In vivo real-time imaging of cutaneous hemoglobin concentration, oxygen saturation, scattering properties, melanin content, and epidermal thickness with visible spatially modulated light

Reciprocal polarization imaging of optical activity in reflection

We present reciprocal polarization imaging for the optical activity of chiral media in reflection geometry. The method is based on the reciprocal polar decomposition of backscattering Mueller matrices accounting for the reciprocity of light waves in forward and backward scattering paths. Anisotropic depolarization is introduced to gain sensitivity to optical activity in backscattering. Experiments with glucose solutions show that while the Lu-Chipman decomposition of the backscattering Mueller matrices produces erroneous results, reciprocal polarization imaging correctly retrieves the optical activity of chiral media. The recovered optical rotation agrees with that obtained in the forward geometry and increases linearly with the concentration and thickness of the chiral media. The potential for in vivo glucose monitoring based on optical activity sensing using reciprocal polarization imaging is then discussed.

Multi-frequency spatial frequency domain imaging: a depth-resolved optical scattering model to isolate scattering contrast in thin layers of skin

Significance

Current methods for wound healing assessment rely on visual inspection, which gives qualitative information. Optical methods allow for quantitative non-invasive measurements of optical properties relevant to wound healing.

Aim

Spatial frequency domain imaging (SFDI) measures the absorption and reduced scattering coefficients of tissue. Typically, SFDI assumes homogeneous tissue; however, layered structures are present in skin. We evaluate a multi-frequency approach to process SFDI data that estimates depth-specific scattering over differing penetration depths.

Approach

Multi-layer phantoms were manufactured to mimic wound healing scattering contrast in depth. An SFDI device imaged these phantoms and data were processed according to our multi-frequency approach. The depth sensitive data were then compared with a two-layer scattering model based on light fluence.

Results

The measured scattering from the phantoms changed with spatial frequency as our two-layer model predicted. The performance of two δ - P 1 models solutions for SFDI was consistently better than the standard diffusion approximation.

Conclusions

We presented an approach to process SFDI data that returns depth-resolved scattering contrast. This method allows for the implementation of layered optical models that more accurately represent physiologic parameters in thin tissue structures as in wound healing.

Reliability of Postoperative Free Flap Monitoring with a Novel Prediction Model Based on Supervised Machine Learning

BACKGROUND

Postoperative free flap monitoring is a critical part of reconstructive microsurgery. Postoperative clinical assessments rely heavily on specialty-trained staff. Therefore, in regions with limited specialist availability, the feasibility of performing microsurgery is restricted. This study aimed to apply artificial intelligence in postoperative free flap monitoring and validate the ability of machine learning in predicting and differentiating types of postoperative free flap circulation.

METHODS

Postoperative data from 176 patients who received free flap surgery were prospectively collected, including free flap photographs and clinical evaluation measures. Flap circulation outcome variables included normal, arterial insufficiency, and venous insufficiency. The Synthetic Minority Oversampling Technique plus Tomek Links (SMOTE-Tomek) was applied for data balance. Data were divided into 80%:20% for model training and validation. Shapley Additive Explanations were used for prediction interpretations of the model.

RESULTS

Of 805 total included flaps, 555 (69%) were normal, 97 (12%) had arterial insufficiency, and 153 (19%) had venous insufficiency. The most effective prediction model was developed based on random forest, with an accuracy of 98.4%. Temperature and color differences between the flap and the surrounding skin were the most significant contributing factors to predict a vascular compromised flap.

CONCLUSIONS

This study demonstrated the reliability of a machine-learning model in differentiating various types of postoperative flap circulation. This novel technique may reduce the burden of free flap monitoring and encourage the broader use of reconstructive microsurgery in regions with a limited number of staff specialists.

Generation of skin tone and pigmented region-modified images using a pigment discrimination model trained with an optical approach

BACKGROUND

Skin tone and pigmented regions, associated with melanin and hemoglobin, are critical indicators of skin condition. While most prior research focuses on pigment analysis, the capability to simulate diverse pigmentation conditions could greatly broaden the range of applications. However, current methodologies have limitations in terms of numerical control and versatility.

METHODS

We introduce a hybrid technique that integrates optical methods with deep learning to produce skin tone and pigmented region-modified images with numerical control. The pigment discrimination model produces melanin, hemoglobin, and shading maps from skin images. The outputs are reconstructed into skin images using a forward problem-solving approach, with model training aimed at minimizing the discrepancy between the reconstructed and input images. By adjusting the melanin and hemoglobin maps, we create pigment-modified images, allowing precise control over changes in melanin and hemoglobin levels. Changes in pigmentation are quantified using the individual typology angle (ITA) for skin tone and melanin and erythema indices for pigmented regions, validating the intended modifications.

RESULTS

The pigment discrimination model achieved correlation coefficients with clinical equipment of 0.915 for melanin and 0.931 for hemoglobin. The alterations in the melanin and hemoglobin maps exhibit a proportional correlation with the ITA and pigment indices in both quantitative and qualitative assessments. Additionally, regions overlaying melanin and hemoglobin are demonstrated to verify independent adjustments.

CONCLUSION

The proposed method offers an approach to generate modified images of skin tone and pigmented regions. Potential applications include visualizing alterations for clinical assessments, simulating the effects of skincare products, and generating datasets for deep learning.

Multiexposure laser speckle contrast analysis system calibration limited by perfusion-dependent scattering on the skin

Significance

Application of multiexposure speckle contrast imaging (MESI) methods for perfusion measurements can correct for the contribution of static scattering of the skin, at the expense of reduced temporal resolution as compared to classical single-exposure methods. Persistence of tissue scattering properties during the measurements could allow for an initial calibration and enhancement of the temporal resolution of the measurements.

Aim

We aim to study the influence of the perfusion on the light scattering of the forearm skin and to use the obtained data for the enhancement of the temporal resolution.

Approach

A wide range of skin perfusion states was induced while monitoring the changes in the dynamic range of the exposure-dependent contrast. Different measurement and evaluation methods were tested based on an initial MESI calibration followed by image recording with reduced number of exposure time values.

Results

The changes in the skin perfusion can alter not only the contribution of the static scattering to the speckle images but also the short-exposure time contrast limit.

Conclusions

The perfusion-dependent scattering of the skin can invalidate the precalibrations (e.g., β calibration) characterizing the combination of the given tissue and the measurement system.

Development of a platform for broadband, spectra-fitted, tissue optical phantoms

SIGNIFICANCE

Current methods of producing optical phantoms are incapable of accurately capturing the wavelength-dependent properties of tissue critical for many optical modalities.

AIM

We aim to introduce a method of producing solid, inorganic phantoms whose wavelength-dependent optical properties can be matched to those of tissue over the wavelength range of 370 to 950 nm.

APPROACH

The concentration-dependent optical properties of 20 pigments were characterized and used to determine combinations that result in optimal fits compared to the target properties over the full spectrum. Phantoms matching the optical properties of muscle and nerve, the diffuse reflectance of pale and melanistic skin, and the chromophore concentrations of a computational skin model with varying oxygen saturation ( StO 2 ) were made with this method.

RESULTS

Both optical property phantoms were found to accurately mimic their respective tissues' absorption and scattering properties across the entire spectrum. The diffuse reflectance phantoms were able to closely approximate skin reflectance regardless of skin type. All three computational skin phantoms were found to have emulated chromophore concentrations close to the model, with an average percent error for the StO 2 of 4.31%.

CONCLUSIONS

This multipigment phantom platform represents a powerful tool for creating spectrally accurate tissue phantoms, which should increase the availability of standards for many optical techniques.

Geometry design for a fully insertable glucose biosensor with multimodal optical readout

Significance

Insertable optical continuous glucose monitors (CGMs) with wearable readers are a strong option for monitoring individuals with diabetes. However, a fully insertable CGM requires a small form factor while still delivering sufficient signal to be read through tissue by an external device. Previous work has suggested that a multimodal repeating unit (barcode) approach may meet these requirements, but the biosensor geometry must be optimized to meet performance criteria.

Aim

This work details in silico trials conducted to evaluate the geometry of a fully insertable multimodal optical biosensor with respect to both optical output and species diffusion in vivo.

Approach

Monte Carlo modeling is used to evaluate the luminescent output of three presupposed biosensor designs based on size constraints for an injectable and logical placement of the bar code compartments. Specifically, the sensitivity of the luminescent output to displacement of the biosensor in the X and Y directions, overall size of the selected design, and size of an individual repeating unit are analyzed. Further, an experimentally validated multiphysics model is used to evaluate the diffusion and reaction of glucose and oxygen within the biosensor to estimate the occurrence of chemical crosstalk between the assay components.

Results

A stacked cylinder multimodal biosensor 4.4 mm in length with repeating units 0.36 mm in length was found to yield a greater luminescent output than the current "barcode" biosensor design. In addition, it was found that a biosensor with enzymatic elements does not significantly deplete glucose locally and thus does not impact the diffusion profile of glucose in adjacent compartments containing nonenzymatic assays.

Conclusions

Computational modeling was used to design the geometry of a multimodal, insertable, and optical CGM to ensure that the optical output and chemical diffusion profile are sufficient for this device to function in vivo.

Spectral imaging of normal, hydrated, and desiccated porcine skin using polarized light

Significance

Spectroscopic and structural imaging of tissue layers is important for investigating tissue health. However, investigating superficial tissue is difficult using optical imaging, due to the convolved absorption and backscatter of light from deeper layers.

Aim

This report investigates the effects of hydration and desiccation of ex vivo porcine skin on the reflectance of polarized light at different wavelengths (light-emitting diodes).

Approach

We developed a spectroscopic polarized imaging system to investigate submicron changes in tissue structures. By separating polarized from depolarized backscattered light, submicron structural changes in subsurface and deeper tissue layers can be separated and monitored.

Results

The results demonstrate that (1) polarized light reflectance is about 2%, consistent with ∼6 scattering events, on average; (2) there was little wavelength dependence to the reflectance of polarized light; (3) increased hydration leads to a modest increase in total reflectance (from 0.8 to 0.9), whereas desiccation had little effect; however, hydration did not affect polarized reflectance, but desiccation slightly lowered polarized reflectance.

Conclusions

Higher scattering from the reticular dermis was likely due to swelling of collagen fiber bundles in the dermal layers, which increased fibril spacing. The epidermal skin surface showed little change due to the stratum corneum resisting desiccation and maintaining hydration.

Wavelength and frequency optimization in spatial frequency domain imaging for two-layer tissue

Spatial frequency domain imaging is a non-contact, wide-field, fast-diffusion optical imaging technique, which in principle uses steady-state spatially modulated light to irradiate biological tissue, reconstruct two-dimensional or three-dimensional tissue optical characteristic map through optical transmission model, and further quantify the spatial distribution of tissue physiological parameters by multispectral imaging technique. The selection of light source wavelength and light field spatial modulation frequency is directly related to the accuracy of tissue optical properties and tissue physiological parameters extraction. For improvement of the measurement accuracy of optical properties and physiological parameters in the two-layer tissue, a multispectral spatial frequency domain imaging system is built based on liquid crystal tunable filter, and a data mapping table of spatially resolved diffuse reflectance and optical properties of two-layer tissue is established based on scaling Monte Carlo method. Combined with the dispersion effect and window effect of light-tissue interaction, the study applies numerical simulation to optimize the wavelength in the 650-850 nm range with spectral resolution of 10 nm. In order to minimize the uncertainty of the optical properties, Cramér-Rao bound is used to optimize the optical field spatial modulation frequency by transmitting the uncertainty of optical properties. The results showed that in order to realize the detection of melanin, oxyhemoglobin, deoxyhemoglobin, water and other physiological parameters in two-layer tissue, the best wavelength combination was determined as 720, 730, 760 and 810 nm according to the condition number. The findings of the Cramér-Rao bound analysis reveal that the uncertainty of optical characteristics for the frequency combinations [0, 0.3] mm^-1, [0, 0.2] mm^-1, and [0, 0.1] mm^-1 increases successively. Under the optimal combination of wavelength and frequency, the diffuse reflectance of the gradient gray-scale plate measured by the multi-spectral spatial frequency domain imaging system is linearly correlated with the calibration value. The error between the measured liquid phantom absorption coefficient and the collimation projection system based on colorimetric dish is less than 2%. The experimental results of human brachial artery occlusion indicate that under the optimal wavelength combination, the change of the second layer absorption coefficient captured by the three frequency combinations decreases in turn, so as the change of oxygen saturation.

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.

Multimodal hyperspectral fluorescence and spatial frequency domain imaging for tissue health diagnostics of the oral cavity

A multimodal, hyperspectral imaging system was built for diagnostics of oral tissues. The system, termed Hyperspectral-Fluorescence-Spatial Frequency Domain Imaging (Hy-F-SFDI), combines the principles of spatial frequency domain imaging, quantitative light fluorescence, and CIELAB color measurement. Hy-F-SFDI employs a compact LED projector, excitation LED, and a 16 channel hyperspectral camera mounted on a custom platform for tissue imaging. A two layer Monte Carlo approach was used to generate a reference table for quick tissue analysis. To demonstrate the clinical capabilities of Hy-F-SFDI, we used the system to quantify gingival tissue hemoglobin volume fraction, detect caries, bacterial activity, and measure tooth color of a volunteer at different time points. Hy-F-SFDI was able to measure quantitative changes in tissue parameters.

In vivo two-dimensional quantitative imaging of skin and cutaneous microcirculation with perturbative spatial frequency domain imaging (p-SFDI)

We introduce perturbative spatial frequency domain imaging (p-SFDI) for fast two-dimensional (2D) mapping of the optical properties and physiological characteristics of skin and cutaneous microcirculation using spatially modulated visible light. Compared to the traditional methods for recovering 2D maps through a pixel-by-pixel inversion, p-SFDI significantly shortens parameter retrieval time, largely avoids the random fitting errors caused by measurement noise, and enhances the image reconstruction quality. The efficacy of p-SFDI is demonstrated by in vivo imaging forearm of one healthy subject, recovering the 2D spatial distribution of cutaneous hemoglobin concentration, oxygen saturation, scattering properties, the melanin content, and the epidermal thickness over a large field of view. Furthermore, the temporal and spatial variations in physiological parameters under the forearm reactive hyperemia protocol are revealed, showing its applications in monitoring temporal and spatial dynamics.

Articular cartilage optical properties in the near-infrared (NIR) spectral range vary with depth and tissue integrity

Optical properties of biological tissues in the NIR spectral range have demonstrated significant potential for in vivo diagnostic applications and are critical parameters for modelling light interaction in biological tissues. This study aims to investigate the optical properties of articular cartilage as a function of tissue depth and integrity. The results suggest consistent wavelength-dependent variation in optical properties between cartilage depth-wise zones, as well as between healthy and degenerated tissue. Also, statistically significant differences (p<0.05) in both optical properties were observed between the different cartilage depth-wise zones and as a result of tissue degeneration. When taken into account, the outcome of this study could enable accurate modelling of light interaction in cartilage matrix and could provide useful diagnostic information on cartilage integrity.

Handheld spatial frequency domain imager for noninvasive Sjögren's syndrome labial salivary gland biopsy

A labial salivary gland biopsy (LSGB) plays an essential role in diagnosing Sjögren's syndrome (SS), but its clinical application is limited due to its invasiveness. Here, we present a handheld single snapshot multiple-frequency demodulation-spatial frequency domain imaging (SSMD-SFDI) device for a rapid optical biopsy of labial salivary glands noninvasively. The structural and physiological parameters of lower lip mucosa were obtained from the light reflectance of the layered oral mucosa. The recovered parameters were found to correlate strongly with the progression of SS. In our pilot study on 15 healthy subjects and 183 SS patients, a support vector machine (SVM) classifier using the measured parameters distinguished healthy subjects, LSGB I, II, III, and IV patients in sequence with AUCs of 0.979, 0.898, 0.906, and 0.978, respectively. Critical structural and physiological alterations in the mucosa due to SS were further identified and used to assess its risk using an explainable neural network. The handheld spatial frequency domain imager may serve as a valuable label-free and noninvasive tool for early diagnosing and surveying SS.

Modeling and Synthesis of Breast Cancer Optical Property Signatures With Generative Models

Is it possible to find deterministic relationships between optical measurements and pathophysiology in an unsupervised manner and based on data alone? Optical property quantification is a rapidly growing biomedical imaging technique for characterizing biological tissues that shows promise in a range of clinical applications, such as intraoperative breast-conserving surgery margin assessment. However, translating tissue optical properties to clinical pathology information is still a cumbersome problem due to, amongst other things, inter- and intrapatient variability, calibration, and ultimately the nonlinear behavior of light in turbid media. These challenges limit the ability of standard statistical methods to generate a simple model of pathology, requiring more advanced algorithms. We present a data-driven, nonlinear model of breast cancer pathology for real-time margin assessment of resected samples using optical properties derived from spatial frequency domain imaging data. A series of deep neural network models are employed to obtain sets of latent embeddings that relate optical data signatures to the underlying tissue pathology in a tractable manner. These self-explanatory models can translate absorption and scattering properties measured from pathology, while also being able to synthesize new data. The method was tested on a total of 70 resected breast tissue samples containing 137 regions of interest, achieving rapid optical property modeling with errors only limited by current semi-empirical models, allowing for mass sample synthesis and providing a systematic understanding of dataset properties, paving the way for deep automated margin assessment algorithms using structured light imaging or, in principle, any other optical imaging technique seeking modeling. Code is available.

Spatial-Frequency Domain Imaging: An Emerging Depth-Varying and Wide-Field Technique for Optical Property Measurement of Biological Tissues

Measurement of optical properties is critical for understanding light-tissue interaction, properly interpreting measurement data, and gaining better knowledge of tissue physicochemical properties. However, conventional optical measuring techniques are limited in point measurement, which partly hinders the applications on characterizing spatial distribution and inhomogeneity of optical properties of biological tissues. Spatial-frequency domain imaging (SFDI), as an emerging non-contact, depth-varying and wide-field optical imaging technique, is capable of measuring the optical properties in a wide field-of-view on a pixel-by-pixel basis. This review first describes the typical SFDI system and the principle for estimating optical properties using the SFDI technique. Then, the applications of SFDI in the fields of biomedicine, as well as food and agriculture, are reviewed, including burn assessment, skin tissue evaluation, tumor tissue detection, brain tissue monitoring, and quality evaluation of agro-products. Finally, a discussion on the challenges and future perspectives of SFDI for optical property estimation is presented.

Dual-DMD hyperspectral spatial frequency domain imaging (SFDI) using dispersed broadband illumination with a demonstration of blood stain spectral monitoring

Spatial frequency domain imaging (SFDI) is a widefield diffuse optical measurement technique capable of generating 2D maps of sub-surface absorption and scattering in biological tissue. We developed a new hyperspectral SFDI instrument capable of collecting images at wavelengths from the visible to the near infrared. The system utilizes a custom-built monochromator with a digital micromirror device (DMD) that can dynamically select illumination wavelength bands from a broadband quartz tungsten halogen lamp, and a second DMD to provide spatially modulated sample illumination. The system is capable of imaging 10 wavelength bands in approximately 25 seconds. The spectral resolution can be varied from 12 to 30 nm by tuning the input slit width and the output DMD column width. We compared the optical property extraction accuracy between the new device and a commercial SFDI system and found an average error of 23% in absorption and 6% in scattering. The system was highly stable, with less than 5% variation in absorption and less than 0.2% variation in scattering across all wavelengths over two hours. The system was used to monitor hyperspectral changes in the optical absorption and reduced scattering spectra of blood exposed to air over 24 hours. This served as a general demonstration of the utility of this system, and points to a potential application for blood stain age estimation. We noted significant changes in both absorption and reduced scattering spectra over multiple discrete stages of aging. To our knowledge, these are the first measurement of changes in scattering of blood stains. This hyperspectral SFDI system holds promise for a multitude of applications in quantitative tissue and diffuse sample imaging.

Dynamic microcirculation PIPE model for functional neuroimaging, non-neuroimaging, and coherent hemodynamics spectroscopy: blood volume and flow velocity variations, and vascular autoregulation

We present a dynamic microcirculation PIPE model for functional neuroimaging, non-neuroimaging, and coherent hemodynamics spectroscopy. The temporal evolution of the concentration and oxygen saturation of hemoglobin in tissue, comprised of the contributions from the arterioles, capillaries, and venules of microvasculature, is determined by time-resolved hemodynamic and metabolic variations in blood volume, flow velocity, and oxygen consumption with a fluid mechanics treatment. Key parameters regarding microcirculation can be assessed, including the effective blood transit times through the capillaries and the venules, and the rate constant of oxygen release from hemoglobin to tissue. The vascular autoregulation can further be quantified from the relationship between the resolved blood volume and flow velocity variations. The PIPE model shows excellent agreement with the experimental cerebral and cutaneous coherent hemodynamics spectroscopy (CHS) and fMRI-BOLD data. It further identifies the impaired cerebral autoregulation distinctively in hemodialysis patients compared to healthy subjects measured by CHS. This new dynamic microcirculation PIPE model provides a valuable tool for brain and other functional studies with hemodynamic-based techniques. It is instrumental in recovering physiological parameters from analyzing and interpreting the signals measured by hemodynamic-based neuroimaging and non-neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) in response to brain activation, physiological challenges, or physical maneuvers.

Single snapshot spatial frequency domain imaging for risk stratification of diabetes and diabetic foot

Diabetic foot is one of the major complications of diabetes. In this work, a real-time Single Snapshot Multiple-frequency Demodulation (SSMD) - Spatial Frequency Domain Imaging (SFDI) system was used to image the forefoot of healthy volunteers, diabetes, and diabetic foot patients. A layered skin model was used to obtain the 2D maps of optical and physiological parameters, including cutaneous hemoglobin concentration, oxygen saturation, scattering properties, melanin content, and epidermal thickness, from every single snapshot. We observed a strong correlation between the measured optical and physiological parameters and the degree of diabetes. The cutaneous hemoglobin concentration, oxygen saturation, and epidermal thickness decrease, whereas the melanin content increases with the progress of diabetes. The melanin content further increases, and the reduced scattering coefficient and scattering power are lower for diabetic foot patients than those of both healthy and diabetic subjects. High accuracies (AUC) of 97.2% (distinguishing the diabetic foot patients among all subjects), 95.2% (separating healthy subjects from the diabetes patients), and 87.8% (classifying mild vs severe diabetes), respectively, are achieved in binary classifications in sequence using the SSMD-SFDI system, demonstrating its applicability to risk stratification of diabetes and diabetic foot. The prognostic value of the SSMD-SFDI system in the prediction of the occurrence of the diabetic foot and other applications in monitoring tissue microcirculation and peripheral vascular disease are also addressed.

Analysis of skin morphological features and real-time monitoring using snapshot hyperspectral imaging

We propose a snapshot hyperspectral imaging system and methods for skin morphological feature analysis and real-time monitoring of skin activities. The analysis method includes a strategy using weighted subtractions between sub-channel images to extract absorption information due to specific chromophores within skin tissue, for example hemoglobin and melanin. Based on morphological analysis results, we carry out real-time monitoring of the skin features to verify the ability of this method to provide temporal responses of the skin tissue activities, which is experimentally shown to be useful in the measurement of heartrate, monitoring of the tissue recovery after a body exercise, and studying of the tissue response due to a vascular occlusion. Compared to conventional multispectral imaging system, the proposed system improves the device simplicity and is immune to motion artifacts. Coupled with the extraction algorithms, the hyperspectral imaging promises a robust skin assessment tool with abilities for qualitative visualization and potentially quantitative analysis of skin features, useful in the applications of cosmetics and clinical dermatology.

Quantifying skin photodamage with spatial frequency domain imaging: statistical results

We investigated the change in optical properties and vascular parameters to characterize skin tissue from mild photodamage to actinic keratosis (AK) with comparison to a published photodamage scale. Multi-wavelength spatial frequency domain imaging (SFDI) measurements were performed on the dorsal forearms of 55 adult subjects with various amounts of photodamage. Dermatologists rated the levels of photodamage based upon the photographs in blinded fashion to allow comparison with SFDI data. For characterization of statistical data, we used artificial neural networks. Our results indicate that optical and vascular parameters can be used to quantify photodamage and can discriminate between the stages as low, medium, and high grades, with the best performance of ∼70%, ∼76% and 80% for characterization of low- medium- and high-grade lesions, respectively. Ultimately, clinicians can use this noninvasive approach for risk assessment and frequent monitoring of high-risk populations.

Multi-wavelength spatial frequency domain diffuse optical tomography using single-pixel imaging based on lock-in photon counting

We present a spatial frequency domain (SFD) diffuse optical tomography for simultaneous acquisition of multi-wavelength tomographic images of turbid media. We propose a highly sensitive single-pixel SFD imaging system for simultaneously collecting multi-wavelength spatially modulated reflectance images, instead of using the expensive electron-multiplying charge-coupled device camera that requires switching between the multi-wavelength collections. The single-pixel SFD imaging system using three low-power light sources (455, 532 and 660 nm) that were intensity-modulated by square waves with three different frequencies for frequency encoding, and all the light sources were focused onto one digital micromirror device (DMD) for generating wide-field sinusoidal illumination patterns. Reflected light from the surface of the turbid media was modulated by the other DMD with many sampling patterns before being spatially integrated. Spatially integrated light signals were frequency decoded with a novel highly sensitive lock-in photon counting detection, then multi-wavelength spatially modulated reflectance images were recovered with the single-pixel imaging (SPI) method. We incorporated the two-dimensional discrete cosine transform (DCT) into the SPI method to reduce the number of sampling patterns, and, thereby, the proposed DCT-SPI scheme achieved a fast acquisition of SFD reflectance images that is desired for a dynamic SFD imaging application. Direct current (DC) and alternating current (AC) amplitudes at all the locations on the media surface were extracted from the recovered images. Multi-wavelength tomographic images were reconstructed with an inversion algorithm based on the first-order Rytov approximation of the diffusion equation, using both the extracted DC and AC amplitudes. We performed experiments using a series of tissue simulating phantoms to verify the performances of the proposed approach and compared the experimental results with those using a conventional camera-based SFD imaging system. The results demonstrate that our DCT-SPI based SFD-DOT approach is well suited for simultaneous reconstruction of multi-wavelength tomographic images to pave the way for many SFD imaging applications.

The color of skin: red diseases of the skin, nails, and mucosa

Red color is pervasive in local and systemic skin conditions. It is a color that often reflects variations of dermal blood flow and extends beyond the rubor and calor of inflammation. The pathophysiology of red skin involves remote and local chemical mediators that dilate arteriolar smooth muscle and increase blood flow to superficial vessels and capillary beds. Incident light hits hemoglobin, which preferentially absorbs light of shorter wavelengths, such as blue, and reflects warmer colors. Due to its pervasiveness and consistency, red color is a useful descriptive factor in helping narrow a differential diagnosis. Red skin disorders include a variety of conditions involving endocrine mediators, cardiovascular responses, and the disruption of the skin barrier. An understanding of the blood's role in these disorders equips clinicians to generate differential diagnoses through the lens of pathophysiology. Dermatologists can improve management by considering red skin as part of systemic disease rather than as an isolated incident.

Physiological and structural characterization of human skin in vivo using combined photothermal radiometry and diffuse reflectance spectroscopy

In this proof-of-concept study we combine two optical techniques to enable assessment of structure and composition of human skin in vivo: Pulsed photothermal radiometry (PPTR), which involves measurements of transient dynamics in mid-infrared emission from sample surface after exposure to a light pulse, and diffuse reflectance spectroscopy (DRS) in visible part of the spectrum. The analysis involves simultaneous fitting of measured PPTR signals and DRS with corresponding predictions of a Monte Carlo model of light-tissue interaction. By using a four-layer optical model of skin we obtain a good match between the experimental and model data when scattering properties of the epidermis and dermis are also optimized on an individual basis. The assessed parameter values correlate well with literature data and demonstrate the expected trends in controlled tests involving temporary obstruction of peripheral blood circulation using a pressure cuff, and acute as well as seasonal sun tanning.

Multi-beam scan analysis with a clinical LINAC for high resolution Cherenkov-excited molecular luminescence imaging in tissue

Cherenkov-excited luminescence scanned imaging (CELSI) is achieved with external beam radiotherapy to map out molecular luminescence intensity or lifetime in tissue. Just as in fluorescence microscopy, the choice of excitation geometry can affect the imaging time, spatial resolution and contrast recovered. In this study, the use of spatially patterned illumination was systematically studied comparing scan shapes, starting with line scan and block patterns and increasing from single beams to multiple parallel beams and then to clinically used treatment plans for radiation therapy. The image recovery was improved by a spatial-temporal modulation-demodulation method, which used the ability to capture simultaneous images of the excitation Cherenkov beam shape to deconvolve the CELSI images. Experimental studies used the multi-leaf collimator on a clinical linear accelerator (LINAC) to create the scanning patterns, and image resolution and contrast recovery were tested at different depths of tissue phantom material. As hypothesized, the smallest illumination squares achieved optimal resolution, but at the cost of lower signal and slower imaging time. Having larger excitation blocks provided superior signal but at the cost of increased radiation dose and lower resolution. Increasing the scan beams to multiple block patterns improved the performance in terms of image fidelity, lower radiation dose and faster acquisition. The spatial resolution was mostly dependent upon pixel area with an optimized side length near 38mm and a beam scan pitch of P = 0.33, and the achievable imaging depth was increased from 14mm to 18mm with sufficient resolving power for 1mm sized test objects. As a proof-of-concept, in-vivo tumor mouse imaging was performed to show 3D rendering and quantification of tissue pO2 with values of 5.6mmHg in a tumor and 77mmHg in normal tissue.

Measurement of tissue optical properties in the context of tissue optical clearing

Nowadays, dynamically developing optical (photonic) technologies play an ever-increasing role in medicine. Their adequate and effective implementation in diagnostics, surgery, and therapy needs reliable data on optical properties of human tissues, including skin. This paper presents an overview of recent results on the measurements and control of tissue optical properties. The issues reported comprise a brief review of optical properties of biological tissues and efficacy of optical clearing (OC) method in application to monitoring of diabetic complications and visualization of blood vessels and microcirculation using a number of optical imaging technologies, including spectroscopic, optical coherence tomography, and polarization- and speckle-based ones. Molecular modeling of immersion OC of skin and specific technique of OC of adipose tissue by its heating and photodynamic treatment are also discussed.

Quantitative diagnosis of tissue microstructure with wide-field high spatial frequency domain imaging

Non-contact and minimally invasive endoscopic optical imaging is an invaluable diagnostic tool for tissue examination and cancer screening. The point sampling techniques with high sensitivity to the tissue microenvironment are time consuming and often not affordable in clinics. There is a major clinical need for a large field-of-view (FOV) rapid screening method to highlight subtle tissue microstructural alterations. To address this unmet need, we have developed High Spatial Frequency Domain Imaging (HSFDI)-a non-contact imaging modality that spatially maps the tissue microscopic scattering structures over a large field of view (>1cm2). Based on an analytical reflectance model of sub-diffusive light from forward-peaked highly scattering media, HSFDI quantifies the spatially-resolved parameters of the light scattering phase function (i.e., the backscattering probability and the light spreading length) from the reflectance of structured light modulated at high spatial frequencies. Enhanced signal to noise ratio (SNR) is achieved at even ultra-high modulation frequencies with single snapshot multiple frequency demodulation (SSMD). The variations in tissue microstructures, including the strength of the background (pudding) refractive index fluctuation and the prominent scattering structure (plum) morphology, can then be inferred. After validation with optical phantoms, measurements of fresh ex vivo tissue samples revealed significant contrast and differentiation of the phase function parameters between different types and disease states (normal, inflammatory, and cancerous) of tissue whereas tissue absorption and reduced scattering coefficients only show modest changes. HSFDI may provide wide-field images of microscopic structural biomarkers unobtainable with either diffuse light imaging or point-based optical sampling. Potential clinical applications include the rapid screening of excised tissue and the noninvasive examination of suspicious lesions during operation.