Neu(t)ralMC: energy-efficient open source Monte Carlo algorithm for assessing photon transport in turbid media.

Light propagation in turbid mediums such as atmosphere, fluids, and biological tissues is a challenging problem which necessitates accurate simulation techniques to account for the effects of multiple scattering. The Monte Carlo method has long established itself as a gold standard and is widely adopted for simulating light transport, however, its computationally intensive nature often requires significant processing power and energy consumption. In this paper a novel, open source Monte Carlo algorithm is introduced which is specifically designed for use with energy-efficient processors, effectively addressing those challenges, while maintaining the accuracy/compatibility and outperforming existing solutions. The proposed implementation optimizes photon transport simulations by exploiting the unique capabilities of Apple's low-power, high-performance M-family of chips. The developed method has been implemented in an open-source software package, enabling seamless adaptation of developed algorithms for specific applications. The accuracy and performance are validated using comprehensive comparison with existing solvers commonly used for biomedical imaging. The results demonstrate that the new algorithm achieves comparable accuracy levels to those of existing techniques while significantly reducing computational time and energy consumption.

Influence of blood pulsation on diagnostic volume in pulse oximetry and photoplethysmography measurements.

Recent advances in the development of ultra-compact semiconductor lasers and technology of printed flexible hybrid electronics have opened broad perspectives for the design of new pulse oximetry and photoplethysmography devices. Conceptual design of optical diagnostic devices requires careful selection of various technical parameters, including spectral range; polarization and intensity of incident light; actual size, geometry, and sensitivity of the detector; and mutual position of the source and detector on the surface of skin. In the current study utilizing a unified Monte Carlo computational tool, we explore the variations in diagnostic volume due to arterial blood pulsation for typical transmitted and back-scattered probing configurations in a human finger. The results of computational studies show that the variations in diagnostic volumes due to arterial pulse wave are notably (up to 45%) different in visible and near-infrared spectral ranges in both transmitted and back-scattered probing geometries. While these variations are acceptable for relative measurements in pulse oximetry and/or photoplethysmography, for absolute measurements, an alignment normalization of diagnostic volume is required and can be done by a computational approach utilized in the framework of the current study.

Influence of blood pulsation on diagnostic volume in pulse oximetry and photoplethysmography measurements: publisher's note.

This publisher's note corrects several errors in Appl. Opt.58, 9398 (2019).APOPAI0003-693510.1364/AO.58.009398.

Two electric field Monte Carlo models of coherent backscattering of polarized light.

Modeling of coherent polarized light propagation in turbid scattering medium by the Monte Carlo method provides an ultimate understanding of coherent effects of multiple scattering, such as enhancement of coherent backscattering and peculiarities of laser speckle formation in dynamic light scattering (DLS) and optical coherence tomography (OCT) diagnostic modalities. In this report, we consider two major ways of modeling the coherent polarized light propagation in scattering tissue-like turbid media. The first approach is based on tracking transformations of the electric field along the ray propagation. The second one is developed in analogy to the iterative procedure of the solution of the Bethe-Salpeter equation. To achieve a higher accuracy in the results and to speed up the modeling, both codes utilize the implementation of parallel computing on NVIDIA Graphics Processing Units (GPUs) with Compute Unified Device Architecture (CUDA). We compare these two approaches through simulations of the enhancement of coherent backscattering of polarized light and evaluate the accuracy of each technique with the results of a known analytical solution. The advantages and disadvantages of each computational approach and their further developments are discussed. Both codes are available online and are ready for immediate use or download.

Photodynamic treatment of malignant melanoma with structured light: in silico Monte Carlo modeling.

In this report, we propose a novel strategy for the photodynamic approach to the treatment of melanoma, aiming to mitigate the excessive absorption and consequent thermal effects. The cornerstone of this approach is an innovative structured illumination technique that optimizes light delivery to the tissue. The methodology of this in silico study involves the development of an optical model of human skin with the presence of melanoma and an accurate simulation technique of photon transport within the complex turbid scattering medium. To assess the effectiveness of our proposed strategy, we introduced a cost function reflecting the irradiated volume and optical radiation absorption within the target area/volume occupied by malformation. By utilizing the cost function, we refine the offset illumination parameters for a variety of target system parameters, ensuring increased efficiency of photodynamic therapy. Our computer simulation results introduce a promising new path towards improved photodynamic melanoma treatments, potentially leading to better therapeutic outcomes and reduced side effects. Further experimental validation is needed to confirm these theoretical advancements, which could contribute towards revolutionizing current melanoma photodynamic treatment methodologies.

Insights into polycrystalline microstructure of blood films with 3D Mueller matrix imaging approach.

This study introduces a novel approach in the realm of liquid biopsies, employing a 3D Mueller-matrix (MM) image reconstruction technique to analyze dehydrated blood smear polycrystalline structures. Our research centers on exploiting the unique optical anisotropy properties of blood proteins, which undergo structural alterations at the quaternary and tertiary levels in the early stages of diseases such as cancer. These alterations manifest as distinct patterns in the polycrystalline microstructure of dried blood droplets, offering a minimally invasive yet highly effective method for early disease detection. We utilized a groundbreaking 3D MM mapping technique, integrated with digital holographic reconstruction, to perform a detailed layer-by-layer analysis of partially depolarizing dry blood smears. This method allows us to extract critical optical anisotropy parameters, enabling the differentiation of blood films from healthy individuals and prostate cancer patients. Our technique uniquely combines polarization-holographic and differential MM methodologies to spatially characterize the 3D polycrystalline structures within blood films. A key advancement in our study is the quantitative evaluation of optical anisotropy maps using statistical moments (first to fourth orders) of linear and circular birefringence and dichroism distributions. This analysis provides a comprehensive characterization of the mean, variance, skewness, and kurtosis of these distributions, crucial for identifying significant differences between healthy and cancerous samples. Our findings demonstrate an exceptional accuracy rate of over 90 % for the early diagnosis and staging of cancer, surpassing existing screening methods. This high level of precision and the non-invasive nature of our technique mark a significant advancement in the field of liquid biopsies. It holds immense potential for revolutionizing cancer diagnosis, early detection, patient stratification, and monitoring, thereby greatly enhancing patient care and treatment outcomes. In conclusion, our study contributes a pioneering technique to the liquid biopsy domain, aligning with the ongoing quest for non-invasive, reliable, and efficient diagnostic methods. It opens new avenues for cancer diagnosis and monitoring, representing a substantial leap forward in personalized medicine and oncology.

Imaging of the interaction of low-frequency electric fields with biological tissues by optical coherence tomography.

Low-frequency electric fields propagating in ex vivo biological tissues have been observed by using double-correlation optical coherence tomography (OCT). An adaptive Wiener filtering approach has been used to remove background noise, and a Fourier domain correlation algorithm has been applied to the sequence of OCT images. The results present the first direct observation (to our knowledge) of the scope of the electric field influencing biological tissues with OCT. The results show that variation in voltage and frequency of the applied electric field relates exponentially to the magnitude of its influence on biological tissue. The magnitude of influence is about twice more for fresh tissue samples in comparison to nonfresh ones. The obtained results suggest that OCT can be used for observation and quantitative evaluation of the electrokinetic changes in biological tissues under different physiological conditions, functional electrical stimulation, and food quality control.

Polarimetric imaging for cervical pre-cancer screening aided by machine learning: ex vivo studies.

Significance: Wide-field imaging Mueller polarimetry is an optical imaging technique that has great potential to become a reliable, fast, non-contact in vivo imaging modality for the early detection of, e.g., deceases and tissue structural malformations, such as cervical intraepithelial neoplasia, in both clinical and low-resource settings. On the other hand, machine learning methods have established themselves as a superior solution in image classification and regression tasks. We combine Mueller polarimetry and machine learning, critically assess the data/classification pipeline, investigate the bias arising from training strategies, and demonstrate how higher levels of detection accuracy can be achieved. Aim: We aim to automate/assist with diagnostic segmentation of polarimetric images of uterine cervix specimens. Approach: A comprehensive capture-to-classification pipeline is developed in house. Specimens are acquired and measured with imaging Mueller polarimeter and undergo histopathological classification. Subsequently, a labeled dataset is created within tagged regions of either healthy or neoplastic cervical tissues. Several machine learning methods are trained utilizing different training-test-set-split strategies, and their corresponding accuracies are compared. Results: Our results include robust measurements of model performance with two approaches: a 90:10 training-test-set-split and leave-one-out cross-validation. By comparing the classifier's accuracy directly with the ground truth obtained during histology analysis, we demonstrate how conventionally used shuffled split leads to an over-estimate of true classifier performance (0.964±0.00). The leave-one-out cross-validation, however, leads to more accurate performance (0.812±0.21) with respect to newly obtained samples that were not used to train the models. Conclusions: Combination of Mueller polarimetry and machine learning is a powerful tool for the task of screening for pre-cancerous conditions in cervical tissue sections. Nevertheless, there is a inherent bias with conventional processes that can be addressed using more conservative classifier training approaches. This results in overall improvements of the sensitivity and specificity of the developed techniques for "unseen" images.

Multispectral sensor fusion in SmartWatch for in situ continuous monitoring of human skin hydration and body sweat loss.

Post-pandemic health operations have become a near-term reality, discussions around wearables are on the rise. How do wearable health solutions effectively deploy and use this opportunity to fill the gap between wellness and healthcare? In this paper, we will talk about wearable healthcare diagnosis, with a particular focus on monitoring skin hydration using optical multi-wavelength sensor fusion. Continuous monitoring of human skin hydration is a task of paramount importance for maintaining water loss dynamics for fitness lovers as well as for skin beauty, integrity and the health of the entire body. Preserving the appropriate levels of hydration ensures consistency of weight, positively affects psychological state, and proven to result in a decrease in blood pressure as well as the levels of "bad" cholesterol while slowing down the aging processes. Traditional methods for determining the state of water content in the skin do not allow continuous and non-invasive monitoring, which is required for variety of consumer, clinical and cosmetic applications. We present novel sensing technology and a pipeline for capturing, modeling and analysis of the skin hydration phenomena and associated changes therein. By expanding sensing capabilities built into the SmartWatch sensor and combining them with advanced modeling and Machine Learning (ML) algorithms, we identified several important characteristics of photoplethysmography (PPG) signal and spectral sensitivity corresponding to dynamics of skin water content. In a hardware aspect, we newly propose the expansion of SmartWatch capabilities with InfraRed light sources equipped with wavelengths of 970 nm and 1450 nm. Evaluation of the accuracy and characteristics of PPG sensors has been performed with biomedical optics-based simulation framework using Monte Carlo simulations. We performed rigorous validation of the developed technology using experimental and clinical studies. The developed pipeline serves as a tool in the ongoing studies of the next generation of optical sensing technology.

Skin Complications of Diabetes Mellitus Revealed by Polarized Hyperspectral Imaging and Machine Learning.

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.

Hyperspectral imaging of human skin aided by artificial neural networks.

We developed a compact, hand-held hyperspectral imaging system for 2D neural network-based visualization of skin chromophores and blood oxygenation. State-of-the-art micro-optic multichannel matrix sensor combined with the tunable Fabry-Perot micro interferometer enables a portable diagnostic device sensitive to the changes of the oxygen saturation as well as the variations of blood volume fraction of human skin. Generalized object-oriented Monte Carlo model is used extensively for the training of an artificial neural network utilized for the hyperspectral image processing. In addition, the results are verified and validated via actual experiments with tissue phantoms and human skin in vivo. The proposed approach enables a tool combining both the speed of an artificial neural network processing and the accuracy and flexibility of advanced Monte Carlo modeling. Finally, the results of the feasibility studies and the experimental tests on biotissue phantoms and healthy volunteers are presented.

Combined use of laser Doppler flowmetry and skin thermometry for functional diagnostics of intradermal finger vessels.

We introduce a noninvasive diagnostic approach for functional monitoring of blood microflows in capillaries and thermoregulatory vessels within the skin. The measuring system is based on the combined use of laser Doppler flowmetry and skin contact thermometry. The obtained results suggest that monitoring of blood microcirculation during the occlusion, performed in conjunction with the skin temperature measurements in the thermally stabilized medium, has a great potential for quantitative assessment of angiospatic dysfunctions of the peripheral blood vessels. The indices of blood flow reserve and temperature response were measured and used as the primarily parameters of the functional diagnostics of the peripheral vessels of skin. Utilizing these parameters, a simple phenomenological model has been suggested to identify patients with angiospastic violations in the vascular system.

Multimodal optical measurement for study of lower limb tissue viability in patients with diabetes mellitus.

According to the International Diabetes Federation, the challenge of early stage diagnosis and treatment effectiveness monitoring in diabetes is currently one of the highest priorities in modern healthcare. The potential of combined measurements of skin fluorescence and blood perfusion by the laser Doppler flowmetry method in diagnostics of low limb diabetes complications was evaluated. Using Monte Carlo probabilistic modeling, the diagnostic volume and depth of the diagnosis were evaluated. The experimental study involved 76 patients with type 2 diabetes mellitus. These patients were divided into two groups depending on the degree of complications. The control group consisted of 48 healthy volunteers. The local thermal stimulation was selected as a stimulus on the blood microcirculation system. The experimental studies have shown that diabetic patients have elevated values of normalized fluorescence amplitudes, as well as a lower perfusion response to local heating. In the group of people with diabetes with trophic ulcers, these parameters also significantly differ from the control and diabetes only groups. Thus, the intensity of skin fluorescence and level of tissue blood perfusion can act as markers for various degrees of complications from the beginning of diabetes to the formation of trophic ulcers.

Backscattering of linearly polarized light from turbid tissue-like scattering medium with rough surface.

In the framework of further development of a unified computational tool for the needs of biomedical optics, we introduce an electric field Monte Carlo (MC) model for simulation of backscattering of coherent linearly polarized light from a turbid tissue-like scattering medium with a rough surface. We consider the laser speckle patterns formation and the role of surface roughness in the depolarization of linearly polarized light backscattered from the medium. The mutual phase shifts due to the photons' pathlength difference within the medium and due to reflection/refraction on the rough surface of the medium are taken into account. The validation of the model includes the creation of the phantoms of various roughness and optical properties, measurements of co- and cross-polarized components of the backscattered/reflected light, its analysis and extensive computer modeling accelerated by parallel computing on the NVIDIA graphics processing units using compute unified device architecture (CUDA). The analysis of the spatial intensity distribution is based on second-order statistics that shows a strong correlation with the surface roughness, both with the results of modeling and experiment. The results of modeling show a good agreement with the results of experimental measurements on phantoms mimicking human skin. The developed MC approach can be used for the direct simulation of light scattered by the turbid scattering medium with various roughness of the surface.

Application of circularly polarized light for non-invasive diagnosis of cancerous tissues and turbid tissue-like scattering media.

Polarization-based optical techniques have become increasingly popular in the field of biomedical diagnosis. In the current report we exploit the directional awareness of circularly and/or elliptically polarized light backscattered from turbid tissue-like scattering media. We apply circularly and elliptically polarized laser light which illuminates the samples of interest, and a standard optical polarimeter is used to observe the polarization state of light backscattered a few millimeters away from the point of incidence. We demonstrate that the Stokes vector of backscattered light depicted on a Poincaré sphere can be used to assess a turbid tissue-like scattering medium. By tracking the Stokes vector of the detected light on the Poincaré sphere, we investigate the utility of this approach for characterization of cancerous and non-cancerous tissue samples in vitro. The obtained results are discussed in the framework of a phenomenological model and the results of a polarization tracking Monte Carlo model, developed in house. Schematic illustration of the experimental approach utilizing circularly and elliptically polarized light for probing turbid tissue-like scattering media.

Propagation of coherent polarized light in turbid highly scattering medium.

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.

Monitoring of interaction of low-frequency electric field with biological tissues upon optical clearing with optical coherence tomography.

The influence of a low-frequency electric field applied to soft biological tissues ex vivo at normal conditions and upon the topical application of optical clearing agents has been studied by optical coherence tomography (OCT). The electro-kinetic response of tissues has been observed and quantitatively evaluated by the double correlation OCT approach, utilizing consistent application of an adaptive Wiener filtering and Fourier domain correlation algorithm. The results show that fluctuations, induced by the electric field within the biological tissues are exponentially increased in time. We demonstrate that in comparison to impedance measurements and the mapping of the temperature profile at the surface of the tissue samples, the double correlation OCT approach is much more sensitive to the changes associated with the tissues' electro-kinetic response. We also found that topical application of the optical clearing agent reduces the tissues' electro-kinetic response and is cooling the tissue, thus reducing the temperature induced by the electric current by a few degrees. We anticipate that dcOCT approach can find a new application in bioelectrical impedance analysis and monitoring of the electric properties of biological tissues, including the resistivity of high water content tissues and its variations.

Alternative forms of Y-box binding protein 1 and YB-1 mRNA.

The multifunctional eukaryotic protein YB-1 (Y-box binding protein 1) plays a role in DNA reparation, transcription regulation, splicing, and mRNA translation, thereby participating in many crucial events in cells. Its effect is dependent mostly on its amount, and hence, on regulation of its synthesis. Published data on regulation of synthesis of YB-1 mediated by its mRNA 5' UTR, and specifically on the 5' UTR length and the presence of TOP-like motifs in this region, are contradictory. Here we report that 5' UTRs of major forms of human, rabbit, and mouse YB-1 mRNAs are about 140 nucleotides long and contain no TOP-like motifs mentioned in the literature. Also, we have found that YB-1 specifically interacts with the 5' UTR of its own mRNA within a region of about 100 nucleotides upstream from the start codon. Apart from YB-1, translation of YB-1 mRNA in a cell free system gives an additional product with an extended N-terminus and lower electrophoretic mobility. The start codon for synthesis of the additional product is AUC at position -(60-58) of the same open reading frame as that for the major product. Also, in the cell there is an alternative YB-1 mRNA with exon 1 replaced by a part of intron 1; YB-1 synthesized in vitro from this mRNA contains, instead of its N-terminal A/P domain, 10-11 amino acids encoded by intron 1.

Peer-to-peer Monte Carlo simulation of photon migration in topical applications of biomedical optics.

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.

Human tissue color as viewed in high dynamic range optical spectral transmission measurements.

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.