The goal of this study is a comparative analysis of the efficiency of the PDT protocols for CT26 tumor model treatment in Balb/c mice employing red and blue light with both topical and intravenous administration of chlorin-based photosensitizers (PSs). The considered protocols include the doses of 250 J/cm2 delivered at 660 nm, 200 J/cm2 delivered at 405 nm, and 250 J/cm2 delivered at both wavelengths with equal energy density contribution. Dual-wavelength fluorescence imaging was employed to estimate both photobleaching efficiency, typical photobleaching rates and the procedure impact depth, while optical coherence tomography with angiography modality (OCT-A) was employed to monitor the tumor vasculature response for up to 7 days after the procedure with subsequent histology inspection. Red light or dual-wavelength PDT regimes with intravenous PS injection were demonstrated to provide the most pronounced tumor response among all the considered cases. On the contrary, blue light regimes were demonstrated to be most efficient among topical application and irradiation only regimes. Tumor size dynamics for different groups is in good agreement with the tumor response predictions based on OCT-A taken in 24h after exposure and the results of histology analysis performed in 7 days after the exposure.
We present a laser resection technique to be used when biotissue is heated by laser radiation to the temperature of material softening and then moved apart by the lateral edge of the optical fiber with a strongly absorbing tip. The absorbing tip allows the decrease in the power of effective cutting of the laser scalpel at the wavelength of 0.97 µm. And it changes the resection speed as well as the characteristics of the damage of the tissues adjacent to the incision in experiments on model media and experimental animals.
Chronic rhinitis (CR) is among the most frequent inflammatory diseases of ear-nose-throat (ENT) covering up to 30% of the population. Different forms of CR require different treatment tactics, which indicates the need for an efficient tool for differential diagnostics of CR. Optical coherence tomography (OCT) is a promising tool for fast non-invasive evaluation of nasal mucosa, which, however, requires further interpretation of the obtained diagnostic image. In this paper, we provide a comparative analysis of several machine learning approaches that aim at automated differential diagnostics of CR based on diagnostic OCT images of 78 patients aged between 28 and 74 ages. Gradient boosting decision trees (GBT) approach reveals the best classification accuracy (98% and 94% for binary and diagnostic classification, respectively). It shows that proposed approaches have potential for automated classification of CR OCT images.
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