Development of thin skin mimicking bilayer solid tissue phantoms for optical spectroscopic studies

Measurement of anisotropy factor of nanoparticle embedded tumor phantoms for plasmonic photothermal therapeutics

Measurement of anisotropy factor (g) in the presence of nanoparticles (NPs) is important for understanding light distribution for plasmonic photothermal cancer therapeutics. Here, anisotropy factor is investigated through bilayer phantoms (epidermal and dermal) of various thicknesses incorporated with gold nanorods (GNRs) concentrations of 10-40 μg/mL by using in-house developed goniometric setup. Results show that 10 μg/mL GNRs in the phantom increase g by ~50% (g = 0.9471) w.r.t. phantom without NPs. Higher concentrations (40 μg/mL) of GNRs decrease g by ~43% (g = 0.5341) w.r.t. phantom with 10 μg/mL GNRs. For 40 μg/mL GNRs phantom, the anisotropy factor reduces by 47% for phantom thickness from 600 to 1800 μm. Anisotropy factor of GNR embedded phantom increased by 44% by using glycerol (10%-40%). Incorporation of NPs in a tumor significantly affects g, a major parameter for light distribution. These measurements provide insights for light scattering based on nanoparticle doses for plasmonic photothermal therapeutics.

Dynamic change in optical properties of a nanoparticle embedded tumor phantom for plasmonic photothermal cancer therapeutics

In this study, the temporal dynamic changes in optical properties of gold nanorods (GNR) embedded tumor phantom, during photothermal interaction, are reported for plasmonic photothermal therapeutics. Tumor mimicking bilayer phantoms were prepared by using 1% agarose incorporated with 0.1% coffee powder, 0.3% intralipid solution as epidermis layer; 3% intralipid solution and 0.3% human hemoglobin (Hb) powder as dermis layer. On incorporating GNRs of concentrations 10, 20, and 40 μg/ml within the phantom, the absorption coefficients increases 4-8 times, while there is minimal change in the reduced scattering coefficients. Further the absorption coefficient increased by ~8% with the incorporation of GNRs of concentration 40 μg/ml, while no considerable dynamic change in the optical properties is observed for the phantom embedded with GNRs of concentrations 10, and 20 μg/ml. The discussed results are useful for the selection of GNRs dose for pre-treatment planning of plasmonic photothermal cancer therapeutics.

Optical Epidermal Mimicry from Ultraviolet to Infrared Wavelengths

Optical tissue phantoms present substantial value for medical imaging and therapeutic applications. We have developed an epidermal tissue phantom to mimic the optical properties of human skin from the ultraviolet to the infrared region, exceeding the breadth of existing studies. An epoxy matrix is combined with melanin-mimicking polydopamine via a cost-effective fabrication strategy. Reflectance and transmittance measurements enable calculation of the wavelength-dependent complex refractive index and absorption coefficient. Results are compared with literature data to establish agreement with a real human epidermis. By analyzing emissive power at a typical skin temperature, the epidermal tissue phantom is shown to accurately mimic the radiative properties of human skin. This simple, multifunctional material represents a promising substitute for human tissue for a variety of medical and bioengineering applications.

Monte Carlo method for assessment of a multimodal insertable biosensor

SIGNIFICANCE

Continuous glucose monitors (CGMs) are increasingly utilized as a way to provide healthcare to the over 10% of Americans that have diabetes. Fully insertable and optically transduced biosensors are poised to further improve CGMs by extending the device lifetime and reducing cost. However, optical modeling of light propagation in tissue is necessary to ascertain device performance.

AIM

Monte Carlo modeling of photon transport through tissue was used to assess the luminescent output of a fully insertable glucose biosensor that uses a multimodal Förster resonance energy transfer competitive binding assay and a phosphorescence lifetime decay enzymatic assay.

APPROACH

A Monte Carlo simulation framework of biosensor luminescence and tissue autofluorescence was built using MCmatlab. Simulations were first validated against previous research and then applied to predict the response of a biosensor in development.

RESULTS

Our results suggest that a diode within the safety standards for light illumination on the skin, with far-red excitation, allows the luminescent biosensor to yield emission strong enough to be detectable by a common photodiode.

CONCLUSIONS

The computational model showed that the expected fluorescent power output of a near-infrared light actuated barcode was five orders of magnitude greater than a visible spectrum excited counterpart biosensor.

Textural Feature Analysis of Optical Coherence Tomography Phantoms

Optical coherence tomography (OCT) is an imaging technique based on interferometry of backscattered lights from materials and biological samples. For the quantitative evaluation of an OCT system, artificial optical samples or phantoms are commonly used. They mimic the structure of biological tissues and can provide a quality standard for comparison within and across devices. Phantoms contain medium matrix and scattering particles within the dimension range of target biological structures such as the retina. The aim was to determine if changes in speckle derived optical texture could be employed to classify the OCT phantoms based on their structural composition. Four groups of phantom types were prepared and imaged. These comprise different concentrations of a medium matrix (gelatin solution), different sized polystyrene beads (PBs), the volume of PBs and different refractive indices of scatterers (PBs and SiO2). Texture analysis was applied to detect subtle optical differences in OCT image intensity, surface coarseness and brightness of regions of interest. A semi-automated classifier based on principal component analysis (PCA) and support vector machine (SVM) was applied to discriminate the various texture models. The classifier detected correctly different phantom textures from 82% to 100%, demonstrating that analysis of the texture of OCT images can be potentially used to discriminate biological structure based on subtle changes in light scattering.

Water and hemoglobin modulated gelatin-based phantoms to spectrally mimic inflamed tissue in the validation of biomedical techniques and the modeling of microdialysis data

SIGNIFICANCE

Tissue simulating phantoms are an important part of validating biomedical optical techniques. Tissue pathology in inflammation and oedema involves changes in both water and hemoglobin fractions.

AIM

We present a method to create solid gelatin-based phantoms mimicking inflammation and oedema with adjustable water and hemoglobin fractions.

APPROACH

One store-bought gelatin and one research grade gelatin were evaluated. Different water fractions were obtained by varying the water-to-gelatin ratio. Ferrous stabilized human hemoglobin or whole human blood was added as absorbers, and the stability and characteristics of each were compared. Intralipid® was used as the scatterer. All phantoms were characterized using spatial frequency domain spectroscopy.

RESULTS

The estimated water fraction varied linearly with expected values (R2  =  0.96 for the store-bought gelatin and R2  =  0.99 for the research grade gelatin). Phantoms including ferrous stabilized hemoglobin stayed stable up to one day but had methemoglobin present at day 0. The phantoms with whole blood remained stable up to 3 days using the store-bought gelatin.

CONCLUSIONS

A range of physiological relevant water fractions was obtained for both gelatin types, with the stability of the phantoms including hemoglobin differing between the gelatin type and hemoglobin preparation. These low-cost phantoms can incorporate other water-based chromophores and be fabricated as thin sheets to form multilayered structures.

Optical properties of PlatSil SiliGlass tissue-mimicking phantoms

In this work, we revise the preparation procedure and conduct an in depth characterization of optical properties for the recently proposed silicone-based tissue-mimicking optical phantoms in the spectral range from 475 to 925 nm. The optical properties are characterized in terms of refractive index and its temperature dependence, absorption and reduced scattering coefficients and scattering phase function related quantifiers. The scattering phase function and related quantifiers of the optical phantoms are first assessed within the framework of the Mie theory by using the measured refractive index of SiliGlass and size distribution of the hollow silica spherical particles that serve as scatterers. A set of purely absorbing optical phantoms in cuvettes is used to evaluate the linearity of the absorption coefficient with respect to the concentration of black pigment that serves as the absorber. Finally, the optical properties in terms of the absorption and reduced scattering coefficients and the subdiffusive scattering phase function quantifier γ are estimated for a subset of phantoms from spatially resolved reflectance using deep learning aided inverse models. To this end, an optical fiber probe with six linearly arranged optical fibers is used to collect the backscattered light at small and large distances from the source fiber. The underlying light propagation modeling is based on the stochastic Monte Carlo method that accounts for all the details of the optical fiber probe.

Model-based quantitative optical biopsy in multilayer in vitro soft tissue models for whole field assessment of nonmelanoma skin cancer

Optical techniques such as fluorescence and diffuse reflectance spectroscopy are proven to have the potential to provide tissue discrimination during the development of malignancies and hence treated as potential tools for noninvasive optical biopsy in clinical diagnostics. Quantitative optical biopsy is challenging and hence the majority of the existing strategies are based on a qualitative assessment of the concerned tissue. Light-tissue interaction models as well as precise optical phantoms can greatly help in the former and here we present a pilot study to assess the optical properties of a multilayer tissue-specific optical phantom with the help of a database generated using multilayer-Monte Carlo (MCML) models. A set of optical models mimicking the properties of actual and diseased conditions of tissues associated with nonmelanoma skin cancer (NMSC) were devised and MCML simulations of fluorescence and diffuse reflectance were performed on these models to generate the spectral signature of identified biomarkers of NMSC such as hemoglobin, flavin adenine dinucleotide, and collagen. A model library was generated and with the extracted features from modeled spectra, classification of normal and NMSC conditions were tested using the [Formula: see text]-nearest neighbor (KNN) classifier. Using an in-house assembled scan-based automated bimodal spectral imaging system with reflectance and fluorescence modalities of operation, a layered, thin, tissue equivalent phantom, fabricated with controlled optical properties mimicking normal and NMSC conditions were tested. The spectral signatures corresponding to the NMSC biomarkers were acquired from this phantom and extracted features from the spectra were tested using the KNN classifier and classification accuracy of 100% was achieved. For further quantitative analysis, the experimental and simulated spectra were compared with respect to the light intensity at the emission peak or absorption dips, spectral line width, and average intensity over a range of wavelength of interest and observed to be analogous within specified and systematic error limits. This methodology is expected to give a better quantitative approach for estimation of tissue properties by correlating the experimental and simulated data.