A common task in the analysis of digitized histological sections is reconstructing a volumetric representation
of the original specimen. Image registration algorithms are used in this task to compensate for translational,
rotational, scale, shear, and local geometric differences between slices. Various systems have been developed
to perform volumetric reconstruction by registering pairs of successive slices according to rigid, similarity,
affine, and/or deformable transformations. To provide a coarse initial volumetric reconstruction, rigid
transformations may be too constrained, as they do not allow for scale or shear; but, affine transformations may
be too flexible, enabling larger scale or shear factors than physically reflected in the histological sections.
One difficulty with these systems is caused by the aperture problem; even if successive slices are registered
reasonably well, the composition of transformations over tens or hundreds of slices can yield global twisting and
scale and shear changes that yield a volumetric reconstruction that is significantly distorted from the shape of
the true specimen. The impact of the aperture problem can be reduced by considering more than two successive
images in the registration process. Systems that take this approach use global energy functions, elastic spring
models, post hoc filtering/smoothing, or solutions to shortest-path problems on graphs.
In this article, we propose a volume reconstruction algorithm that handles the aperture problem and yields
nearly rigid transformations (i.e., affine transformations with small scale and shear factors). Our algorithm is
based on robust geometric alignment of descriptive feature points (for example, using SIFT16) via constrained
optimization. We will illustrate our algorithm on the task of volumetric reconstruction from histological sections
of a chicken embryo with an embedded tumor spheroid.
Non-invasive tumor microvasculature visualization and characterization play significant roles in the detection of tumors
and importantly, for aiding in the development of therapeutic strategies. The feasibility and effectiveness of a Doppler
variance standard deviation imaging method for tumor angiogenesis on chorioallantoic membrane were tested in vivo on
a rat glioma F98 tumor spheroid. Utilizing a high resolution Doppler Variance Optical Coherence Tomography
(DVOCT) system with A-line rate of 20 kHz, three-dimensional mapping of a tumor with a total area of 3×2.5mm2 was
completed within 15 seconds. The top-view image clearly visualized the complex vascular perfusion with the detection
of capillaries as small as approximately 10μm. The results of the current study demonstrate the capability of the Doppler
variance standard deviation imaging method as a non-invasive assessment of tumor angiogenesis, with the potential for
its use in clinical settings.
An in-vivo tumor model composed of multicellular human glioma spheroids implanted on a shell-less chorioallantoic
membrane (CAM), has been developed. Following removal of a portion of the ectodermal epithelium layer of the CAM,
human glioma spheroids were implanted on day 7 of embryonic development. Tumor invasion, rapid growth and
vasculature formation were observed 7 days post implantation. Single tumor cell migration towards blood vessels,
angiogenesis and satellite tumor growth were also evident.
The human tumor/CAM model is being used to examine the effects of combined ALA PDT and anti-angiogenic agents.
The shell-less CAM is well suited for topical, i.p. and i.v. photosensitizer and/or drug application.
An in vivo shell-less chick chorioallantoic membrane (CAM) brain tumor model has been developed to investigate the effects of photodynamic therapy (PDT) and anti-antiogenic treatments. Multicellular human glioma spheroids were placed on the CAM at day 7 of embryonic development. Angiogenesis was observed four days post implantation. Significant damage to the CAM vasculature was observed immediately following 5-aminolevulinic acid (ALA) mediated PDT.
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