The fiber orientation derived from DTI or

The early computational models of the heart were geometrical models,
mainly depicting the left ventricle. Before the rise of cardiac imaging
modalities, capturing the anatomical geometry of the heart presented a
challenge. The virtual anatomical representation relied on geometrical models
or post-mortem heart dissections. Initial simulations of the left ventricle even
relied on spherical models (Burch et al., 1952). One of the
relatively early computer simulations of cardiac function which highlighted the
importance of heart size and shape in such simulations was performed by
Koushanpour and colleagues (Koushanpour and
Collings, 1966). Advances
in cardiac imaging modalities and its implementation into routine diagnostic
algorithms have accelerated the shift towards image based models (Aoki et al.,
1987; Kayvanpour et al., 2015;
Trayanova et al., 2012; Vetter and
McCulloch, 1998; Zienkiewicz et al.,
1977).

The introduction and acknowledgment of the finite
element method represent a crucial point in the history of cardiac simulation
through the simplified analysis of complex structural and mathematical
problems. The finite element method opened up new possibilities in
computational simulations (Bathe, 2007;
Zienkiewicz et al., 1977). The need for
virtual 3D models of the heart to evaluate, predict and estimate cardiac
function in different settings has been evident in early works. The integration
of various elements into the anatomical model to simulate the desired properties
could be achieved through the generation of 3D volume meshes. The finite
element method facilitated the solutions of complex biophysical challenges into
this implementation (Bathe, 2007; Janz and Grimm, 1972; Vinson et al., 1979; Zienkiewicz et al., 1977).

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Fiber orientation plays a fundamental role in
representing the patient specific functional myocardial phenotype using the 3D
anatomical-based model due to the axis-dependent electrical and contractile
propagation (Bayer et al.,
2012; Trayanova et al., 2012). Recent studies
have shown an acceptable estimation of fiber orientation using rule-based linear
approaches when compared to the fiber orientation derived from DTI or histological
preparations (Geerts et al.,
2002; Jiang et al., 2004; Toussaint et al., 2010). Today, due to
advances in diverse science sectors, individually personalized cardiac models became
a reality. To decrease computational time, costs and load, most cardiac models
only selectively incorporate certain elements (anatomical, biomechanical or
electrophysiological elements), such that the model still fulfills the intended
purpose (Trayanova et
al., 2012). The translation
of personalized cardiac models into the clinical setting for research and
routine diagnostic purposes is yet to be implemented.

Individualized and personalized care is a promising step towards better
and cost-effective medical care. The necessity of in-silico cardiac modeling to gain a better understanding of the
pathomechanisms of heart failure has been brought into the spotlight. Extensive
and detailed computer models that mimic myocardial function based on mathematical
rules have been developed over the past years. This project focuses on the
introduction of a new personalized multi-scale cardiac model that is suitable
for use in a clinical setting. By merging clinical data and imaging sequences
from cardiac MRI with invasive pressure measurements from heart catheterization,
a global personalization of the computational model is theoretically possible. This
project had the following objectives: