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DEPTH SENSITIVITY IN DIFFUSE REFLECTANCE SPECTROSCOPY
USING FIBER-OPTIC SENSOR
Akshay Singhal
Project Guide : Dr. N. Sujatha
Bio-photonics Lab , Dept. of Applied Mechanics , Indian Institute of Technology Madras .
Introduction
Bio-optical techniques, particularly diffuse
reflectance spectroscopy (DRS) has applications
in quantitative optical study of tissues, etc.
Knowledge of depth profile of local blood region
(LBR) in skin tissue is important in diagnosis and
treatment, e.g. , in assessing degree of burn.
Present work inquires into depth-sensitivity of
DRS and into optimal source-detector fiber
separation (SDS) for maximum light collection
efficiency (preferential probing) from LBR. It
models an approach based on varying SDS for
estimating depth of LBR in skin.
Determining optimal SD separation
Skin tissue modeling
Simulation results of 4-layer model and
depth-estimation
Conclusion and Future Scope
References
4-layer skin
tissue model
epidermis (melanin)
local blood region (hemoglobin)
depth
source
fiberdetector fibers at
varying SDS
Fig. 1 : Problem statement schematized
perfused dermis
perfused dermis
Yunhan Luo’s [1] analysis for determining optimal
SDS for measuring chromophores in sandwiched
layer, based on Monte-Carlo simulation (MCS)
[2] of mean penetration-depth (mpd) profile of
reflectance, has been extended by varying the
depth of the sandwiched layer .
The SDS values shown in Fig. 2 and Fig. 3 are
matching , indicating optimality of that SDS for
preferential probing into sandwiched layer and
usefulness of mpd in depth-sensitivity of DRS.
Layer n μa [cm-1] μs [cm-1] gthickness
[cm]
1 1.37 4.5 140 0.873 varying
2 1.37 10 140 0.873 0.01
3 1.37 1.8 92 0.873 10
Table 1 : Optical parameters input to MCS
Fig. 2 : mpd v/s SDS
Fig. 3 : profile of fractional reflectance from chromophore region.
Skin’s multi-layered structure and local blood
region has been lumped into 4-layer model
(Fig. 1). Optical properties (μa, μs, g, n) (Fig. 4)
and structural configuration for each layer were
taken from sources [3] and using in-vivo
reflectance measurements of palm skin.
Blood volume % in perfused dermis was fixed at
2% after profile-matching task (Fig. 5 and Fig. 6).
Fig. 4 : Absorption coefficients (4-layer model)
Fig. 5 : Experimental setup for profile matching between simulated and
measured reflectance spectrum at 1.1 mm SDS
SDS = 1.1mm
palm
Fig. 6 : Profile-match between experimental and simulated reflectance
‘mpd profile v/s SDS’ of 4-layer model, for varying
depth of blood and λ=540 nm, is shown in Fig. 7.
It can be used for further optimal SDS analysis.
Spatially-resolved diffuse reflectance intensity
profile for varying depth of blood and λ=540 nm is
shown in (Fig. 8). It is clear that slope of this
curve (Fig. 9) is a depth-indicative feature.
Fig. 7 : mpd profile (4-layer model) at λ=540nm
Fig. 8 : diffuse reflectance v/s SDS at λ=540nm
Fig. 9 : depth-indicative feature (slope of Rd (r) v/s SDS)
In Fig. 9 , slope varies drastically for the case of
λ=540 nm and 580 nm because of strong
absorption of blood , while very marginally for the
case of 620 and 660 nm. This simulated slope
profile can be used for depth-estimation of LBR.
4-layer model of skin tissue with local blood
region, and its simulated mpd profile for varying
depth of LBR which is indicative of optimal SDS
for max collection efficiency from LBR, can be
used for future studies on depth-estimation of
local blood region in skin.
Depth-indicative feature, slope (Fig. 9) can be
used for estimating depth of LBR by quantitative
matching with slope obtained experimentally.
Experimental validation of depth-indicativeness
of slope feature using model-mimicking phantom
shall ready the approach to be used on skin.
[1] Luo, Y., Cui, H., Gu, X., Liu, R., & Xu, K. (2005). “Determination of
optimal source-detector separation in measuring chromophores in
layered tissue with diffuse reflectance.” Chinese Optics Letters, 3(11),
659-661.
[2] Wang, L., Jacques, S. L., & Zheng, L. (1995). “MCML—Monte Carlo
modeling of light transport in multi-layered tissues.” Computer
methods and programs in biomedicine, 47(2), 131-146.
[3] Nishidate, I., Maeda, T., Aizu, Y., & Niizeki, K. (2007). “Visualizing
depth and thickness of a local blood region in skin tissue using
diffuse reflectance images.” Journal of Biomedical optics, 12(5),
054006-054006.