Biomedical Engineering Reference
In-Depth Information
Note that from Eq. ( 6 ), the interaction of the underlying field C with the
neighboring cells is realized via the function h N . The size of the spatial region of
interaction is a consequence of the choice of our mesoscale, related to the value of
η <
1. Indeed, Eq. ( 37 ) represents an averaging over a large number of cells, at the
level of the mesoscale (given by the size of
η
); furthermore K N converges to a Dirac
δ
-function sufficiently slow, so that we may apply a “law of large numbers” in such
a way that h N (
approaches the limit Eq. ( 38 ). We need to be sure that the sum in
Eq. ( 37 ) is performed over a sufficiently large number of cells, which is equivalent
to say that the range of K N has not to shrink to zero too fast with respect to the
increase of the number of cells.
In the limit the relevant density will satisfy a deterministic evolution equation of
the type
x
,
t
)
Op 1
d s
t
) , C
(
,
) ρ (
,
)
=
(
,
) ρ (
,
)
+
ρ ( ·,
( ·,
) ,
( ·,
)
.
g
z
t
z
t
d z
g
z
0
z
0
d z
s
s
g
s
(39)
D
D
0
This approximated measure then substitutes the random measure Q N (
in the
evolution equations for the underlying fields at the macroscale, so that they are now
completely deterministic
t
)
Op 3
t C
Op 2 [ C
C
(
x
,
t
)=
( ·,
t
)](
x
)+
( ·,
t
) ρ ( ·,
t
)
(
x
)
;
(40)
they may be used to drive the kinetic parameters of the cell processes at the
microscale, thus leading to simple stochastic processes
F C
d Z k
Z k
d W k
(
t
)=
( ·,
t
)
(
(
t
))
d t
+ σ
(
t
) ,,
k
=
1
,...,
N
(
t
) .
(41)
These kind of models are known as hybrid models , since they are stochastic at
the level of individuals Eq. ( 41 ) and deterministic at the level of the field Eq. ( 40 ).
3.1
Tumor-Induced Angiogenesis
Given the evolution equation ( 16 ) for the empirical measure Q N (
, let us observe
that due to the Doob's inequality and Eq. ( 21 ), the quadratic variation of the zero
mean martingale Eq. ( 17 ) is such that
t
)
sup
t
) | F 0 2
2 F 0
M N (
M N (
E
T |
t
4 C
E
|
T
) |
 
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