Monte Carlo simulation of in vivo Raman spectral measurements of human skin with a multi-layered tissue optical model

Monte Carlo simulation of the effect of melanin concentration on light-tissue interactions in transmittance and reflectance finger photoplethysmography

Photoplethysmography (PPG) uses light to detect volumetric changes in blood, and is integrated into many healthcare devices to monitor various physiological measurements. However, an unresolved limitation of PPG is the effect of skin pigmentation on the signal and its impact on PPG based applications such as pulse oximetry. Hence, an in-silico model of the human finger was developed using the Monte Carlo (MC) technique to simulate light interactions with different melanin concentrations in a human finger, as it is the primary determinant of skin pigmentation. The AC/DC ratio in reflectance PPG mode was evaluated at source-detector separations of 1 mm and 3 mm as the convergence rate (Q), a parameter that quantifies the accuracy of the simulation, exceeded a threshold of 0.001. At a source-detector separation of 3 mm, the AC/DC ratio of light skin was 0.472 times more than moderate skin and 6.39 than dark skin at 660 nm, and 0.114 and 0.141 respectively at 940 nm. These findings are significant for the development of PPG-based sensors given the ongoing concerns regarding the impact of skin pigmentation on healthcare devices.

Raman spectroscopy in chronic heart failure diagnosis based on human skin analysis

This work aims at studying Raman spectroscopy in combination with chemometrics as an alternative fast noninvasive method to detect chronic heart failure (CHF) cases. Optical analysis is focused on the changes in the spectral features associated with the biochemical composition changes of skin tissues. A portable spectroscopy setup with the 785 nm excitation wavelength was used to record skin Raman features. In this in vivo study, 127 patients and 57 healthy volunteers were involved in measuring skin spectral features by Raman spectroscopy. The spectral data were analyzed with a projection on the latent structures and discriminant analysis. 202 skin spectra of patients with CHF and 90 skin spectra of healthy volunteers were classified with 0.888 ROC AUC for the 10-fold cross validated algorithm. To identify CHF cases, the performance of the proposed classifier was verified by means of a new test set that is equal to 0.917 ROC AUC.

Meshless Monte Carlo radiation transfer method for curved geometries using signed distance functions

SIGNIFICANCE

Monte Carlo radiation transfer (MCRT) is the gold standard for modeling light transport in turbid media. Typical MCRT models use voxels or meshes to approximate experimental geometry. A voxel-based geometry does not allow for the precise modeling of smooth curved surfaces, such as may be found in biological systems or food and drink packaging. Mesh-based geometry allows arbitrary complex shapes with smooth curved surfaces to be modeled. However, mesh-based models also suffer from issues such as the computational cost of generating meshes and inaccuracies in how meshes handle reflections and refractions.

AIM

We present our algorithm, which we term signedMCRT (sMCRT), a geometry-based method that uses signed distance functions (SDF) to represent the geometry of the model. SDFs are capable of modeling smooth curved surfaces precisely while also modeling complex geometries.

APPROACH

We show that using SDFs to represent the problem's geometry is more precise than voxel and mesh-based methods.

RESULTS

sMCRT is validated against theoretical expressions, and voxel and mesh-based MCRT codes. We show that sMCRT can precisely model arbitrary complex geometries such as microvascular vessel network using SDFs. In comparison with the current state-of-the-art in MCRT methods specifically for curved surfaces, sMCRT is more precise for cases where the geometry can be defined using combinations of shapes.

CONCLUSIONS

We believe that SDF-based MCRT models are a complementary method to voxel and mesh models in terms of being able to model complex geometries and accurately treat curved surfaces, with a focus on precise simulation of reflections and refractions. sMCRT is publicly available at https://github.com/lewisfish/signedMCRT.

An experimental and numerical modelling investigation of the optical properties of Intralipid using deep Raman spectroscopy

In this study, Monte Carlo simulations were created to investigate the distribution of Raman signals in tissue phantoms and to validate the arctk code that was used. The aim was to show our code is capable of replicating experimental results in order to use it to advise similar future studies and to predict the outcomes. The experiment performed to benchmark our code used large volume liquid tissue phantoms to simulate the scattering properties of human tissue. The scattering agent used was Intralipid (IL), of various concentrations, filling a small quartz tank. A thin sample of PTFE was made to act as a distinct layer in the tank; this was our Raman signal source. We studied experimentally, and then reproduced via simulations, the variation in Raman signal strength in a transmission geometry as a function of the optical properties of the scattering agent and the location of the Raman material in the volume. We have also found that a direct linear extrapolation of scattering coefficients between concentrations of Intralipid is an incorrect assumption at lower concentrations when determining the optical properties. By combining experimental and simulation results, we have calculated different estimates of these scattering coefficients. The results of this study give insight into light propagation and Raman transport in scattering media and show how the location of maximum Raman signal varies as the optical properties change. The success of arctk in reproducing observed experimental signal behaviour will allow us in future to inform the development of noninvasive cancer screening applications (such as breast and prostate cancers) in vivo.

A computationally efficient Monte-Carlo model for biomedical Raman spectroscopy

Monte Carlo (MC) modeling is a valuable tool to gain fundamental understanding of light-tissue interactions, provide guidance and assessment to optical instrument designs, and help analyze experimental data. It has been a major challenge to efficiently extend MC towards modeling of bulk-tissue Raman spectroscopy (RS) due to the wide spectral range, relatively sharp spectral features, and presence of background autofluorescence. Here, we report a computationally efficient MC approach for RS by adapting the massively-parallel Monte Carlo eXtreme (MCX) simulator. Simulation efficiency is achieved through "isoweight," a novel approach that combines the statistical generation of Raman scattered and Fluorescence emission with a lookup-table-based technique well-suited for parallelization. The MC model uses a graphics processor to produce dense Raman and fluorescence spectra over a range of 800 - 2000 cm^-1 with an approximately 100× increase in speed over prior RS Monte Carlo methods. The simulated RS signals are compared against experimentally collected spectra from gelatin phantoms, showing a strong correlation.

Raman spectroscopy of human skin for kidney failure detection

The object of this paper is in vivo study of skin spectral-characteristics in patients with kidney failure by conventional Raman spectroscopy in near infrared region. The experimental dataset was subjected to discriminant analysis with the projection on latent structures (PLS-DA). Application of Raman spectroscopy to investigate the forearm skin in 85 adult patients with kidney failure (90 spectra) and 40 healthy adult volunteers (80 spectra) has yielded the accuracy of 0.96, sensitivity of 0.94 and specificity of 0.99 in terms of identifying the target subjects with kidney failure. The autofluorescence analysis in the near infrared region identified the patients with kidney failure among healthy volunteers of the same age group with specificity, sensitivity, and accuracy of 0.91, 0.84, and 0.88, respectively. When classifying subjects by the presence of kidney failure using the PLS-DA method, the most informative Raman spectral bands are 1315 to 1330, 1450 to 1460, 1700 to 1800 cm^-1 . In general, the performed study demonstrates that for in vivo skin analysis, the conventional Raman spectroscopy can provide the basis for cost-effective and accurate detection of kidney failure and associated metabolic changes in the skin.

Application driven assessment of probe designs for Raman spectroscopy

In vivo Raman spectroscopy has been utilized for the non-invasive, non-destructive assessment of tissue pathophysiology for a variety of applications largely through the use of fiber optic probes to interface with samples of interest. Fiber optic probes can be designed to optimize the collection of Raman-scattered photons from application-dependent depths, and this critical consideration should be addressed when planning a study. Herein we investigate four distinct probe geometries for sensitivity to superficial and deep signals through a Monte Carlo model that incorporates Raman scattering and fluorescence. Experimental validation using biological tissues was performed to accurately recapitulate in vivo scenarios. Testing in biological tissues agreed with modeled results and revealed that microlens designs had slightly enhanced performance at shallow depths (< 1 mm), whereas all of the beampath-modified designs yielded more signal from deep within tissue. Simulation based on fluence maps generated using ray-tracing in the absence of optical scattering had drastically different results as a function of depth for each probe compared to the biological simulation. The contrast in simulation results between the non-scattering and biological tissue phantoms underscores the importance of considering the optical properties of a given application when designing a fiber optic probe. The model presented here can be easily extended for optimization of entirely novel probe designs prior to fabrication, reducing time and cost while improving data quality.

Experimental validation of a spectroscopic Monte Carlo light transport simulation technique and Raman scattering depth sensing analysis in biological tissue

SIGNIFICANCE

Raman spectroscopy (RS) applied to surgical guidance is attracting attention among scientists in biomedical optics. Offering a computational platform for studying depth-resolved RS and probing molecular specificity of different tissue layers is of crucial importance to increase the precision of these techniques and facilitate their clinical adoption.

AIM

The aim of this work was to present a rigorous analysis of inelastic scattering depth sampling and elucidate the relationship between sensing depth of the Raman effect and optical properties of the tissue under interrogation.

APPROACH

A new Monte Carlo (MC) package was developed to simulate absorption, fluorescence, elastic, and inelastic scattering of light in tissue. The validity of the MC algorithm was demonstrated by comparison with experimental Raman spectra in phantoms of known optical properties using nylon and polydimethylsiloxane as Raman-active compounds. A series of MC simulations were performed to study the effects of optical properties on Raman sensing depth for an imaging geometry consistent with single-point detection using a handheld fiber optics probe system.

RESULTS

The MC code was used to estimate the Raman sensing depth of a handheld fiber optics system. For absorption and reduced scattering coefficients of 0.001 and 1  mm  -  1, the sensing depth varied from 105 to 225  μm for a range of Raman probabilities from 10  -  6 to 10  -  3. Further, for a realistic Raman probability of 10  -  6, the sensing depth ranged between 10 and 600  μm for the range of absorption coefficients 0.001 to 1.4  mm  -  1 and reduced scattering coefficients of 0.5 to 30  mm  -  1.

CONCLUSIONS

A spectroscopic MC light transport simulation platform was developed and validated against experimental measurements in tissue phantoms and used to predict depth sensing in tissue. It is hoped that the current package and reported results provide the research community with an effective simulating tool to improve the development of clinical applications of RS.

Direct observation of glucose fingerprint using in vivo Raman spectroscopy

Noninvasive blood glucose monitoring has been a long-standing dream in diabetes management. The use of Raman spectroscopy, with its molecular specificity, has been investigated in this regard over the past decade. Previous studies reported on glucose sensing based on indirect evidence such as statistical correlation to the reference glucose concentration. However, these claims fail to demonstrate glucose Raman peaks, which has raised questions regarding the effectiveness of Raman spectroscopy for glucose sensing. Here, we demonstrate the first direct observation of glucose Raman peaks from in vivo skin. The signal intensities varied proportional to the reference glucose concentrations in three live swine glucose clamping experiments. Tracking spectral intensity based on linearity enabled accurate prospective prediction in within-subject and intersubject models. Our direct demonstration of glucose signal may quiet the long debate about whether glucose Raman spectra can be measured in vivo in transcutaneous glucose sensing.

Mathematical simulation of temperature distribution in tumor tissue and surrounding healthy tissue treated by laser combined with indocyanine green

Background

Photothermal therapy is a local treatment method for cancer and the heat energy generated from it could destroy the tumor cells. This study is aimed to investigate the temperature distribution in tumor tissue and surrounding health tissue of tumor bearing mice applying mathematical simulation model. Tumor bearing mice treated by laser combined with or without indocyanine green. Monte Carlo method and the Pennes bio-heat equation were used to calculate the light distribution and heat energy. COMSOL Multiphysic was adopted to construct three dimensional temperature distribution model.

Results

This study revealed that the data calculated by simulation model is in good agreement with the surface temperature monitored by infrared thermometer. Effected by the optical parameters and boundary conditions of tissue, the highest temperature of tissue treated by laser combined with indocyanine green was about 65 °C which located in tumor tissue and the highest temperature of tissue treated by laser was about 43 °C which located under the tumor tissue. The temperature difference was about 20 °C. Temperature distribution in tissue was not uniform. The temperature difference in different parts of tumor tissue raised up to 15 °C. The temperature of tumor tissue treated by laser combined with indocyanine green was about 20 °C higher than that of the surrounding healthy tissue.

Conclusions

Reasonably good matching between the calculated temperature and the measured temperature was achieved, thus demonstrated great utility of our modeling method and approaches for deepening understand in the temperature distribution in tumor tissue and surrounding healthy tissue during the laser combined with photosensitizer. The simulation model could provide guidance and reference function for the effect of photothermal therapy.

Electronic supplementary material

The online version of this article (10.1186/s12976-019-0107-3) contains supplementary material, which is available to authorized users.

Advances in the simulation of light-tissue interactions in biomedical engineering

Monte Carlo (MC) simulation for light propagation in scattering and absorbing media is the gold standard for studying the interaction of light with biological tissue and has been used for years in a wide variety of cases. The interaction of photons with the medium is simulated based on its optical properties and the original approximation of the scattering phase function. Over the past decade, with the new measurement geometries and recording techniques invented also the corresponding sophisticated methods for the description of the underlying light-tissue interaction taking into account realistic parameters and settings were developed. Applications, such as multiple scattering, optogenetics, optical coherence tomography, Raman spectroscopy, polarimetry and Mueller matrix measurement have emerged and are still constantly improved. Here, we review the advances and recent applications of MC simulation for the active field of the life sciences and the medicine pointing out the new insights enabled by the theoretical concepts.

Monte Carlo simulation of the influence of internal optical absorption on the external Raman signal for biological samples

Proper understanding of Raman spectroscopic signals from biological samples requires the quantification of internal signal absorption and its effect on the Raman spectra detected outside the samples under study. In this paper, we describe an efficient Monte Carlo method to simulate Raman scattering in biological tissues and solutions and compare the findings with experimental results obtained in samples with different absorber concentrations and optical properties. As an illustrative example, we focus on solutions of beta-carotene (bCar) in ethanol with different concentrations of absorber (ink) added. We find good agreement between simulation and experiment, thus indicating a way to quantify the influence of internal signal absorption in Raman measurements.

Portable spectroscopic system for in vivo skin neoplasms diagnostics by Raman and autofluorescence analysis

The present paper studies the applicability of a portable cost-effective spectroscopic system for the optical screening of skin tumors. in vivo studies of Raman scattering and autofluorescence (AF) of skin tumors with the 785 nm excitation laser in the near-infrared region included malignant melanoma, basal cell carcinoma and various types of benign neoplasms. The efficiency of the portable system was evaluated by comparison with a highly sensitive spectroscopic system and with the diagnosis accuracy of a human oncologist. Partial least square analysis of Raman and AF spectra was performed; specificity and sensitivity of various skin oncological pathologies detection varied from 78.9% to 100%. Hundred percent accuracy of benign and malignant skin tumors differentiation is possible only with a combined analysis of Raman and AF signals.

Simulation of Raman scattering including detector parameters and sampling volume

Raman spectroscopy can be employed to measure the chemical composition of a sample, which can in turn be used to extract biological information. The aim of this paper is to introduce an efficient simulation technique for Raman spectroscopy in turbid (scattering) media taking into account relevant detector parameters and the sampling volume. We simulate the process of photon motion in turbid media by means of the Monte Carlo (MC) method. The numerical simulation of Raman scattering consists of two stages: calculation of the photon fluence at each point of the medium and subsequent generation of the corresponding amount of Raman photons at each point. The developed model allows simulation of both confocal and optical fiber probe Raman setups. In more detail, the model efficiently simulates Raman signals for different single and multi-layer phantoms and geometries, including focused and collimated (i.e., the fiber-based case) excitation laser beams as well as different values for the numerical aperture and the excitation beam radius. In the future, our results offer the potential to improve the design of Raman systems for in vivo applications in biomedical research.

Two efficient approaches for modeling of Raman scattering in homogeneous turbid media

The quantitative analysis of Raman spectroscopic signals in biological tissue is generally difficult. Typical samples contain a multitude of molecular species and, in addition, measurements are altered by attenuation of the Raman signal. Realistic numerical modeling of the Raman process can help to facilitate the quantitative analysis of the Raman spectra, but approaches so far are scarce and often time-consuming. In this work, we report on two different and very efficient approaches for modeling of Raman scattering in turbid media irradiated by laser light. Both approaches utilize the Monte Carlo method to simulate the Raman scattering process. We compare the efficiency of both approaches and discuss possible future extensions and experimental validation.