Photodynamic therapy (PDT) is one of the most promising methods for tumor treatment based on the activation of a photosensitizer (PS) with laser radiation to selectively eliminate pathological cells. The fluorescence properties of the PS can be used to evaluate PDT efficacy by monitoring photobleaching, which is measured through changes in fluorescence intensity within the laser exposed area. Accurate tracking of the region-of-interest is necessary since the pathological region may shift due to patient movement during the PDT procedure. This process is complicated by foreign objects within the imaging area and the progressive decrease in fluorescence intensity during laser exposure, which together hinder precise fluorescence intensity assessment. This study aims at developing a novel approach for fluorescence imaging PDT monitoring consisting in choosing a combination of probing wavelength and tracking algorithm. To reach this aim we compared several existing approaches and developed a specialized software tool for implementing and testing tracking algorithms on different image series: fluorescence (405 nm, 660 nm excitation) and backscattered light. Using a database of clinical PDT and phantom study results, we compared the efficiency of standard tracking algorithms: Median Flow, Tracking Learning Detection, Minimum Output Sum of Squared Error, and Channel and Spatial Reliability Tracker. The analysis revealed that the optimal approach for tracking the pathological area is to use 660 nm image series with the CSRT algorithm, enhanced by automatic reinitialization for occlusion recovery. The developed software facilitates individualized laser dose adjustment and improves PDT efficacy by providing reliable, automated assessment of PS photobleaching.

Reconstruction of biotissue optical properties from spatially resolved fiber optic diffuse reflectance spectroscopy (DRS) measurements requires a fast and accurate solution of the forward problem of light transport for a specified DRS configuration. In this study we report on comparative analysis of three analytical models of diffuse reflectance (Green’s function, a model proposed by Farrell et al (1992), and a refined model proposed by Sergeeva et al (2024)) with the Monte Carlo-simulated reflectance in extensive range of optical parameters. The refined model demonstrates the best accuracy among all three analytical models for source-detector distances (SDDs) exceeding 2 mm. A semi-analytical fit of massive MC reflectance is proposed which possesses a discrepancy of less than 2% in the entire range of considered absorption and scattering and at SDDs below 2 mm. The accuracy of chromophore concentration recovery from MC simulated spectra of reflectance for a medium mimicking dermis is evaluated for all the discussed models.

Theoretical models of lidar echo signals, which are formed when probing seawater with laser pulses modulated by a broadband high-frequency signal with the use of matched detection (for "compression" of the modulating signal), have been developed. The models are suitable for calculating elastic backscattering signals and fluorescence echo signals; they are constructed based on analytical solutions of the radiation transfer equation in the small-angle approximation. The elastic backscattering signal model has been verified using Monte Carlo statistical simulations. It has been shown that the considered probing method will allow recording vertical profiles of optically active substances contained in water with the same spatial resolution as the ultrashort pulse probing method, however, with lower probing power.

We report on the development of Monte Carlo based models of signal formation in systems of spectral and fluorescence imaging. Numerical simulations allow tracking photon trajectories providing imaging volume analysis, while parallel processor architecture allows to significantly speed up calculations.

From March to June 2022, Shanghai was struck by a new coronavirus variant, Omicron, resulting in the infected cases of at least 600,000 people. Despite implementing a strict containment policy of city-wide silence (i.e., residents were not allowed to go out unless necessary), the outbreak cannot be effectively prevented within a short period of time. A significant academic and practical question is: how could we prevent and control outbreak of COVID-19 in large, densely populated cities like Shanghai? It is necessary to develop a rational epidemic spreading model for large cities, in order to accurately predict the trend of disease and quantitatively assess the impact of non-pharmaceutical interventions. In this paper, a multilayer commuter metapopulation network model is constructed to capture commuting flows and the size of epidemic outbreak during commuting between districts. The model accurately predicts epidemic spreading in each district of Shanghai. Assuming strict city-wide lockdowns, with each district locked down and limited inter-district commuting as social zones, simulations demonstrate significant suppression of outbreaks due to social-level interventions. For example, a 1-fold increase in PCR (Polymerase Chain Reaction) testing efficiency reduces the size of epidemic outbreak by approximately 70%. Larger districts require stricter controls to prevent exponential growth. Lockdowns effectively prevent epidemic outbreak at low disease rates but less so at high rates. Liberalized policies lead to varied outbreak trends, with economically developed regions peaking earlier due to higher population densities. This study provides a comprehensive framework for quantitatively evaluating the impact of social and regional controls on urban epidemics.

The results of statistical modeling of the backscatter signal in lidars when probing the water column with pulses with internal modulation by complex frequency modulated signals and their matched processing in the receiving path of the lidar are presented. The simulation results are compared with analytical calculations in the small-angle approximation. It is shown that the photons spread along their paths, associated with multiple scattering in the medium, does not prevent effective compression of the complex signal, and the small-angle approximation well describes the energy-carrying part of the signal backscattered by the water column. A comparison was made of the levels of backscatter signals when probing water with a short pulse and a complexly modulated pulse. It is shown that the use of complexly modulated illumination pulses makes it possible to reduce the power emitted by the source while maintaining the level of the backscattering signal in the lidar and its range resolution. Calculations of the levels of the signal backscattered by a localized diffusely reflecting object are performed and it is shown that at a delay value corresponding to the arrival time of ballistic photons, the compressed pulse is not distorted. At long delay times, a pulse tail is formed due to the spread of photons along their paths. An example of calculating the backscattering pulse in the presence of a non-reflecting object in the water is given.

In this paper, we report on a study regarding the efficiency of the post-operational phototherapy of the tumor bed after resection with both a cold knife and a laser scalpel in laboratory mice with CT-26 tumors. Post-operational processing included photodynamic therapy (PDT) with a topically applied chlorin-based photosensitizer (PS), performed at wavelengths of 405 or 660 nm, with a total dose of 150 J/cm2. The selected design of the tumor model yielded zero recurrence in the laser scalpel group and 92% recurrence in the cold knife group without post-processing, confirming the efficiency of the laser scalpel in oncology against the cold knife. The application of PDT after the cold knife resection decreased the recurrence rate to 70% and 42% for the 405 nm and 660 nm procedures, respectively. On the other hand, the application of PDT after the laser scalpel resection induced recurrence rates of 18% and 30%, respectively, for the considered PDT performance wavelengths. The control of the penetration of PS into the tumor bed by fluorescence confocal microscopy indicated the deeper penetration of PS in the case of the cold knife, which presumably provided deeper PDT action, while the low-dose light exposure of deeper tissues without PS, presumably, stimulated tumor recurrence, which was also confirmed by the differences in the recurrence rate in the 405 and 660 nm groups. Irradiation-only light exposures, in all cases, demonstrated higher recurrence rates compared to the corresponding PDT cases. Thus, the PDT processing of the tumor bed after resection could only be recommended for the cold knife treatment and not for the laser scalpel resection, where it could induce tumor recurrence.

Dual-wavelength photodynamic therapy (PDT) in combination with fluoescence monitoring has great potential in medical applications, in particular, in the treatment of skin diseases. In this study we conducted numerical Monte Carlo experiments in a two-layer skin model to simulate the absorbed light dose distribution for PDT with chlorin-based photosensitizers as well as to estimate the fluorescence imaging depth depending on the probing radiation wavelength and the photosensitizer (PS) in-depth distribution. The obtained dependencies provide a detailed overview of the light absorption profile and fluorescence signal formation for different PS distribution in layered biotissues, and can be used in various fluorescence based light dosimetry techniques.

We report on the results of a simulation of the photon density waves with pulse amplitude modulation by a complex frequency modulated signal. The problem is considered for the optical properties typical for sea water with anisotropy factor values varying from 0.75 to 0.93 at source-detector distances up to 120 m. It is shown that multiple scattering in a medium does not prevent effective compression of a signal registered using matched detection. Two competing phenomena affecting the detected pulse duration and depending on the central frequency of the modulation signal are discussed. The effect of faster attenuation of high harmonics in a complexly modulated signal leads to the detected signal duration increase as a consequence of multiple scattering. On the other hand, anomalous dispersion of photon density waves in media with scattering anisotropy leads to the pulse self-compression. The simulation results presented in the paper demonstrate the prevalence of different phenomena depending on the central frequency of the modulation signal resulting in a pulse duration decrease or increase in different frequency ranges covering the band from 107 to 2 109 Hz. The effect of the phase function shape on the observed effect is also discussed. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

Relevance. To investigate the characteristics of the COVID-19 pandemic and introduce timely and effective measures, there is a need for models that can predict the impact of various restrictive actions or characteristics of disease itself on COVID-19 spread dynamics. Employing agent-based models can be attractive because they take into consideration different population characteristics (e.g., age distribution and social activity) and restrictive measures, laboratory testing, etc., as well as random factors that are usually omitted in traditional modifications of the SIR-like dynamic models. Aim. Improvement of the previously proposed agent-based model [23,24] for modeling the spread of COVID-19 in various regions of the Russian Federation. At this stage, six waves of the spread of COVID-19 have been modeled in the Nizhny Novgorod region as a whole region, as well as in its individual cities, taking into account restrictive measures and vaccination of the population. Materials and Methods. In this paper we extend a recently proposed agent-based model for Monte Carlo-based numerical simulation of the spread of COVID-19 with consideration of testing and vaccination strategies. Analysis is performed in MATLAB/ GNU Octave. Results. Developed multicentral model allows for more accurate simulation of the epidemic dynamics within one region, when a patient zero usually arrives at a regional center, after which the distribution chains capture the periphery of the region due to pendulum migration. Furthermore, we demonstrate the application of the developed model to analyze the epidemic spread in the Nizhny Novgorod region of Russian Federation. The simulated dynamics of the daily newly detected cases and COVID-19-related deaths was in good agreement with the official statistical data both for the region as whole and different periphery cities. Conclusions. The results obtained with developed model suggest that the actual number of COVID-19 cases might be 1.5–3.0 times higher than the number of reported cases. The developed model also took into account the effect of vaccination. It is shown that with the same modeling parameters, but without vaccination, the third and fourth waves of the epidemic would be united into one characterized by a huge rise in the morbidity rates and the occurrence of natural individual immunity with the absence of further pandemic waves. Nonetheless, the number of deaths would exceed the real one by about 9–10 times.

The effects of cytotoxic chemotherapy on tumor vasculature and oxygenation are in the focus of modern investigations because vascular structure and distribution of oxygen influence tumor behavior and treatment response. The aim of our study was to monitor changes in the vascular component of colorectal tumor xenografts induced by a clinical combination of chemotherapy drugs FOLFOX in vivo using two complementary techniques: diffuse reflectance spectroscopy (DRS) and optical coherence tomography-based microangiography (OCT-MA). These techniques revealed a slower decrease in tumor blood oxygenation in treated tumors as compared to untreated ones, faster suppression of tumor vasculature perfusion and increase in water content as a result of treatment, and decrease in total hemoglobin in untreated tumors. Immunohistochemical analysis of hypoxia-inducible factor HIF-2α detected tissue hypoxia as a consequence of inappropriate oxygen supply in the treated tumors. The obtained results show the prospects for monitoring of treatment efficacy using DRS and OCT-MA.

A refined analytical model of spatially resolved diffuse reflectance with small source-detector separations (SDSs) for the in vivo skin studies is proposed. Compared to the conventional model developed by Farrell et al., it accounts for the limited acceptance angle of the detector fiber. The refined model is validated in the wide range of optical parameters by Monte Carlo simulations of skin diffuse reflectance at SDSs of units of mm. Cases of uniform dermis and two-layered epidermis-dermis structures are studied. Higher accuracy of the refined model compared to the conventional one is demonstrated in the separate, constraint-free reconstruction of absorption and reduced scattering spectra of uniform dermis from the Monte Carlo simulated data. In the case of epidermis-dermis geometry, the recovered values of reduced scattering in dermis are overestimated and the recovered values of absorption are underestimated for both analytical models. Presumably, in the presence of a thin mismatched topical layer, only the effective attenuation coefficient of the bottom layer can be accurately recovered using a diffusion theory-based analytical model while separate reconstruction of absorption and reduced scattering fails due to the inapplicability of the method of images. These findings require implementation of more sophisticated models of light transfer in inhomogeneous media in the recovery algorithms.

We studied grafted tumors obtained by subcutaneous implantation of kidney cancer cells into male white rats. Gold nanorods with a plasmon resonance of about 800 nm were injected intratumorally for photothermal heating. Experimental irradiation of tumors was carried out percutaneously using a near-infrared diode laser. Changes in the optical properties of the studied tissues in the spectral range 350-2200 nm under plasmonic photothermal therapy (PPT) were studied. Analysis of the observed changes in the absorption bands of water and hemoglobin made it possible to estimate the depth of thermal damage to the tumor. A significant decrease in absorption peaks was observed in the spectrum of the upper peripheral part and especially the tumor capsule. The obtained changes in the optical properties of tissues under laser irradiation can be used to optimize laboratory and clinical PPT procedures.

We report on creation of a diffuse optical spectroscopy (DOS) setup in a wide VIS-NIR spectral range with a contact fiber-optic probe using a self-calibration technique. A four measurement procedure employing two source and two collection fibers arranged symmetrically allows to calculate extinction spectrum of investigated tissue, excluding DOS instrumental characteristics and reducing the influence of absorption inhomogeneities on a tissue surface. High accuracy of a measured extinction spectra allows one to account for more tissue chromophores and precisely assess tissue physiological properties. The proposed system was applied successfully in preliminary in vivo studies.

Many intervention strategies, such as patient isolation and contact tracking, had been implemented in different countries to slow down and control the spread because of the enormous threats and losses caused by COVID-19. Since the contact relationships of millions of people within cities change over time, it is difficult to accurately predict the dynamics of large-scale outbreaks and evaluate the impact of the contact tracking and isolation strategy based on individual contact history on epidemic transmission. Here, we propose a non-markov spreading model based on individual contact dynamic network, to simulate the dynamic contact processes in a city with millions of people. In this model, the historical contact population of each infected person can be backtracked and tracked. Our model can accurately describe the COVID-19 epidemic in Wuhan and Hong Kong. We assess the impact of four agent-based epidemic intervention strategies: travel control, contact tracking and isolation, vaccination, and regular nucleic acid testing to all residents on the epidemic evolution and economic losses. We find that for the original SARS-CoV-2 virus, a strict travel control strategy is effective in both suppressing the spread of COVID-19 and minimizing economic losses. For the Omicron variant (BA.2) with stronger infectious capacity, a relatively loose travel control and an appropriate combination of the other three strategies can effectively control the epidemic outbreak while minimize economic losses. This paper provides an efficient framework for assessing the combination of different agent-based strategies by large-scale simulations in the case of unknown historical contact information of large populations, and the studies on different combinations of control strategies can provide theoretical guidance for future prevention and control.

We developed a novel machine-learning-based algorithm based on a gradient boosting regressor for three-dimensional pixel-by-pixel mapping of blood oxygen saturation based on dual-wavelength optoacoustic data. Algorithm training was performed on in silico data produced from Monte-Carlo-generated absorbed light energy distributions in tissue-like vascularized media for probing wavelengths of 532 and 1064 nm and the empirical instrumental function of the optoacoustic imaging setup with further validation of the independent in silico data. In vivo optoacoustic data for rabbit-ear vasculature was employed as a testing dataset. The developed algorithm allowed in vivo blood oxygen saturation mapping and showed clear differences in blood oxygen saturation values in veins at 15 degrees C and 43 degrees C due to functional arteriovenous anastomoses. These results indicated that dual-wavelength optoacoustic imaging could serve as a cost-effective alternative to complicated multiwavelength quantitative optoacoustic imaging.

The paper reports on the numerical study of temporal characteristics, frequency and phase responses of the photon density waves generated by a point-sized source in scattering media with different scattering anisotropy and absorption index. The study is performed with time-resolved Monte-Carlo simulations for a wide range of medium optical properties covering values typical for aerosols and sea water. We demonstrate that although the normalized pulse delay increases monotonically with distance in the course of propagation in the medium, for particular sets of optical properties its normalized width shows a non-monotonous trend with a maximum corresponding to distances where ballistic and multiply scattered photons give comparable contribution to the irradiance field. In the frequency responses of photon density waves for certain combinations of optical properties at particular distances a deep minimum is formed, also associated with the interference of partial waves. The dimensionless frequency corresponding to this minimum monotonically increases with the increase in anisotropy factor. Dependencies of local and averaged phase and group velocities on distance derived from phase responses revealed a formation of a minima in local group velocities dependencies with further increase to the average velocity values at higher distances, which is also associated with relative contribution of low- and multiply scattered photons. The revealed dependencies can be useful for verifying the analytical models of nonstationary radiation transfer and directly for assessing the achievable parameters of optical systems for various purposes operating in natural scattering media, such as the atmosphere and sea water.

Maxillary sinus pathologies remain among the most common ENT diseases requiring timely diagnosis for successful treatment. Standard ENT inspection approaches indicate low sensitivity in detecting maxillary sinus pathologies. In this paper, we report on capabilities of digital diaphanoscopy combined with machine learning tools in the detection of such pathologies. We provide a comparative analysis of two machine learning approaches applied to digital diapahnoscopy data, namely, convolutional neural networks and linear discriminant analysis. The sensitivity and specificity values obtained for both employed approaches exceed the reported accuracy indicators for traditional screening diagnosis methods (such as nasal endoscopy or ultrasound), suggesting the prospects of their usage for screening maxillary sinuses alterations. The analysis of the obtained values showed that the linear discriminant analysis, being a simpler approach as compared to neural networks, allows one to detect the maxillary sinus pathologies with the sensitivity and specificity of 0.88 and 0.98, respectively.

The COVID-19 pandemics remains one of the largest global challenges. Necessity of effective systemic aids for the minimization of losses leads to the requirement of adequate models allowing to predict the impact of different factors on the spread of the disease. Agent-based simulation models provide a suitable solution with the possibility to accurately account for such factors as age structure of a population, characteristics of isolation, self-isolation strategies and testing strategies, presence of super-spreaders etc. In this paper we report on the results of simulating the spread of COVID-19 in several representative regions of Russia using an agent-based model with a general pool combined with the simulation of population testing strategy. The model accounts for the following key epidemiologic characteristics: population age distribution, reproducibility rate, distributions of infectivity period, a period of clinical manifestation, and age-dependent probability of critical disease. It is demonstrated that the daily epidemiologic curves can be predicted well for different territories with the same model parameters, except for the initial number of infected agents and region-dependent testing as well as isolation strategies, which are considered to be tuning parameters of the model. The developed approach can be further expanded to other regions of different countries, while the determined model parameters could be used as starting values for such simulations.

We report on the comparative analysis of self-calibrating and single-slope diffuse reflectance spectroscopy in resistance to different measurement perturbations. We developed an experimental setup for diffuse reflectance spectroscopy (DRS) in a wide VIS-NIR range with a fiber-optic probe equipped with two source and two detection fibers capable of providing measurements employing both single- and dual-slope (self-calibrating) approaches. In order to fit the dynamic range of a spectrometer in the wavelength range of 460–1030 nm, different exposure times have been applied for short (2 mm) and long (4 mm) source-detector distances. The stability of the self-calibrating and traditional single-slope approaches to instrumental perturbations were compared in phantom and in vivo studies on human palm, including attenuations in individual channels, fiber curving, and introducing optical inhomogeneities in the probe–tissue interface. The self-calibrating approach demonstrated high resistance to instrumental perturbations introduced in the source and detection channels, while the single-slope approach showed resistance only to perturbations introduced into the source channels.