Aging and diabetes lead to protein glycation and cause dysfunction of collagen-containing tissues. The accompanying structural and functional changes of collagen significantly contribute to the development of various pathological malformations affecting the skin, blood vessels, and nerves, causing a number of complications, increasing disability risks and threat to life. In fact, no methods of non-invasive assessment of glycation and associated metabolic processes in biotissues or prediction of possible skin complications, e.g., ulcers, currently exist for endocrinologists and clinical diagnosis. In this publication, utilizing emerging photonics-based technology, innovative solutions in machine learning, and definitive physiological characteristics, we introduce a diagnostic approach capable of evaluating the skin complications of diabetes mellitus at the very earlier stage. The results of the feasibility studies, as well as the actual tests on patients with diabetes and healthy volunteers, clearly show the ability of the approach to differentiate diabetic and control groups. Furthermore, the developed in-house polarization-based hyperspectral imaging technique accomplished with the implementation of the artificial neural network provides new horizons in the study and diagnosis of age-related diseases.

Conceptual engineering design and optimization of laser-based imaging techniques and optical diagnostic systems used in the field of biomedical optics requires a clear understanding of the light-tissue interaction and peculiarities of localization of the detected optical radiation within the medium. The description of photon migration within the turbid tissue-like media is based on the concept of radiative transfer that forms a basis of Monte Carlo (MC) modeling. An opportunity of direct simulation of influence of structural variations of biological tissues on the probing light makes MC a primary tool for biomedical optics and optical engineering. Due to the diversity of optical modalities utilizing different properties of light and mechanisms of light-tissue interactions a new MC code is typically required to be developed for the particular diagnostic application. In current paper introducing an object oriented concept of MC modeling and utilizing modern web applications we present the generalized online computational tool suitable for the major applications in biophotonics. The computation is supported by NVIDEA CUDA Graphics Processing Unit providing acceleration of modeling up to 340 times.

High dynamic range optical-to-near-infrared transmission measurements for different parts of human body in the spectral range from 650 to 950 nm have been performed. Experimentally measured spectra are correlated with Monte Carlo simulations using chromaticity coordinates in CIE 1976 L*a*b* color space. Both a qualitative and a quantitative agreement have been found, paving a new way of characterizing human tissues in vivo. The newly developed experimental and computational platform for assessing tissue transmission spectra is anticipated to have a considerable impact on identifying favorable conditions for laser surgery and optical diagnostics, while providing supplementary information about tissue properties.

Within the framework of further development of unified Monte Carlo code for the needs of biomedical optics and biophotonics, we present an approach for modeling of coherent polarized light propagation in highly scattering turbid media, such as biological tissues. The temporal coherence of light, linear and circular polarization, interference, and the helicity flip of circularly polarized light due to reflection at the medium boundary and/or backscattering events are taken into account. To achieve higher accuracy in the results and to speed up the modeling, the implementation of the code utilizes parallel computing on NVIDIA graphics processing units using Compute Unified Device Architecture. The results of the simulation of coherent linearly and circularly polarized light are presented in comparison with the results of known theoretical studies and the results of alternative modelings.

In the framework of further development of the unified approach of photon migration in complex turbid media, such as biological tissues we present a peer-to-peer (P2P) Monte Carlo (MC) code. The object-oriented programming is used for generalization of MC model for multipurpose use in various applications of biomedical optics. The online user interface providing multiuser access is developed using modern web technologies, such as Microsoft Silverlight, ASP.NET. The emerging P2P network utilizing computers with different types of compute unified device architecture-capable graphics processing units (GPUs) is applied for acceleration and to overcome the limitations, imposed by multiuser access in the online MC computational tool. The developed P2P MC was validated by comparing the results of simulation of diffuse reflectance and fluence rate distribution for semi-infinite scattering medium with known analytical results, results of adding-doubling method, and with other GPU-based MC techniques developed in the past. The best speedup of processing multiuser requests in a range of 4 to 35 s was achieved using single-precision computing, and the double-precision computing for floating-point arithmetic operations provides higher accuracy.