Subdiffuse scattering model for single fiber reflectance spectroscopy

Non-invasive assessment of skin hydration and sensation with diffuse reflectance spectroscopy

The skin is a vital organ in the human body, providing essential functions such as protection, sensation, and metabolism. Skin hydration is one of the crucial factors in maintaining normal skin function. Insufficient skin hydration can lead to dryness, shedding of the stratum corneum, a decrease in skin barrier function, and may cause skin inflammation. Therefore, maintaining or improving skin hydration is critical in promoting healthy skin. Currently, the commonly used method for measuring skin hydration is bioelectrical capacitance analysis, which is often affected by environmental humidity and can only provide limited information. To overcome these limitations, this study used diffuse reflectance spectroscopy (DRS) in the wavelength range of 400-1000 nm to quantify skin absorption and scattering modulation caused by changes in skin hydration states. The advantages of this technique include rapid measurements, non-invasiveness, a straightforward optical setup, and suitability for prolonged skin monitoring. We found that DRS-derived skin absorption coefficients had a correlation coefficient of 0.93 with the skin capacitance at various skin hydration states. In addition, our findings reveal that absorption and scattering coefficients may be useful in discerning skin hydration enhancement induced by applying soaked cotton pads or cosmeceutical facial masks, as well as evaluating skin sensation. This study verifies that the DRS method could be a convenient and effective tool for evaluating skin hydration related information.

Diffuse photon remission associated with the center-illuminated-area-detection geometry. II. Approach to the time-domain model

This part proposes a model of time-dependent diffuse photon remission for the center-illuminated-area-detection (CIAD) geometry, by virtue of area integration of the radially resolved time-dependent diffuse photon remission formulated with the master-slave dual-source scheme demonstrated in Part I for steady-state measurements. The time-domain model is assessed against Monte Carlo (MC) simulations limiting to only the Heyney-Greenstein scattering phase function for CIAD of physical scales and medium properties relevant to single-fiber reflectance (SfR) and over a 2 ns duration, in compliance with the timespan of the only experimental report of SfR demonstrated with a 50 µm gradient index fiber. The time-domain model-MC assessments are carried out for an absorption coefficient ranging three orders of magnitude over [0.001,0.01,0.1,1]m m -1 at a fixed scattering, and a reduced scattering coefficient ranging three orders of magnitude over [0.01,0.1,1,10]m m -1 at a fixed absorption, among others. Photons of shorter and longer propagation times, relative to the diameter of the area of collection, respond differently to the scattering and absorption changes. Limited comparisons of MC between CIAD and a top-hat geometry as the idealization of SfR reveal that the time-domain photon remissions of the two geometries differ appreciably in only the early arriving photons.

Model for the diffuse reflectance in spatial frequency domain imaging

Significance

In spatial frequency domain imaging (SDFI), tissue is illuminated with sinusoidal intensity patterns at different spatial frequencies. For low spatial frequencies, the reflectance is diffuse and a model derived by Cuccia et al. (doi 10.1117/1.3088140) is commonly used to extract optical properties. An improved model resulting in more accurate optical property extraction could lead to improved diagnostic algorithms.

Aim

To develop a model that improves optical property extraction for the diffuse reflectance in SFDI compared to the model of Cuccia et al.

Approach

We derive two analytical models for the diffuse reflectance, starting from the theoretical radial reflectance R ( ρ ) for a pencil-beam illumination under the partial current boundary condition (PCBC) and the extended boundary condition (EBC). We compare both models and the model of Cuccia et al. to Monte Carlo simulations.

Results

The model based on the PCBC resulted in the lowest errors, improving median relative errors compared to the model of Cuccia et al. by 45% for the reflectance, 10% for the reduced scattering coefficient and 64% for the absorption coefficient.

Conclusions

For the diffuse reflectance in SFDI, the model based on the PCBC provides more accurate results than the currently used model by Cuccia et al.

Diffuse photon remission associated with the center-illuminated-area-detection geometry: Part I, an approach to the steady-state model

Diffuse photon remission associated with the center-illuminated-area-detection (CIAD) geometry has been useful for non-contact sensing and may inform single-fiber reflectance (SfR). This series of work advances model approaches that help enrich the understanding and applicability of the photon remission by CIAD. The general approach is to derive the diffuse photon remission by the area integration of the radially resolved diffuse reflectance while limiting the analysis to a medium exhibiting only the Heyney-Greenstein (HG) scattering phase function. Part I assesses the steady-state photon remission in CIAD over a reduced scattering scaled diameter of μ s ' d _{a r e a} ∈[0.5×10^-3,10³] that covers the range extensively modeled for SfR. The corresponding radially resolved diffuse reflectance is obtained by concatenating an empirical expression for the semi-ballistic region near the point-of-illumination and a formula utilizing a master-slave dual-source scheme over the semi-diffusive to a diffusive regime while being constrained by an extrapolated zero-boundary condition. The terminal algebraic photon remission is examined against Monte Carlo simulations for an absorption coefficient over [0.001,1]m m ^-1, a reduced scattering coefficient over [0.01,1000]m m ^-1, a HG scattering anisotropy factor within [0.5,0.95], and a diameter of the area of collection ranging [50,1000]µm. The algebraic model is also applied to phantom data acquired over a ∼2c m non-contact CIAD configuration and with a 200 µm SfR probe. The model approach will be extended in a subsequent work towards the time-of-flight characteristics of CIAD.

MCDataset: a public reference dataset of Monte Carlo simulated quantities for multilayered and voxelated tissues computed by massively parallel PyXOpto Python package

SIGNIFICANCE

Current open-source Monte Carlo (MC) method implementations for light propagation modeling are many times tedious to build and require third-party licensed software that can often discourage prospective researchers in the biomedical optics community from fully utilizing the light propagation tools. Furthermore, the same drawback also limits rigorous cross-validation of physical quantities estimated by various MC codes.

AIM

Proposal of an open-source tool for light propagation modeling and an easily accessible dataset to encourage fruitful communications amongst researchers and pave the way to a more consistent comparison between the available implementations of the MC method.

APPROACH

The PyXOpto implementation of the MC method for multilayered and voxelated tissues based on the Python programming language and PyOpenCL extension enables massively parallel computation on numerous OpenCL-enabled devices. The proposed implementation is used to compute a large dataset of reflectance, transmittance, energy deposition, and sampling volume for various source, detector, and tissue configurations.

RESULTS

The proposed PyXOpto agrees well with the original MC implementation. However, further validation reveals a noticeable bias introduced by the random number generator used in the original MC implementation.

CONCLUSIONS

Establishing a common dataset is highly important for the validation of existing and development of MC codes for light propagation in turbid media.

Toward improved endoscopic surveillance with multidiameter single fiber reflectance spectroscopy in patients with Barrett's esophagus

Patients with Barrett's esophagus are at an increased risk to develop esophageal cancer and, therefore, undergo regular endoscopic surveillance. Early detection of neoplasia enables endoscopic treatment, which improves outcomes. However, early Barrett's neoplasia is easily missed during endoscopic surveillance. This study investigates multidiameter single fiber reflectance spectroscopy (MDSFR) to improve Barrett's surveillance. Based on the concept of field cancerization, it may be possible to identify the presence of a neoplastic lesion from measurements elsewhere in the esophagus or even the oral cavity. In this study, MDSFR measurements are performed on non-dysplastic Barrett's mucosa, squamous mucosa, oral mucosa, and the neoplastic lesion (if present). Based on logistic regression analysis on the scattering parameters measured by MDSFR, a classifier is developed that can predict the presence of neoplasia elsewhere in the Barrett's segment from measurements on the non-dysplastic Barrett's mucosa (sensitivity 91%, specificity 71%, AUC = 0.77). Classifiers obtained from logistic regression analysis for the squamous and oral mucosa do not result in an AUC significantly different from 0.5.

Experimental validation of a recently developed model for single-fiber reflectance spectroscopy

SIGNIFICANCE

We recently developed a model for the reflectance measured with (multi-diameter) single-fiber reflectance (SFR) spectroscopy as a function of the reduced scattering coefficient μs', the absorption coefficient μa, and the phase function parameter psb. We validated this model with simulations.

AIM

We validate our model experimentally. To prevent overfitting, we investigate the wavelength-dependence of psb and propose a parametrization with only three parameters. We also investigate whether this parametrization enables measurements with a single fiber, as opposed to multiple fibers used in multi-diameter SFR (MDSFR).

APPROACH

We validate our model on 16 phantoms with two concentrations of Intralipid-20% (μs'=13 and 21  cm  -  1 at 500 nm) and eight concentrations of Evans Blue (μa  =  1 to 20  cm  -  1 at 605 nm). We parametrize psb as 10  -  5  ·    (  p1  (  λ  /  650  )    +  p2(λ/650)2  +  p3(λ/650)3  )  .

RESULTS

Average errors were 7% for μs', 11% for μa, and 16% with the parametrization of psb; and 7%, 17%, and 16%, respectively, without. The parametrization of psb improved the fit speed 25 times (94 s to <4  s). Average errors for only one fiber were 50%, 33%, and 186%, respectively.

CONCLUSIONS

Our recently developed model provides accurate results for MDSFR measurements but not for a single fiber. The psb parametrization prevents overfitting and speeds up the fit.

Active line scan with spatial gating for sub-diffuse reflectance imaging of scatter microtexture

We examine the value of an active line scan with spatial gating for imaging sub-diffuse, wide-field reflectance microtexture. Line scanning combined with spatial gating and linear translation can be used for localized detection of features in the surface layer of a turbid target. The line scan provides broadband spatial frequency modulation, and the spatial gating effectively high-pass filters the reflectance. The major benefit of this approach is that of high dynamic range (70%-90%) signal preservation and high contrast to noise when imaging at high spatial frequencies. Alternative approaches, such as spatial frequency domain imaging, are degraded by low dynamic range in demodulated images, making it nearly impossible to image over a wide field of view at frequencies over 1.5mm-1 using commercial technology. As such, active line scanning with spatial gating presents as an inherently high sensitivity and high dynamic range method of imaging microscopic scattering features in only the surface layer of a turbid medium.

Subdiffuse scattering and absorption model for single fiber reflectance spectroscopy

Single fiber reflectance (SFR) spectroscopy is a technique that is sensitive to small-scale changes in tissue. An additional benefit is that SFR measurements can be performed through endoscopes or biopsy needles. In SFR spectroscopy, a single fiber emits and collects light. Tissue optical properties can be extracted from SFR spectra and related to the disease state of tissue. However, the model currently used to extract optical properties was derived for tissues with modified Henyey-Greenstein phase functions only and is inadequate for other tissue phase functions. Here, we will present a model for SFR spectroscopy that provides accurate results for a large range of tissue phase functions, reduced scattering coefficients, and absorption coefficients. Our model predicts the reflectance with a median error of 5.6% compared to 19.3% for the currently used model. For two simulated tissue spectra, our model fit provides accurate results.