A DOMAIN EMBEDDING STRATEGY FOR SOLVING THE BIDOMAIN
EQUATIONS ON COMPLICATED GEOMETRIES
G. T. Lines, J. Sundnes, A. Tveito
Simula Research Laboratory,
P.O. Box 134 Lysaker, N-1325, Norway
Abstract: Simulations with the bidomain equations are often
solved on simple geometries due to the complexity introduced by using
more realistic boundaries. In this work we propose a method where all
the calculations are carried out on squares and boxes even when the
tissue boundaries are complex. This is achieved by domain embedding
and proper extension of the conductivity tensors in the model.We show
in this work how realistic geometries can be implemented for a simulator
working on lattice grids only.
INTRODUCTION
In many applications of the bidomain model it is important to use realistic
geometries, re-entry simulations being one example. The geometry is
then often represented by an unstructured grid, which makes the implementation
of the simulator hard compared to the case where the equations are defined
over a structured grid. Although there exists tools for dealing with
these complications, the fact remains that a lot of work is still carried
out on idealized geometries.
METHOD
The coupled bidomain[1] and forward problem can be formulated as:
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C c |
¶v
¶t
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+ cIion(v,s) = Ñ·(Mi Ñ(v+ue)) |
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Ñ·((Mi+Me) Ñue) = - Ñ·(Mi Ñv) |
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(1) |
where H is the myocardial region and T is the rest of the computational
domain. The physical parameters C and
c are membrane capacitance and membrane surface area per volume tissue. The matrices
M
i,M
e and M
T are conductivity tensors
for intra- and extra-cellular space in H and for extra cardiac tissue
in T. The primary unknowns are the transmembrane potential v, the extra
cellular potential u
e, and the extra cardiac potential u
T.
To compute the ion-current I
ion a
set of states s must be known, these are determined from an ODE system[2]
with right hand side F.
Our aim is to construct a method were a simple grid can be used to solve
(
1) even if H and T are complex. We first note
that (
1) can be reduced to a simpler system[3].
In particular the boundary conditions for u
T and u
e
make it possible to combine the elliptic equations on H and T. To this
end we define
W = T
ÈH and
The equation for u becomes
where
and
The next simplification is to expand the domains H and T into two circumscribing
boxes H
¢ and T
¢, see Figure 1. The parabolic part of the problem is only defined over
the myocardial domain H. The boundary condition states that the intra
cellular current does not leave the domain. This is implemented by setting
M
i=0 on H
¢-H. A similar approach is used to implement the no-flow condition on
¶W, i.e. M
T=0 on T
¢-T. There will be overlap between T and H
¢, M
T will in this area be defined according to its extra cardiac
location.
As a third and final simplification we propose an operator splitting
method to solve the reduced system. The ODEs and the two PDEs are thus
not solved simultaneously, but in three separate steps.

Figure 1: The original domains H and T embedded in boxes H¢ and T¢ .
IMPLEMENTATION
Constructing appropriate grids for the the problem is now fairly
simple since the domains are only rectangles or boxes. If the finite
difference scheme will be used a lattice grid is suitable. In the test
cases presented here we have used the finite element method with triangular
elements i 2D.
Since the solution from one domain is needed to compute the solution
in the other domain a mapping is needed between the domains. This is
particularly easy to construct if the inner grid is a subset of the
outer grid, i.e. with common nodes and elements. Such an arrangement
is shown in Figure 2.
Figure 2: Cross section of the torso. The drawn boundaries are from
outer to inner: ¶W
¢, ¶
W, ¶H
¢ and ¶H
(both epi- and endocardium). The coarsest grid is shown with dotted lines.
Note that the grid over H¢ is a subset of the grid over
W¢.
To construct the conductivity tensors the geometries of the true domains
must be represented in some form. In a 2D setting it might be given
as polygons. In general a function is needed that can decide if a given
point is on the inside or on the outside of a domain. We will not go
into detail about how such functions can be constructed. It suffice
to say that it is in general a lot simpler to implement an indicator
function for a surface than it is to construct a grid based on the same
surface.
As mentioned above, the boundary conditions on the physical boundaries
will be taken care of by the conductivity tensors. The type of boundary
condition on the artificial boundaries can be either natural or essential,
the choice will not effect the solution on the interior domains.
DISCUSSION
To illustrate the technique we have used a 2D slice of the torso with
realistic endo- and epicardial boundaries as shown in Figure 2. The
domain T in this example is not connected, it consists of the extra
cardiac space plus the two blood cavities of the ventricles. This will
not complicate the computation since only H and
W are relevant for the simulator, both of which are connected and also rectangular
after the embedding.
Figure 3 shows the solution late in the depolarization phase. The non-embedded
reference solution is show at the top. In the finest level of refinement(bottom),
we see that the depolarization sequence is well preserved, which indicates
that the error introduced by the embedding is small, provided that a
fine resolution is used (approximately 400.000 nodes).

Figure 3: Top: The transmembrane potential in the original simulation.
Below: Embedded approach. Two levels of refinement, finest at the
bottom. For comparison, completely unexcited tissue is shown in white.
We note that the technique is also applicable for isolated heart simulations,
both in the mono- and bidomain case. Although the approach simplifies
the implementation there will be computational overhead due to increased
tissue volume.
REFERENCES
[1] C.S. Henriquez, "Simulating the Electrical Behavior of Cardiac Tissue
Using the Bidomain Model",
Critical Reviews in Biomedical Engineering,
vol 21, pp. 1-77, 1993.
[2] R.L. Winslow, D.F. Scollan, A. Holmes, C.K. Yung, J. Zhang , M.S.
Jafri, "Electrophysiological modeling of cardiac ventricular function:
From cell to organ",
Ann Rev Biomded Engng, vol 2, pp. 119-155,
2000.
[3] J. Sundnes, G.T. Lines, A. Tveito, "Efficient solution of ordinary
differential equations modeling electrical activity in cardiac cells",
Math. Biosc., vol 172, pp. 55-72, 2001.
© International Society for Bioelectromagnetism