Tissue diagnostic features generated by a bimodal technique integrating scanning time-resolved fluorescence spectroscopy (TRFS) and ultrasonic backscatter microscopy (UBM) are investigated in an in vivo hamster oral carcinoma model. Tissue fluorescence is excited by a pulsed nitrogen laser and spectrally and temporally resolved using a set of filters/dichroic mirrors and a fast digitizer, respectively. A 41-MHz focused transducer (37-μm axial, 65-μm lateral resolution) is used for UBM scanning. Representative lesions of the different stages of carcinogenesis show that fluorescence characteristics complement ultrasonic features, and both correlate with histological findings. These results demonstrate that TRFS-UBM provide a wealth of co-registered, complementary data concerning tissue composition and structure as it relates to disease status. The direct co-registration of the TRFS data (sensitive to surface molecular changes) with the UBM data (sensitive to cross-sectional structural changes and depth of tumor invasion) is expected to play an important role in pre-operative diagnosis and intra-operative determination of tumor margins.
KEYWORDS: Animal model studies, Tissues, 3D modeling, Finite element methods, Diffusion, Sensors, Bioluminescence, Fluorescence tomography, Optical properties, Data modeling
The forward problem of optical bioluminescence and fluorescence tomography seeks to determine, for a given
3D source distribution, the photon density on the surface of an animal. Photon transport through tissues is
commonly modeled by the diffusion equation. The challenge, then, is to accurately and efficiently solve the
diffusion equation for a realistic animal geometry and heterogeneous tissue types. Fast analytical solvers are
available that can be applied to arbitrary geometries but assume homogeneity of tissue optical properties and
hence have limited accuracy. The finite element method (FEM) with volume tessellation allows reasonably
accurate modeling of both animal geometry and tissue heterogeneity, but this approach is computationally
intensive. The computational challenge is heightened when one is working with multispectral data to improve
source localization and conditioning of the inverse problem. Here we present a fast forward model based on
the Born approximation that falls in between these two approaches. Our model introduces tissue heterogeneity
as perturbations in diffusion and absorption coefficients at rectangular grid points inside a mouse atlas. These
reflect as a correction term added to the homogeneous forward model. We have tested our model by performing
source localization studies first with a biolumnescence simulation setup and then with an experimental setup
using a fluorescent source embedded in an inhomogeneous phantom that mimicks tissue optical properties.
Atlases are normalized representations of anatomy that can provide a standard coordinate system for in vivo
imaging studies. For Optical Bioluminescence Tomography (OBT) in small animals, the animal's surface topography
can be reconstructed from structured light measurements, but internal anatomy is unavailable unless
additional CT or MR images are acquired. We present a novel method for estimating the internal organ structure
of a mouse by warping a labeled 3D volumetric mouse atlas with the constraint that the surfaces of the two
should match. Surface-constrained harmonic maps used for this bijective warping are computed by minimizing
the covariant harmonic energy. We demonstrate the application of this warping scheme in OBT, where scattering
and absorption coefficients of tissue are functions of the internal anatomy and hence, better estimates
of the organ structures can lead to a more accurate forward model resulting in improved source localization.
We first estimated the subject's internal geometry using the atlas-based warping scheme. Then the mouse was
tessellated and optical properties were assigned based on the estimated organ structure. Bioluminescent sources
were simulated, an optical forward model was computed using a finite-element solver, and multispectral data
were simulated. We evaluate the accuracy of the forward model computed using the warped atlas against that
assuming a homogeneous mouse model. This is done by comparing each model against a 'true' optical forward
model where the anatomy of the mouse is assumed known. We also evaluate the impact of anatomical alignment
on bioluminescence source localization.
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