 2.037

6.  A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations.

Authors:  Marina Strocchi; Christoph M Augustin; Matthias A F Gsell; Elias Karabelas; Aurel Neic; Karli Gillette; Orod Razeghi; Anton J Prassl; Edward J Vigmond; Jonathan M Behar; Justin Gould; Baldeep Sidhu; Christopher A Rinaldi; Martin J Bishop; Gernot Plank; Steven A Niederer
Journal:  PLoS One       Date:  2020-06-26       Impact factor: 3.240

Review 7.  A short history of the development of mathematical models of cardiac mechanics.

Authors:  Steven A Niederer; Kenneth S Campbell; Stuart G Campbell
Journal:  J Mol Cell Cardiol       Date:  2018-11-29       Impact factor: 5.000

8.  A rule-based method for predicting the electrical activation of the heart with cardiac resynchronization therapy from non-invasive clinical data.

Authors:  A W C Lee; U C Nguyen; O Razeghi; J Gould; B S Sidhu; B Sieniewicz; J Behar; M Mafi-Rad; G Plank; F W Prinzen; C A Rinaldi; K Vernooy; S Niederer
Journal:  Med Image Anal       Date:  2019-07-05       Impact factor: 8.545

Review 9.  Computational models in cardiology.

Authors:  Steven A Niederer; Joost Lumens; Natalia A Trayanova
Journal:  Nat Rev Cardiol       Date:  2019-02       Impact factor: 32.419

Review 10.  A Heart for Diversity: Simulating Variability in Cardiac Arrhythmia Research.

Authors:  Haibo Ni; Stefano Morotti; Eleonora Grandi
Journal:  Front Physiol       Date:  2018-07-20       Impact factor: 4.566

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