Fluorescence imaging modalities are currently a routine tool for the assessment of marker distribution within biological tissues, including monitoring of fluorescent photosensitizers (PSs) in photodynamic therapy (PDT). Conventional fluorescence imaging techniques provide en-face two-dimensional images, while depth-resolved techniques require complicated tomographic modalities. In this paper, we report on a cost-effective approach for the estimation of fluorophore localization depth based on dual-wavelength probing. Owing to significant difference in optical properties of superficial biotissues for red and blue ranges of optical spectra, simultaneous detection of fluorescence excited at different wavelengths provides complementary information from different measurement volumes. Here, we report analytical and numerical models of the dual-wavelength fluorescence imaging of PS-containing biotissues considering topical and intravenous PS administration, and demonstrate the feasibility of this approach for evaluation of the PS localization depth based on the fluorescence signal ratio. The results of analytical and numerical simulations, as well as phantom experiments, were translated to the in vivo imaging to interpret experimental observations in animal experiments, human volunteers, and clinical studies. The proposed approach allowed us to estimate typical accumulation depths of PS localization which are consistent with the morphologically expected values for both topical PS administration and intravenous injection.

The aim of the study was to assess the capabilities of combined application of dual-wavelength fluorescence visualization and contactless skin thermometry during photodynamic therapy monitoring (PDT) of basal cell cancer. Materials and Methods. The study was performed at the University Clinic of Privolzhsky Research Medical University (Nizhny Novgorod). Nine clinically, dermatoscopically, and histologically verified foci of basal cell skin cancer were exposed to PDT sessions (wavelength of 662 nm, light dose density of 150 J/cm 2 ) with systemic application of chlorin-based photosensitizer Fotoditazin. A semiconductor laser system Latus-T (Russia) was employed for irradiation. Dual-wavelength fluorescence visualization and contactless thermometry with an IR pyrometer were used to monitor the PDT sessions. Results. The PDT sessions of nine foci of basal cell cancer were carried out under the control of fluorescence imaging and contactless thermometry. Photosensitizer photobleaching in all foci amounted to 40% signifying a percent of photosensitizer involved in the photodynamic reaction. It has been shown that the combined employment of dual-wavelength fluorescence monitoring and contactless thermometry during the PDT of basal cell skin cancer allows oncologists to control simultaneously the degree of photosensitizer photobleaching and the depth of the photodynamic effect in tissues, the extent of involving the mechanisms associated with hyperthermia as well as the correctness of the procedure conducting. In the course of 9-month dynamic follow-up after the treatment, no clinical and dermatoscopic signs of recurrence were found. Conclusion. A bimodal control of PDT enables the assessment of the correctness and efficacy of the procedure performance. The contactless control of tissue heating allows ensuring the temperature mode for hyperthermia realization, while the fluorescence monitoring makes it possible to evaluate the accumulation of the photosensitizer in the tumor and the depth of the PDT action as well as to predict the procedure efficacy based on the photobleaching data. The complementary use of these techniques allows the adjustment of the mode directly in the course of the PDT procedure. The acquisition of the sufficient statistical data on the combined monitoring will result in the development of a novel PDT protocol.

Artificial intelligence is a term used to describe computer technology in the modeling of intelligent behavior and critical thinking comparable to that of humans. To date, some of the first areas of medicine to be influenced by advances in artificial intelligence technologies will be those most dependent on imaging. These include ophthalmology, radiology, and dermatology. In connection with the emergence of numerous medical applications, scientists have formulated criteria for their assessment. This list included: clinical validation, regular application updates, functional focus, cost, availability of an information block for specialists and patients, compliance with the conditions of government regulation, and registration. One of the applications that meet all the requirements is the ProRodinki software package, developed for use by patients and specialists in the Russian Federation. Taking into account a widespread and rapidly developing competitive environment, it is necessary to soberly treat the resources of such applications, not exaggerating their capabilities and not considering them as a substitute for a specialist.

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