Abstract: Microbubbbles incorporating ultrasound have been used to increase the efficacy of targeted drug delivery, because microstreaming induced by cavitating bubbles affects the drug perfusion into the target cells and tissues. In order to clarify the physical effects of microstreaming on drug perfusion into tissues, a preliminary experimental study of perfusion enhancement by a stably oscillating microbubble was performed. Microstreaming was induced by an oscillating bubble at 15 kHz, and perfusion of dye into an agar phantom was optically measured by histology on agar phantom. Surface color intensity and the penetration length of dye in the agar phantom were increased more than 70% and 30%, respectively, due to the microstreaming induced by an oscillating bubble. The mass of dye perfused into a tissue phantom for 30 s was increased about 80% in the phantom with an oscillating bubble. This preliminary experiment shows the physical effects of steady streaming by an oscillating bubble can enhance the drug perfusion into the tissues while minimizing the biological effects.
Abstract: Fourier transform infrared (FT-IR) spectroscopic imaging
is an emerging technique that provides both chemically and
spatially resolved information. The rich chemical content of data
may be utilized for computer-aided determinations of structure and
pathologic state (cancer diagnosis) in histological tissue sections for
prostate cancer. FT-IR spectroscopic imaging of prostate tissue has
shown that tissue type (histological) classification can be performed to
a high degree of accuracy [1] and cancer diagnosis can be performed
with an accuracy of about 80% [2] on a microscopic (≈ 6μm)
length scale. In performing these analyses, it has been observed
that there is large variability (more than 60%) between spectra from
different points on tissue that is expected to consist of the same
essential chemical constituents. Spectra at the edges of tissues are
characteristically and consistently different from chemically similar
tissue in the middle of the same sample. Here, we explain these
differences using a rigorous electromagnetic model for light-sample
interaction. Spectra from FT-IR spectroscopic imaging of chemically
heterogeneous samples are different from bulk spectra of individual
chemical constituents of the sample. This is because spectra not
only depend on chemistry, but also on the shape of the sample.
Using coupled wave analysis, we characterize and quantify the nature
of spectral distortions at the edges of tissues. Furthermore, we
present a method of performing histological classification of tissue
samples. Since the mid-infrared spectrum is typically assumed to
be a quantitative measure of chemical composition, classification
results can vary widely due to spectral distortions. However, we
demonstrate that the selection of localized metrics based on chemical
information can make our data robust to the spectral distortions
caused by scattering at the tissue boundary.