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

Monte Carlo Simulation of the Effect of Melanin Concentration on Light-Tissue Interactions in Reflectance Pulse Oximetry

Over the past ten years, there has been an increasing demand for reliable consumer wearables as users are inclined to monitor their health and fitness metrics in real-time, especially since the COVID-19 pandemic. Reflectance pulse oximeters in fitness trackers and smartwatches provide convenient, non-invasive SpO2 measurements but face challenges in achieving medical-grade accuracy, particularly due to difficulties in capturing physiological signals, which may be affected by skin pigmentation. Hence, this study sets out to investigate the influence of skin pigmentation, particularly in individuals with darker skin, on the accuracy and reliability of SpO2 measurement in consumer wearables that utilise reflectance pulse oximeters. A Monte Carlo model is developed to assess the effect on simulated reflectance pulse oximetry measurements across light, moderate, and dark skin types for oxygen saturation levels between 70 and 100%. The results indicate that a one-algorithm-fits-all calibration approach may be insufficient, and root mean square errors (RMSEs) of at least 0.3956%, 0.9132%, and 8.4111% for light, moderate, and dark skin are observed when compared to transmittance calibration algorithms. Further research is required to validate these findings and improve the performance of reflectance pulse oximeters in real-world applications, particularly in the context of consumer wearables.

Quantitative simulation of near-infrared light treatment for Alzheimer's disease using patient-individualized optical-parametric phantoms

Significance

Alzheimer's disease (AD) is a brain disorder characterized by its multifactorial nature and complex pathogenesis, highlighting the necessity for multimodal and individualized interventions. Among emerging therapies, near-infrared (NIR) light treatment shows promise as a therapeutic modality for AD. However, existing clinical studies lack sufficient data on light dosimetry, parameter optimization, and dose-response.

Aim

A versatile framework was developed to enable patient-individualized Monte Carlo simulation. A standardized dataset was established, including digital phantoms derived from 20 AD patients who received NIR light treatment.

Approach

The phantoms were synthesized and mapped with multispectral optical parameters, integrating cortical parcellation, subcortical segmentation, and sparse annotation. Structure-related light fluence pathways and dose-response relationships were elucidated using simulation results and cognitive/functional assessments.

Results

The capability for enhancing simulation fidelity and exploring dose-response relationships was verified using standard templates and clinical data. Linear independence was identified between changes in activities of daily living scale scores and energy deposition in gray matter.

Conclusions

The framework offers a solution toward dose-response analysis, parameter optimization, and safety control in the clinical translation for multiple treatment paradigms, demonstrating promise for individualized, standardized, and precise intervention planning.

Tutorial on methods for estimation of optical absorption and scattering properties of tissue

Significance

The estimation of tissue optical properties using diffuse optics has found a range of applications in disease detection, therapy monitoring, and general health care. Biomarkers derived from the estimated optical absorption and scattering coefficients can reflect the underlying progression of many biological processes in tissues.

Aim

Complex light-tissue interactions make it challenging to disentangle the absorption and scattering coefficients, so dedicated measurement systems are required. We aim to help readers understand the measurement principles and practical considerations needed when choosing between different estimation methods based on diffuse optics.

Approach

The estimation methods can be categorized as: steady state, time domain, time frequency domain (FD), spatial domain, and spatial FD. The experimental measurements are coupled with models of light-tissue interactions, which enable inverse solutions for the absorption and scattering coefficients from the measured tissue reflectance and/or transmittance.

Results

The estimation of tissue optical properties has been applied to characterize a variety of ex vivo and in vivo tissues, as well as tissue-mimicking phantoms. Choosing a specific estimation method for a certain application has to trade-off its advantages and limitations.

Conclusion

Optical absorption and scattering property estimation is an increasingly important and accessible approach for medical diagnosis and health monitoring.

MCOCT: an experimentally and numerically validated, open-source Monte Carlo simulator for optical coherence tomography

Here, we present MCOCT, a Monte Carlo simulator for optical coherence tomography (OCT), incorporating a Gaussian illumination scheme and bias to increase backscattered event collection. MCOCT optical fluence was numerically compared and validated to an established simulator (MCX) and showed concordance at the focus while diverging slightly with distance to it. MCOCT OCT signals were experimentally compared and validated to OCT signals acquired in tissue-mimicking phantoms with known optical properties and showed a similar attenuation pattern with increasing depth while diverging beyond 1.5 mm and proximal to layer interfaces. MCOCT may help in the design of OCT systems for a wide range of applications.

Importance sampling-accelerated simulation of full-spectrum backscattered diffuse reflectance

The Monte Carlo (MC) method is one of the most widely used numerical tools to model the light interaction with tissue. However, due to the low photon collection efficiency and the need to simulate the entire emission spectrum, it is computationally expensive to simulate the full-spectrum backscattered diffuse reflectance (F-BDR). Here, we propose an acceleration scheme based on importance sampling (IS). We derive the biasing sampling function tailored for simulating BDR based on the two-term scattering phase function (TT). The parameters of the TT function at different wavelengths are directly obtained by fitting the Mie scattering phase function. Subsequently, we incorporate the TT function and its corresponding biased function into the redefined IS process and realize the accelerated simulation of F-BDR. Phantom simulations based on the Fourier-domain optical coherence tomography (FD-OCT) are conducted to demonstrate the efficiency of the proposed method. Compared to the original simulator without IS, our proposed method achieves a 373× acceleration in simulating the F-BDR of the multi-layer phantom with a relative mean square error (rMSE) of less than 2%. Besides, by parallelly computing A-lines, our method enables the simulation of an entire B-scan in less than 0.4 hours. To our best knowledge, it is the first time that a volumetric OCT image of a complex phantom is simulated. We believe that the proposed acceleration method can be readily applied to fast simulations of various F-BDR-dependent applications. The source codes of this manuscript are also publicly available online.

Monte Carlo-based full-wavelength simulator of Fourier-domain optical coherence tomography

Monte Carlo (MC) simulation has been widely used to study imaging procedures, including Fourier-domain optical coherence tomography (FD-OCT). Despite the broadband nature of FD-OCT, the results obtained at a single wavelength are often used in previous studies. Some wavelength-relied imaging applications, such as spectroscopic OCT (S-OCT), are unlikely to be simulated in this way due to the lack of information from the entire spectrum. Here, we propose a novel simulator for full-wavelength MC simulation of FD-OCT. All wavelengths within the emission spectrum of the light source will be simulated, and the optical properties derived from Mie theory will be applied. We further combine the inverse discrete Fourier transform (IDFT) with a probability distribution-based signal pre-processing to combat the excessive noises in the OCT signal reconstruction, which is caused by the non-uniform distribution of the scattering events at different wavelengths. Proof-of-concept simulations are conducted to show the excellent performance of the proposed simulator on signal reconstruction and optical properties extraction. Compared with the conventional method, the proposed simulator is more accurate and could better preserve the wavelength-dependent features. For example, the mean square error (MSE) computed between the backscattering coefficient extracted by the proposed simulator and the ground truth is 0.11, which is far less than the value (7.67) of the conventional method. We believe this simulator could be an effective tool to study the wavelength dependency in FD-OCT imaging as well as a preferred solution for simulating spectroscopic OCT.

Modeling toolchain for realistic simulation of photoacoustic data acquisition

SIGNIFICANCE

Physics-based simulations of photoacoustic (PA) signals are used to validate new methods, to characterize PA setups and to generate training datasets for machine learning. However, a thoroughly validated PA simulation toolchain that can simulate realistic images is still lacking.

AIM

A quantitative toolchain was developed to model PA image acquisition in complex tissues, by simulating both the optical fluence and the acoustic wave propagation.

APPROACH

Sampling techniques were developed to decrease artifacts in acoustic simulations. The performance of the simulations was analyzed by measuring the point spread function (PSF) and using a rotatable three-channel phantom, filled with cholesterol, a human carotid plaque sample, and porcine blood. Ex vivo human plaque samples were simulated to validate the methods in more complex tissues.

RESULTS

The sampling techniques could enhance the quality of the simulated PA images effectively. The resolution and intensity of the PSF in the turbid medium matched the experimental data well. Overall, the appearance, signal-to-noise ratio and speckle of the images could be simulated accurately.

CONCLUSIONS

A PA toolchain was developed and validated, and the results indicate a great potential of PA simulations in more complex and heterogeneous media.

Highly reliable SERS substrate based on plasmonic hybrid coupling between gold nanoislands and periodic nanopillar arrays

To improve both sensitivity and reliability, a hybrid SERS substrate of combining gold nanoislands (GNI) with periodic MgF₂ nanopillar arrays was successfully developed. SERS detection performance of the proposed substrates was evaluated in terms of enhancement effect, signal-to-noise ratio (SNR), linearity, reproducibility and repeatability, and compared with the performance of a conventional SERS substrate based on GNI. Experimental and simulation results presented that significant improvement of SERS intensity and SNR by more than 3 times and a notable reduction in relative standard deviation were obtained. We hope that the suggested SERS platform with unique advantages in sensitivity and reliability could be extended to point-of-care detection of a variety of biomolecular reactions.