1. No category

OptogenSIM includes the simulation code, generic tissue models, and defined tissue type atlases.
The workflow of this simulation platform is shown below
Prepare the simulation parameters and
data using Matlab code (including light
delivery parameters, generic tissue
library, and 3D brain tissue atlas)
Conduct 3D Monte Carlo
simulation using
standard C code
View the simulation
results using Matlab code
If the simulations used the atlases provided here, then only need to import the atlas
without need for further segmentation. The 3D volume can be viewed using e.g.
SPMMOUSE software.
For simulation on other 3D rodent brain atlases, the brain tissue first needs to be
segmented into tissue types e.g. GM, WM, and CSF. The two priors atlases introduced
here can be used as the templates to help segment individual 3D brain images with
SPM software.
Schematic of light delivery simulation on the 3D Monte Carlo platform
1 Simulation code
The fundamental codes are available from http://omlc.org/software/mc/mcxyz/.
The codes used in this simulation platform are adapted from them and will be uploaded in the
future.
2 Generic tissue models for gray matter and white matter1
The reduced scattering coefficient can be modeled as1
( )
(
(
(
)
)
(
)(
1
(
)
)
),
(1)
where the scaling factor is
(
total
(
)
= (
), the Rayleigh scattering is
) , and the Mie scattering is
(
)(
(
)
)
. The
absorption coefficient can be modeled as1
(
)
, (2)
where S is Hemoglobin (HGb) oxygen saturation of mixed arterio-venous vasculature, B is
average blood volume fraction, W is water content, F is fat content volume fraction, M is
melanosome volume fraction,
deoxygenated whole blood,
concentration(C(M)),
indicates the oxygenated whole blood,
is bilirubin concentration (C(M)),
indicates
-carotene
is the extinction coefficients. The absorption spectrum for each absorber
is from OMLC website. 2 Table 1 and 2 list the parameters for the tissue models which can be
added to the tissue library to conduct simulation.
Table 1 Parameters of generic tissue models of the reduced scattering coefficient defined in Eq.1
#
Tissue
Data reference
[Gottschalk(1992)4,
Yaroslavsky(2002)3]
2
gray matter
12.61
0.00
1.20
Yaroslavsky(2002) 3
3
gray matter
24.59
0.10
1.00
*
4
gray matter(average)
22.92
0.033
1.067
*
5
white matter
71.23
0.00
1.00
[Gottschalk(1992) 4,
Yaroslavsky(2002) 3]
6
white matter
82.71
0.00
1.18
Yaroslavsky(2002) 3
7
white matter
52.82
0.00
1.00
*
8
white matter(average)
68.92
0.00
1.06
*
*: Obtained from this work, Gottschalk(1992) is the work indirectly cited by Yaroslavsky(2002) 3,
Yaroslavsky(2002) is the work by Yaroslavsky.et al. 3
1
gray matter
3
31.56
0
2
1.00
Table 2 Parameters of generic tissue models specifying the absorption coefficient defined in Eq. 2
# Tissue
B%
S%
W%
Data reference
1 gray matter
6.49
0
70.69
[Gottschalk(1992) 4,
Yaroslavsky(2002) 3]
2 gray matter
0.14
0.63
79.99
Yaroslavsky(2002) 3
3 gray matter
0.66
0.01
80
*
4 gray matter(average)
0.21
76.89
*
2.43
5 white matter
3.93
38.55
80
[Gottschalk19924,
Yaroslavsky(2002) 3]
6 white matter
0.41
76.67
80
Yaroslavsky(2002) 3
7 white matter
0.40
0
80
*
8 white matter(average)
1.58
38.41
80
*
4
3
*: Obtained from this work, Gottschalk(1992) is the work cited by Yaroslavsky(2002) , Yaroslavsky(2002) 3 is
the work by Yaroslavsky.et al3.
3 Defined brain atlases
The defined tissue type atlas will be able to be downloaded here. However, the original ones
should be directly request from the authors of the atlases.
3.1 a 3D average mouse brain tissue type atlas: the original average brain atlas5 was based on ex vivo
brain magnetic resonance imaging(MRI) of 47 R6/2 transgenic and 42 wild type (WT) mice at 18 weeks
of age and was included in the software package SPMMouse.5,6
3.2 a 3D average rat brain tissue atlas: the original average rat brain atlas was based on in vivo rat T2
MRI images for thirty Wistar rats at (6, 7, 8, 9, 10) weeks of age.7
3.3 a 3D single mouse brain tissue atlas: the original atlas is based a representative ex-vivo adult male
C57BL/6J mouse brain atlas selected from a comprehensive digital atlas database based on magnetic
resonance microscopy images.8
An user interface will be developed in the future to early use the above
Reference
1. Jacques, S. L. Optical properties of biological tissues: a review. Phys. Med. Biol. 58, R37 (2013).
2. The Oregon Medical Laser Center (OMLC) at OHSU. at <http://omlc.ogi.edu/news/aboutOMLC.index>
3. Yaroslavsky, A. N. et al. Optical properties of selected native and coagulated human brain tissues in
vitro in the visible and near infrared spectral range. Phys. Med. Biol. 47, 2059 (2002).
4. Gottschalk, W. Ein Messverfahren zur Bestimmung der Optischen Parameter biologischer Gewebe in
vitro Dissertation 93 HA8984 Universitaet Fridriciana. (1992).
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5. Sawiak, S. J., Wood, N. I., Williams, G. B., Morton, A. J. & Carpenter, T. A. Voxel-based morphometry
in the R6/2 transgenic mouse reveals differences between genotypes not seen with manual 2D
morphometry. Neurobiol. Dis. 33, 20–27 (2009).
6. Sawiak, S. SPM Mouse. SPMMouse at <http://www.spmmouse.org/>
7. Valdés-Hernández, P. A. et al. An in vivo MRI template set for morphometry, tissue segmentation,
and fMRI localization in rats. Front. Neuroinformatics 5, (2011).
8. Ma, Y. et al. A three-dimensional digital atlas database of the adult C57BL/6J mouse brain by
magnetic resonance microscopy. Neuroscience 135, 1203–1215 (2005).
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