Automatic characterization and segmentation of human skin using three-dimensional optical coherence tomography

Rapid measurement of epidermal thickness in OCT images of skin

Epidermal thickness (ET) changes are associated with several skin diseases. To measure ET, segmentation of optical coherence tomography (OCT) images is essential; manual segmentation is very time-consuming and requires training and some understanding of how to interpret OCT images. Fast results are important in order to analyze ET over different regions of skin in rapid succession to complete a clinical examination and enable the physician to discuss results with the patient in real time. The well-known CNN-graph search (CNN-GS) methodology delivers highly accurate results, but at a high computational cost. Our objective was to build a computational core, based on CNN-GS, able to accurately segment OCT skin images in real time. We accomplished this by fine-tuning the hyperparameters, testing a range of speed-up algorithms including pruning and quantization, designing a novel pixel-skipping process, and implementing the final product with efficient use of core and threads on a multicore central processing unit (CPU). We name this product CNN-GS-skin. The method identifies two defined boundaries on OCT skin images in order to measure ET. We applied CNN-GS-skin to OCT skin images, taken from various body sites of 63 healthy individuals. Compared with CNN-GS, our described method reduced computation time by 130 [Formula: see text] with minimal reduction in ET determination accuracy (from 96.38 to 94.67%).

Optical attenuation coefficient of skin under low compression

In various biomedical optics therapies, knowledge of how light is absorbed or scattered by tissues is crucial. Currently, it is suspected that a low compression applied to the skin surface may improve light delivery into tissue. However, the minimum pressure needed to be applied to significantly increase the light penetration into the skin has not been determined. In this study, we used optical coherence tomography (OCT) to measure the optical attenuation coefficient of the human forearm dermis in a low compression regime (<8k P a). Our results show low pressures such as 4 kPa to 8 kPa are sufficient to significantly increase light penetration by decreasing the attenuation coefficient by at least 1.0m m ^-1.

Multiparametric Quantitative Analysis of Photodamage to Skin Using Optical Coherence Tomography

Ultraviolet (UV) irradiation causes 90% of photodamage to skin and long-term exposure to UV irradiation is the largest threat to skin health. To study the mechanism of UV-induced photodamage and the repair of sunburnt skin, the key problem to solve is how to non-destructively and continuously evaluate UV-induced photodamage to skin. In this study, a method to quantitatively analyze the structural and tissue optical parameters of artificial skin (AS) using optical coherence tomography (OCT) was proposed as a way to non-destructively and continuously evaluate the effect of photodamage. AS surface roughness was achieved based on the characteristic peaks of the intensity signal of the OCT images, and this was the basis for quantifying AS cuticle thickness using Dijkstra's algorithm. Local texture features within the AS were obtained through the gray-level co-occurrence matrix method. A modified depth-resolved algorithm was used to quantify the 3D scattering coefficient distribution within AS based on a single-scattering model. A multiparameter assessment of AS photodamage was carried out, and the results were compared with the MTT experiment results and H&E staining. The results of the UV photodamage experiments showed that the cuticle of the photodamaged model was thicker (56.5%) and had greater surface roughness (14.4%) compared with the normal cultured AS. The angular second moment was greater and the correlation was smaller, which was in agreement with the results of the H&E staining microscopy. The angular second moment and correlation showed a good linear relationship with the UV irradiation dose, illustrating the potential of OCT in measuring internal structural damage. The tissue scattering coefficient of AS correlated well with the MTT results, which can be used to quantify the damage to the bioactivity. The experimental results also demonstrate the anti-photodamage efficacy of the vitamin C factor. Quantitative analysis of structural and tissue optical parameters of AS by OCT enables the non-destructive and continuous detection of AS photodamage in multiple dimensions.

Semisupervised representative learning for measuring epidermal thickness in human subjects in optical coherence tomography by leveraging datasets from rodent models

SIGNIFICANCE

Morphological changes in the epidermis layer are critical for the diagnosis and assessment of various skin diseases. Due to its noninvasiveness, optical coherence tomography (OCT) is a good candidate for observing microstructural changes in skin. Convolutional neural network (CNN) has been successfully used for automated segmentation of the skin layers of OCT images to provide an objective evaluation of skin disorders. Such method is reliable, provided that a large amount of labeled data is available, which is very time-consuming and tedious. The scarcity of patient data also puts another layer of difficulty to make the model more generalizable.

AIM

We developed a semisupervised representation learning method to provide data augmentations.

APPROACH

We used rodent models to train neural networks for accurate segmentation of clinical data.

RESULT

The learning quality is maintained with only one OCT labeled image per volume that is acquired from patients. Data augmentation introduces a semantically meaningful variance, allowing for better generalization. Our experiments demonstrate the proposed method can achieve accurate segmentation and thickness measurement of the epidermis.

CONCLUSION

This is the first report of semisupervised representative learning applied to OCT images from clinical data by making full use of the data acquired from rodent models. The proposed method promises to aid in the clinical assessment and treatment planning of skin diseases.

Deep-learning approach for automated thickness measurement of epithelial tissue and scab using optical coherence tomography

SIGNIFICANCE

In order to elucidate therapeutic treatment to accelerate wound healing, it is crucial to understand the process underlying skin wound healing, especially re-epithelialization. Epidermis and scab detection is of importance in the wound healing process as their thickness is a vital indicator to judge whether the re-epithelialization process is normal or not. Since optical coherence tomography (OCT) is a real-time and non-invasive imaging technique that can perform a cross-sectional evaluation of tissue microstructure, it is an ideal imaging modality to monitor the thickness change of epidermal and scab tissues during wound healing processes in micron-level resolution. Traditional segmentation on epidermal and scab regions was performed manually, which is time-consuming and impractical in real time.

AIM

We aim to develop a deep-learning-based skin layer segmentation method for automated quantitative assessment of the thickness of in vivo epidermis and scab tissues during a time course of healing within a rodent model.

APPROACH

Five convolution neural networks were trained using manually labeled epidermis and scab regions segmentation from 1000 OCT B-scan images (assisted by its corresponding angiographic information). The segmentation performance of five segmentation architectures was compared qualitatively and quantitatively for validation set.

RESULTS

Our results show higher accuracy and higher speed of the calculated thickness compared with human experts. The U-Net architecture represents a better performance than other deep neural network architectures with 0.894 at F1-score, 0.875 at mean intersection over union, 0.933 at Dice similarity coefficient, and 18.28  μm at an average symmetric surface distance. Furthermore, our algorithm is able to provide abundant quantitative parameters of the wound based on its corresponding thickness maps in different healing phases. Among them, normalized epidermal thickness is recommended as an essential hallmark to describe the re-epithelialization process of the rodent model.

CONCLUSIONS

The automatic segmentation and thickness measurements within different phases of wound healing data demonstrates that our pipeline provides a robust, quantitative, and accurate method for serving as a standard model for further research into effect of external pharmacological and physical factors.

Application of OCT-Derived Attenuation Coefficient in Acute Burn-Damaged Skin

BACKGROUND AND OBJECTIVES

There remains a need to objectively monitor burn wound healing within a clinical setting, and optical coherence tomography (OCT) is proving itself one of the ideal modalities for just such a use. The aim of this study is to utilize the noninvasive and multipurpose capabilities of OCT, along with its cellular-level resolution, to demonstrate the application of optical attenuation coefficient (OAC), as derived from OCT data, to facilitate the automatic digital segmentation of the epidermis from scan images and to work as an objective indicator for burn wound healing assessment.

STUDY DESIGN/MATERIALS AND METHODS

A simple, yet efficient, method was used to estimate OAC from OCT images taken over multiple time points following acute burn injury. This method enhanced dermal-epidermal junction (DEJ) contrast, which facilitated the automatic segmentation of the epidermis for subsequent thickness measurements. In addition, we also measured and compared the average OAC of the dermis within said burns for correlative purposes.

RESULTS

Compared with unaltered OCT maps, enhanced DEJ contrast was shown in OAC maps, both from single A-lines and completed B-frames. En face epidermal thickness and dermal OAC maps both demonstrated significant changes between imaging sessions following burn injury, such as a loss of epidermal texture and decreased OAC. Quantitative analysis also showed that OAC of acute burned skin decreased below that of healthy skin following injury.

CONCLUSIONS

Our study has demonstrated that the OAC estimated from OCT data can be used to enhance imaging contrast to facilitate the automatic segmentation of the epidermal layer, as well as help elucidate our understanding of the pathological changes that occur in human skin when exposed to acute burn injury, which could serve as an objective indicator of skin injury and healing.

Two-dimensional correlation (2D) method for improving the accuracy of OCT-based noninvasive blood glucose concentration (BGC) monitoring

The optical scattering coefficient (μ_s) in the dermis layer of human skin obtained with optical coherence tomography (OCT) has shown to have a strong correlation with the blood glucose concentration (BGC), which can be used for noninvasive BGC monitoring. Unfortunately, the nonhomogeneity in the skin may cause inaccuracies for the BGC analysis. In this paper, we propose a 2D correlation analysis method to identify 2D regions in the skin with μ_s sensitive to BGC variations and only use data in these regions to calculate μ_s for minimizing the inaccuracy induced by nonhomogeneity and therefore improving the accuracy of OCT-based BGC monitoring. We demonstrate the effectiveness of the 2D method with OCT data obtained with in vivo human forearm skins of nine different human subjects. In particular, we present a 3D OCT data set in a two-dimensional (2D) map of depth vs. a lateral dimension and calculate the correlation coefficient R between the μ_s and the BGC in each region of the 2D map with the BGC data measured with a glucose meter using finger blood. We filter out the μ_s data from regions with low R values and only keep the μ_s data with R values sufficiently high (R-filter). The filtered μ_s data in all the regions are then averaged to produce an average μ_s data. We define a term called overall relevancy (OR) to quantify the degree of correlation between the filtered/averaged μ_s data and the finger-blood BGC data to determine the optimal R value for such an R-filter with the highest obtained OR. We found that the optimal R for such an R-filter has an absolute value (|R|) of 0.6 or 0.65. We further show that the R-filter obtained with the 2D correlation method yields better OR between μ_s and the BGC than that obtained with the previously reported 1D correlation method. We believe that the method demonstrated in this paper is important for understanding the influence of BGC on μ_s in human skins and therefore for improving the accuracy of OCT-based noninvasive BGC monitoring, although further studies are required to validate its effectiveness.

Parametric imaging of attenuation by optical coherence tomography: review of models, methods, and clinical translation

SIGNIFICANCE

Optical coherence tomography (OCT) provides cross-sectional and volumetric images of backscattering from biological tissue that reveal the tissue morphology. The strength of the scattering, characterized by an attenuation coefficient, represents an alternative and complementary tissue optical property, which can be characterized by parametric imaging of the OCT attenuation coefficient. Over the last 15 years, a multitude of studies have been reported seeking to advance methods to determine the OCT attenuation coefficient and developing them toward clinical applications.

AIM

Our review provides an overview of the main models and methods, their assumptions and applicability, together with a survey of preclinical and clinical demonstrations and their translation potential.

RESULTS

The use of the attenuation coefficient, particularly when presented in the form of parametric en face images, is shown to be applicable in various medical fields. Most studies show the promise of the OCT attenuation coefficient in differentiating between tissues of clinical interest but vary widely in approach.

CONCLUSIONS

As a future step, a consensus on the model and method used for the determination of the attenuation coefficient is an important precursor to large-scale studies. With our review, we hope to provide a basis for discussion toward establishing this consensus.

Optical coherence tomography as a noninvasive 3D real time imaging tool for the rapid evaluation of phenotypic variations in insect embryonic development

Noninvasive visualization of embryos at different development stages is crucial for the understanding of the basic developmental biology. It is therefore desirable to have an imaging tool capable of rapidly evaluating the effects of gene manipulation or genome editing in developing embryos for the studies of gene functions and genetic engineering. Here, we propose and demonstrate a novel use of optical coherence tomography (OCT) to noninvasively exam the embryonic development of the migratory locusts in real time with 3-dimensional (3D) view capability. In particular, we obtain the sufficiently high spatial resolution tomographic 2D and 3D images of live locust embryos throughout their development processes. We show that not only we are able to noninvasively observe all previously known forms of blastokinesis as an embryo develops, such as anatrepsis, katatrepsis, revolution, rotation and diapauses, and determine their precise occurring time or duration, but also discover an unreported rotation form we named "twist." In addition, with the OCT images we determined the exact occurring time of diapauses of the locusts from Tibetan plateau for the first time. Finally, we demonstrate that OCT systems can be used to rapidly capture the development defects of genetically modified embryos in which certain genes essential for embryonic development were suppressed by RNA interference. Our work shows that OCT is an enabling imaging tool with sufficient spatial resolution for the rapid evaluation of embryonic variations of small animals.

Edge detector-based automatic segmentation of the skin layers and application to moisturization in high-resolution 3 Tesla magnetic resonance imaging

INTRODUCTION

Previous studies have demonstrated the feasibility to explore moisturization with quantification imaging based on T2 mapping. The aim of this study was to describe and validate the first robust automated method to segment the first layers of the skin.

MATERIALS AND METHODS

Data were picked from a previous study that included 35 healthy subjects who underwent a 3T MRI (multi spin echo calculation T2-weighted sequence) with a microscopic coil on the left heel before and one hour after moisturization. The automatic algorithm was composed of the T2 map generation, a Canny filter, a selection of boundaries, and a local regression to delimitate stratum corneum, epidermis, and dermis. An automated affine registration was applied between the exams before and after moisturization.

RESULTS

The failure rate of the algorithm was below 5%. Mean computation time was 139.12s. There was a significant and strong correlation between the automatic measurements and the manual ones for the T2 values (ρ: 0.905, P < 0.001) and for the thickness measurements (ρ: 0.8663; P < 0.001). For registration, mean of the Dice index was 0.64 [0.47; 0.80] and of the Hausdorff distance was 0.29 mm 95% CI: [0.28; 0.30].

CONCLUSION

The proposed automatic method to study the first skin layers in 3T MRI using micro-coils was robust and described T2 values and thickness measurements with a strong correlation to manual measurements. The use of an automated affine registration could also permit the generation of a mapping for a visual assessment of moisturization.

Three-dimensional graph-based skin layer segmentation in optical coherence tomography images for roughness estimation

Automatic skin layer segmentation in optical coherence tomography (OCT) images is important for a topographic assessment of skin or skin disease detection. However, existing methods cannot deal with the problem of shadowing in OCT images due to the presence of hair, scales, etc. In this work, we propose a method to segment the topmost layer of the skin (or the skin surface) using 3D graphs with a novel cost function to deal with shadowing in OCT images. 3D graph cuts use context information across B-scans when segmenting the skin surface, which improves the segmentation as compared to segmenting each B-scan separately. The proposed method reduces the segmentation error by more than 20% as compared to the best performing related work. The method has been applied to roughness estimation and shows a high correlation with a manual assessment. Promising results demonstrate the usefulness of the proposed method for skin layer segmentation and roughness estimation in both normal OCT images and OCT images with shadowing.

Optical coherence tomography angiography of normal skin and inflammatory dermatologic conditions

BACKGROUND

In clinical dermatology, the identification of subsurface vascular and structural features known to be associated with numerous cutaneous pathologies remains challenging without the use of invasive diagnostic tools.

OBJECTIVE

To present an advanced optical coherence tomography angiography (OCTA) method to directly visualize capillary-level vascular and structural features within skin in vivo.

METHODS

An advanced OCTA system with a 1310 nm wavelength was used to image the microvascular and structural features of various skin conditions. Subjects were enrolled and OCTA imaging was performed with a field of view of approximately 10 × 10 mm. Skin blood flow was identified using an optical microangiography (OMAG) algorithm. Depth-resolved microvascular networks and structural features were derived from segmented volume scans, representing tissue slabs of 0-132, 132-330, and 330-924 μm, measured from the surface of the skin.

RESULTS

Subjects with both healthy and pathological conditions, such as benign skin lesions, psoriasis, chronic graft-versus-host-disease (cGvHD), and scleroderma, were OCTA scanned. Our OCTA results detailed variations in vascularization and local anatomical characteristics, for example, depth-dependent vascular, and structural alterations in psoriatic skin, alongside their resolve over time; vascular density changes and distribution irregularities, together with corresponding structural depositions in the skin of cGvHD patients; and vascular abnormalities in the nail folds of a patient with scleroderma.

CONCLUSION

OCTA can image capillary blood flow and structural features within skin in vivo, which has the potential to provide new insights into the pathophysiology, as well as dynamic changes of skin diseases, valuable for diagnoses, and non-invasive monitoring of disease progression and treatment. Lasers Surg. Med. 50:183-193, 2018. © 2018 Wiley Periodicals, Inc.

An overview of methods to mitigate artifacts in optical coherence tomography imaging of the skin

BACKGROUND

Optical coherence tomography (OCT) of skin delivers three-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution modality, OCT images suffer from some artifacts that lead to misinterpretation of tissue structures. Therefore, an overview of methods to mitigate artifacts in OCT imaging of the skin is of paramount importance. Speckle, intensity decay, and blurring are three major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the consequence of deficiencies of optical components.

METHOD

Two speckle reduction methods (one based on artificial neural network and one based on spatial compounding), an attenuation compensation algorithm (based on Beer-Lambert law) and a deblurring procedure (using deconvolution), are described. Moreover, optical properties extraction algorithm based on extended Huygens-Fresnel (EHF) principle to obtain some additional information from OCT images are discussed.

RESULTS

In this short overview, we summarize some of the image enhancement algorithms for OCT images which address the abovementioned artifacts. The results showed a significant improvement in the visibility of the clinically relevant features in the images. The quality improvement was evaluated using several numerical assessment measures.

CONCLUSION

Clinical dermatologists benefit from using these image enhancement algorithms to improve OCT diagnosis and essentially function as a noninvasive optical biopsy.

Semi-automated localization of dermal epidermal junction in optical coherence tomography images of skin

Identifying the location of the dermal epidermal junction (DEJ) in skin images is essential in several clinical applications of dermatology such as epidermal thickness determination in healthy versus unhealthy skins, such as basal cell carcinoma. Optical coherence tomography (OCT) facilitates the visual detection of DEJ in vivo. However, due to the granular texture of speckle and a low contrast between dermis and epidermis, a skin border detection method is required for DEJ localization. Current DEJ algorithms work well for skins with a visible differentiable epidermal layer but not for the skins of different body sites. In this paper, we present a semi-automated DEJ localization algorithm based on graph theory for OCT images of skin. The proposed algorithm is performed in an interactive framework by a graphical representation of an attenuation coefficient map through a uniform-cost search method. For border thinning, a fuzzy-based nonlinear smoothing technique is used. For evaluation, the DEJ detection method is used by several experts, and the results are compared with manual segmentation. The mean thickness error between the proposed algorithm and the experts' opinion in the Bland-Altman plot is computed as 14 μm; this is comparable to the resolution of the OCT. The results suggest that the proposed image processing method successfully detects DEJ.

Automated segmentation and enhancement of optical coherence tomography-acquired images of rodent brain

BACKGROUND

Optical coherence tomography (OCT) is a non-invasive optical imaging method that has proven useful in various fields such as ophthalmology, dermatology and neuroscience. In ophthalmology, significant progress has been made in retinal layer segmentation and enhancement of OCT images. There are also segmentation algorithms to separate epidermal and dermal layers in OCT-acquired images of human skin.

NEW METHOD

We describe simple image processing methods that allow automatic segmentation and enhancement of OCT images of rodent brain.

RESULTS

We demonstrate the effectiveness of the proposed methods for OCT-based microangiography (OMAG) and tissue injury mapping (TIM) of mouse cerebral cortex. The results show significant improvement in image contrast, delineation of tissue injury, allowing visualization of different layers of capillary beds.

COMPARISON WITH EXISTING METHODS

Previously reported methods for other applications are yet to be used in neuroscience due to the complexity of tissue anatomy, unique physiology and technical challenges.

CONCLUSIONS

OCT is a promising tool that provides high resolution in vivo microvascular and structural images of rodent brain. By automatically segmenting and enhancing OCT images, structural and microvascular changes in mouse cerebral cortex after stroke can be monitored in vivo with high contrast.

Sensor-Based Technique for Manually Scanned Hand-Held Optical Coherence Tomography Imaging

Hand-held optical coherence tomography (OCT) imaging probes offer flexibility to image sites that are otherwise challenging to access. While the majority of hand-held imaging probes utilize galvanometer- or MEMS-scanning mirrors to transversely scan the imaging beam, these probes are commonly limited to lateral fields-of-view (FOV) of only a few millimeters. The use of a freehand manually scanned probe can significantly increase the lateral FOV. However, using the traditional fixed-rate triggering scheme for data acquisition in a manually scanned probe results in imaging artifacts due to variations in the scan velocity of the imaging probe. These artifacts result in a structurally inaccurate image of the sample. In this paper, we present a sensor-based manual scanning technique for OCT imaging, where real-time feedback from an optical motion sensor is used to trigger data acquisition. This technique is able to circumvent the problem of motion artifacts during manual scanning by adaptively altering the trigger rate based on the instantaneous scan velocity, enabling OCT imaging over a large lateral FOV. The feasibility of the proposed technique is demonstrated by imaging several biological and nonbiological samples.

High-resolution extended source optical coherence tomography

High resolution optical coherence tomography (OCT) is capable of providing detailed tissue microstructures that are critical for disease diagnosis, yet its sensitivity is usually degraded since the system key components are typically not working at their respective center wavelengths. We developed a novel imaging system that achieves enhanced sensitivity without axial resolution degradation by the use of a spectrally encoded extended source (SEES) technique; it allows larger sample power without exceeding the maximum permissible exposure (MPE). In this study, we demonstrate a high-resolution extended source (HRES) OCT system, which is capable of providing a transverse resolution of 4.4 µm and an axial resolution of 2.1 µm in air with the SEES technique. We first theoretically show a sensitivity advantage of 6-dB of the HRES-OCT over that of its point source counterpart using numerical simulations, and then experimentally validate the applicability of the SEES technique to high-resolution OCT (HR-OCT) by comparing the HRES-OCT with an equivalent point-source system. In the HRES-OCT system, a dispersive prism was placed in the infinity space of the sample arm optics to spectrally extend the visual angle (angular subtense) of the light source to 10.3 mrad. This extended source allowed ~4 times larger MPE than its point source counterpart, which results in an enhancement of ~6 dB in sensitivity. Specifically, to solve the unbalanced dispersion between the sample and the reference arm optics, we proposed easy and efficient methods for system calibration and dispersion correction, respectively. With a maximum scanning speed reaching up to 60K A-lines/s, we further conducted imaging experiments with HRES-OCT using the human fingertip in vivo and the swine eye tissues ex vivo. Results demonstrate that the HRES-OCT is able to achieve significantly larger penetration depth than its conventional point source OCT counterpart.

Measurements of the thermal coefficient of optical attenuation at different depth regions of in vivo human skins using optical coherence tomography: a pilot study

We present detailed measurement results of optical attenuation's thermal coefficients (referenced to the temperature of the skin surface) in different depth regions of in vivo human forearm skins using optical coherence tomography (OCT). We first design a temperature control module with an integrated optical probe to precisely control the surface temperature of a section of human skin. We propose a method of using the correlation map to identify regions in the skin having strong correlations with the surface temperature of the skin and find that the attenuation coefficient in these regions closely follows the variation of the surface temperature without any hysteresis. We observe a negative thermal coefficient of attenuation in the epidermis. While in dermis, the slope signs of the thermal coefficient of attenuation are different at different depth regions for a particular subject, however, the depth regions with a positive (or negative) slope are different in different subjects. We further find that the magnitude of the thermal coefficient of attenuation coefficient is greater in epidermis than in dermis. We believe the knowledge of such thermal properties of skins is important for several noninvasive diagnostic applications, such as OCT glucose monitoring, and the method demonstrated in this paper is effective in studying the optical and biological properties in different regions of skin.

Epidermal segmentation in high-definition optical coherence tomography

Epidermis segmentation is a crucial step in many dermatological applications. Recently, high-definition optical coherence tomography (HD-OCT) has been developed and applied to imaging subsurface skin tissues. In this paper, a novel epidermis segmentation method using HD-OCT is proposed in which the epidermis is segmented by 3 steps: the weighted least square-based pre-processing, the graph-based skin surface detection and the local integral projection-based dermal-epidermal junction detection respectively. Using a dataset of five 3D volumes, we found that this method correlates well with the conventional method of manually marking out the epidermis. This method can therefore serve to effectively and rapidly delineate the epidermis for study and clinical management of skin diseases.

In situ optical coherence tomography of percutaneous implant-tissue interfaces in a murine model

Novel surface coatings of percutaneous implants need to be tested in biocompatibility studies. The use of animal models for testing usually involves numerous lethal biopsies for the analysis of the implant-tissue interface. In this study, optical coherence tomography (OCT) was used to monitor the reaction of the skin to a percutaneous implant in an animal model of hairless but immunocompetent mice. In vivo optical biopsies with OCT were taken at days 7 and 21 after implantation and post mortem on the day of noticeable inflammation. A Fourier-domain OCT was programmed for spoke pattern scanning schemes centered at the implant midpoint to reduce motion artifacts during in vivo imaging. Image segmentation allowed the automatic detection and morphometric analysis of the skin contour and the subcutaneous implant anchor. On the basis of the segmentation, the overall refractive index of the tissue within one OCT data set was estimated as a free parameter of a fitting algorithm, which corrects for the curved distortion of the planar implant base in the OCT images. OCT in combination with the spoke scanning scheme and image processing provided time-resolved three-dimensional optical biopsies around the implants to assess tissue morphology.

OCT skin image enhancement through attenuation compensation

The enhancement of optical coherence tomography (OCT) skin images can help dermatologists investigate the morphologic information of the images more effectively. In this paper, we propose an enhancement algorithm with the stages that includes speckle reduction, skin layer detection, and attenuation compensation. A weighted median filter is designed to reduce the level of speckle while preserving the contrast. A novel skin layer detection technique is then applied to outline the main skin layers: stratum corneum, epidermis, and dermis. The skin layer detection algorithm does not make any assumption about the structure of the skin. A model of the light attenuation is then used to estimate the attenuation coefficient of the stratum corneum, epidermis, and dermis layers. The performance of the algorithm has been evaluated qualitatively based on visual evaluation and quantitatively using two no-reference quality metrics: signal-to-noise ratio and contrast-to-noise ratio. The enhancement algorithm is tested on 35 different skin OCT images, which show significant improvements in the quality of the images, especially in the structures at deeper levels.

Diabetes imaging-quantitative assessment of islets of Langerhans distribution in murine pancreas using extended-focus optical coherence microscopy

Diabetes is characterized by hyperglycemia that can result from the loss of pancreatic insulin secreting β-cells in the islets of Langerhans. We analyzed ex vivo the entire gastric and duodenal lobes of a murine pancreas using extended-focus Optical Coherence Microscopy (xfOCM). To identify and quantify the islets of Langerhans observed in xfOCM tomograms we implemented an active contour algorithm based on the level set method. We show that xfOCM reveals a three-dimensional islet distribution consistent with Optical Projection Tomography, albeit with a higher resolution that also enables the detection of the smallest islets (≤ 8000 μm(3)). Although this category of the smallest islets represents only a negligible volume compared to the total β-cell volume, a recent study suggests that these islets, located at the periphery, are the first to be destroyed when type I diabetes develops. Our results underline the capability of xfOCM to contribute to the understanding of the development of diabetes, especially when considering islet volume distribution instead of the total β-cell volume only.

Defect detection and property evaluation of indium tin oxide conducting glass using optical coherence tomography

This study demonstrates a new approach for evaluating the properties of indium tin oxide (ITO) conducting glass and identifying defects using optical coherence tomography (OCT). A swept-source OCT system was implemented to scan the ITO conducting glass to enable two-dimensional or three-dimensional imaging. With OCT scanning, the defects can be clearly identified at various depths. Several parameters in addition to morphological information can be estimated simultaneously, including the thickness of the glass substrate, the refractive index, reflection coefficient, and transmission coefficient, all of which can be used to evaluate the quality of ITO conducting glass. This study developed a modified method for evaluating the refractive index of glass substrates without having to perform multiple scans as well as a segmentation algorithm to separate the interfaces. The results show the potential of OCT as an imaging tool for the inspection of defects in ITO conducting glass.

Model based 3D segmentation and OCT image undistortion of percutaneous implants

Optical Coherence Tomography (OCT) is a noninvasive imaging technique which is used here for in vivo biocompatibility studies of percutaneous implants. A prerequisite for a morphometric analysis of the OCT images is the correction of optical distortions caused by the index of refraction in the tissue. We propose a fully automatic approach for 3D segmentation of percutaneous implants using Markov random fields. Refraction correction is done by using the subcutaneous implant base as a prior for model based estimation of the refractive index using a generalized Hough transform. Experiments show the competitiveness of our algorithm towards manual segmentations done by experts.

Scattering attenuation microscopy of oral epithelial dysplasia

We present a new method for quantitative visualization of premalignant oral epithelium called scattering attenuation microscopy (SAM). Using low-coherence interferometry, SAM projects measurements of epithelial optical attenuation onto an image of the tissue surface as a color map. The measured attenuation is dominated by optical scattering that provides a metric of the severity of oral epithelial dysplasia (OED). Scattering is sensitive to the changes in size and distribution of nuclear material that are characteristic of OED, a condition recognized by the occurrence of basal-cell-like features throughout the epithelial depth. SAM measures the axial intensity change of light backscattered from epithelial tissue. Scattering measurements are obtained from sequential axial scans of a 3-D tissue volume and displayed as a 2-D SAM image. A novel segmentation method is used to confine scattering measurement to epithelial tissue. This is applied to oral biopsy samples obtained from 19 patients. Our results show that imaging of tissue scattering can be used to discriminate between different dysplastic severities and furthermore presents a powerful tool for identifying the most representative tissue site for biopsy.

In-vivo dynamic characterization of microneedle skin penetration using optical coherence tomography

The use of microneedles as a method of circumventing the barrier properties of the stratum corneum is receiving much attention. Although skin disruption technologies and subsequent transdermal diffusion rates are being extensively studied, no accurate data on depth and closure kinetics of microneedle-induced skin pores are available, primarily due to the cumbersome techniques currently required for skin analysis. We report on the first use of optical coherence tomography technology to image microneedle penetration in real time and in vivo. We show that optical coherence tomography (OCT) can be used to painlessly measure stratum corneum and epidermis thickness, as well as microneedle penetration depth after microneedle insertion. Since OCT is a real-time, in-vivo, nondestructive technique, we also analyze skin healing characteristics and present quantitative data on micropore closure rate. Two locations (the volar forearm and dorsal aspect of the fingertip) have been assessed as suitable candidates for microneedle administration. The results illustrate the applicability of OCT analysis as a tool for microneedle-related skin characterization.

Automated segmentation of tissue structures in optical coherence tomography data

Segmentation of optical coherence tomography (OCT) images provides useful information, especially in medical imaging applications. Because OCT images are subject to speckle noise, the identification of structures is complicated. Addressing this issue, two methods for the automated segmentation of arbitrary structures in OCT images are proposed. The methods perform a seeded region growing, applying a model-based analysis of OCT A-scans for the seed's acquisition. The segmentation therefore avoids any user-intervention dependency. The first region-growing algorithm uses an adaptive neighborhood homogeneity criterion based on a model of an OCT intensity course in tissue and a model of speckle noise corruption. It can be applied to an unfiltered OCT image. The second performs region growing on a filtered OCT image applying the local median as a measure for homogeneity in the region. Performance is compared through the quantitative evaluation of artificial data, showing the capabilities of both in terms of structures detected and leakage. The proposed methods were tested on real OCT data in different scenarios and showed promising results for their application in OCT imaging.

Investigation of post-glaucoma-surgery structures by three-dimensional and polarization sensitive anterior eye segment optical coherence tomography

A sequential case series of post-glaucoma-surgery structures examined by three-dimensional corneal and anterior eye segment optical coherence tomography (3D-CASOCT) and 3D polarization sensitive CASOCT (PS-CASOCT) is presented. A total of 5 patients who underwent glaucoma surgery were included in this study. Of these, 1, 1, and 3 patient underwent trabeculotomy, laser iridotomy, and trabeculectomy respectively. One patient each who had undergone trabeculotomy or laser iridotomy was examined using a prototype 3D-CASOCT. This prototype is based on swept-source OCT technology, uses a probe beam with a center wavelength of 1.31 microm, and has an axial resolution of 11.6 microm and a scanning speed of 20,000 A lines/s. All 3 patients who underwent trabeculectomy were examined by PS-CASOCT, which has similar specifications to those of 3DCASOCT, measures the depth-resolved birefringence of a specimen, and yields conventional OCT images. Detailed 3D visualization of the incision site of trabeculotomy and the ablation site of laser iridotomy was achieved using 3D-CASOCT. PS-CASOCT revealed, in addition to the structural details, the birefringent properties of the tissues of the trabeculectomy bleb. Some blebs showed abnormal birefringence in the conjunctiva and in a remnant fluid pool. This may indicate the existence of fibrosis in these regions. Both 3D-CASOCT and PS-CASOCT provide clinically significant information for the postoperative assessment of structures created during glaucoma surgery. Interactive 3D datasets of all cases are provided for interactive clinical review. Complex raw 3D OCT volumes are also provided as a reference dataset for the development of PS-OCT algorithms.

Towards automated classification of clinical optical coherence tomography data of dense tissues

The native contrast of optical coherence tomography (OCT) data in dense tissues can pose a challenge for clinical decision making. Automated data evaluation is one way of enhancing the clinical utility of measurements. Methods for extracting information from structural OCT data are appraised here. A-scan analysis allows characterization of layer thickness and scattering parameters, whereas image analysis renders itself to segmentation, texture and speckle analysis. All fully automated approaches combine pre-processing, feature registration, data reduction, and classification. Pre-processing requires de-noising, feature recognition, normalization and refining. In the current literature, image exclusion criteria, initial parameters, or manual input are common requirements. The interest of the presented methods lies in the prospect of objective, quick, and/or post-acquisition processing. There is a potential to improve clinical decision making based on automated processing of OCT data.

Optical coherence tomography: a potential tool for unsupervised prediction of treatment response for Port-Wine Stains

BACKGROUND

Treatment of Port-Wine Stains (PWS) suffers from the absence of a reliable real-time tool for monitoring a clinical endpoint. Response to treatment varies substantially according to blood vessel geometry. Even though optical coherence tomography (OCT) has been identified as a modality with potential to suit this need, it has not been introduced as a standard clinical monitoring tool. One reason could be that - although OCT acquires data in real-time - gigabyte data transfer, processing and communication to a clinician may impede the implementation as a clinical tool.

OBJECTIVES

We investigate whether an automated algorithm can address this problem.

METHODS

Based on our understanding of pulsed dye laser treatment, we present the implementation of an unsupervised, real-time classification algorithm which uses principal components data reduction and linear discriminant analysis. We evaluate the algorithm using 96 synthesized test images and 7 clinical images.

RESULTS

The synthesized images are classified correctly in 99.8%. The clinical images are classified correctly in 71.4%.

CONCLUSIONS

Principal components-fed linear discriminant analysis (PC-fed LDA) may be a valuable method to classify clinical images. Larger sampling numbers are required for a better training model. These results justify undertaking a study involving more patients and show that disease can be described as a function of available treatment options.

Effective indicators for diagnosis of oral cancer using optical coherence tomography

A swept-source optical coherence tomography system is used to clinically scan oral precancer and cancer patients for statistically analyzing the effective indicators of diagnosis. Three indicators are considered, including the standard deviation (SD) of an A-mode scan signal profile, the exponential decay constant (alpha) of an A-mode-scan spatial-frequency spectrum, and the epithelium thickness (T) when the boundary between epithelium and lamina propria can still be identified. Generally, in abnormal mucosa, the standard deviation becomes larger, the decay constant of the spatial-frequency spectrum becomes smaller, and epithelium becomes thicker. The sensitivity and specificity of the three indicators are discussed based on universal and individual relative criteria. It is found that SD and alpha are good diagnosis indicators for moderate dysplasia and squamous cell carcinoma. On the other hand, T is a good diagnosis indicator for epithelia hyperplasia and moderate dysplasia.

Assessment of dermal wound repair after collagen implantation with optical coherence tomography

We present an animal study to examine the utility and potential limitations of optical coherence tomography (OCT) for noninvasive evaluation of biomaterial scaffold-assisted wound healing. The transverse and axial resolutions of the OCT system at the wavelength of 1.3 microm were 12 and 10 microm, respectively. A murine full-thickness transcutaneous wound model was employed, in which a phi 10 mm full-thickness wound was created on the back of each male Balb/cJ mouse and a porous collagen scaffold was implanted in the wound bed followed by coverage with a Tegaderm film. Sequential cross-sectional OCT scans were performed at different time points postsurgical intervention to track morphological changes during wound recovery, and the captured OCT images were validated by their corresponding histological specimens. The results indicated that with removal of the high-scattering skin, OCT was capable of imaging to a depth of over 1.5 mm into the wound bed and differentiating various features evolved during wound healing at a high resolution approaching histopathology. OCT was able to not only delineate the epidermis and dermis of normal mouse skin, but also differentiate collagen implant from the underlying subcutaneous tissue; besides, it could track the wound size changes in both lateral and vertical directions. More importantly, OCT was able to detect inflammation, early re-epithelialization, and resorption of the collagen scaffold. These findings suggested the potential of OCT for noninvasive and high-resolution monitoring of assisted wound healing in vivo, longitudinally, and instantaneously.

Near real-time classification of optical coherence tomography data using principal components fed linear discriminant analysis

An optical coherence tomography (OCT) prediction algorithm is designed and tested on a data set of sample images (taken from vegetables and porcine tissues) to demonstrate proof of concept. Preprocessing and classification of data are fully automated, at a rate of 60,000 A-scansmin on a standard computer and can be considered to deliver in near real-time. A data set consisting of nine groups was classified correctly in 82% of cases after cross-validation. Sets of fewer groups reach higher rates. The algorithm is able to distinguish groups with strong visual similarity among several groups of varying resemblance. Surface recognition and normalizing to the surface are essential for this approach. The mean divided by the standard deviation is a suitable descriptor for reducing a set of surface normalized A-scans. The method enables grouping of separate A-scans and is therefore straightforward to apply on 3-D data. OCT data can reliably be classified using principal component analysis combined with linear discriminant analysis. It remains to be shown whether this algorithm fails in the clinical setting, where interpatient variation can be greater than the deviations that are investigated as a disease marker.

Three-dimensional visualization of choroidal vessels by using standard and ultra-high resolution scattering optical coherence angiography

Scattering optical coherence angiography (S-OCA) is a noninvasive imaging method that is based on the high-speed standard 800nm band spectral-domain optical coherence tomography (SD-OCT) and the ultra-high-resolution SD-OCT which has the axial resolution of 6.1 mum and 2.9 mum in tissue, respectively. In this paper, we have demonstrated the use of this method for in vivo human retinal imaging. A three-dimensional view of the choroidal vasculature was obtained by segmenting the choroidal vessels; this was done using intensity threshold based binarization at each depth plane relative to the retinal pigment epithelium. A vascular projection image was obtained by integrating the segmented choroidal vasculature. In order to assess the feasibility of the proposed method, we compared these images with those obtained using existing invasive methods such as fluorescein angiography and indocyanine green angiography. Clinically worthful images are obtained from the application of S-OCA to the agerelated macular degeneration and polypoidal choroidal vasculopathy.

In vivo high-contrast imaging of deep posterior eye by 1-microm swept source optical coherence tomography and scattering optical coherence angiography

Retinal, choroidal and scleral imaging by using swept-source optical coherence tomography (SS-OCT) with a 1-microm band probe light, and high-contrast and three-dimensional (3D) imaging of the choroidal vasculature are presented. This SS-OCT has a measurement speed of 28,000 A-lines/s, a depth resolution of 10.4 microm in tissue, and a sensitivity of 99.3 dB. Owing to the high penetration of the 1-microm probe light and the high sensitivity of the system, the in vivo sclera of a healthy volunteer can be observed. A software-based algorithm of scattering optical coherence angiography (S-OCA) is developed for the high-contrast and 3D imaging of the choroidal vessels. The S-OCA is used to visualize the 3D choroidal vasculature of the in vivo human macula and the optic nerve head. Comparisons of S-OCA with several other angiography techniques including Doppler OCA, Doppler OCT, fluorescein angiography, and indocyanine green angiography are also presented.

Validation of optical coherence tomographyin vivousing cryostat histology

We aimed to validate for the first time optical coherence tomography (OCT) measurements of epidermal thickness (ET) using cryopreparation for histology. OCT assessments of ET were performed on healthy skin using the algorithms as follows: first, peak-to-valley analysis of the A-scan (ET-OCT-V), second, line-traced image analysis of the B-scan (ET-OCT-IA). Histology was performed using cryostat sections which were also evaluated using the image analysis (ET-Histo). We selected 114 samples, including B-scans and corresponding histology, for method comparison between ET-OCT-IA and ET-Histo. Forty-two A-scans were available for method comparison between ET-OCT-V and ET-Histo. Bland and Altman plots revealed a marked bias with wide 95% limits of agreement for ET-OCT-V versus ET-Histo. Comparison of ET-OCT-IA versus ET-Histo revealed only a slight bias and narrow 95% limits of agreement. A-scan analysis for ET determination is linked to significant limitations and lacks agreement with histology. By contrast, we observed satisfactory agreement between ET-OCT-IA and ET-Histo indicating that both methods can be utilized interchangeably. OCT using the line-traced image analysis of the B-scan appears to be a valid and relatively practicable method for the determination of ET in vivo. Furthermore, the comparisons with the in vivo OCT profiles demonstrate that cryostat sectioning provides a better preservation of relative and absolute dimensions of skin layers than paraffin embedding.

Noninvasive assessment of cutaneous wound healing using ultrahigh-resolution optical coherence tomography

Ultrahigh-resolution optical coherence tomography (OCT) was used for noninvasive in vivo evaluation of the wound healing process. Cutaneous wounds were induced by 2.5-mm diameter full-thickness punch biopsies on the dorsal surface of seven mice. OCT imaging was performed to assess the structural characteristics associated with the healing process. The OCT results were compared to corresponding histology. Two automated quantitative analysis routines were implemented to identify the dermal-epidermal junction and segment the OCT images. Hallmarks of cutaneous wound healing such as wound size, epidermal migration, dermal-epidermal junction formation, and differences in wound composition were readily identified on the OCT images. Blister formation was also observed. Preliminary findings suggest OCT is a viable tool to noninvasively monitor wound healing in vivo.

In vivo data of epidermal thickness evaluated by optical coherence tomography: effects of age, gender, skin type, and anatomic site

BACKGROUND

The knowledge of epidermal thickness (ET) is of great significance in many areas of medical and biological research.

OBJECTIVES

We aimed to assess optical coherence tomography (OCT) in terms of precision, and to investigate the influence of several constitutional factors, such as age, gender, skin type, and anatomic site, on the mean ET using OCT in vivo.

METHODS

Eighty-three subjects were studied using OCT in vivo. Intra- and inter-day repeatability measurements were performed. The mean ET was assessed in six different body sites of young (20-40 years old) and old (60-80 years old) Caucasians, respectively. An ethnic group was included into the study.

RESULTS

OCT proved to be a precise technique in terms of repeatability and reproducibility as expressed in low coefficients of variation. Comparison of young and old Caucasians demonstrated a significant decrease of ET with age in all anatomic sites investigated. ET assessed in males and females did not significantly differ, except for forehead skin which is significantly thinner in old females than in males. ET observed in Caucasians did not significantly differ from ET measured in ethnic individuals. Anatomic sites insignificantly influenced ET on an inter-individual level. However, differences of ET between body sites on an intra-individual level are significant.

CONCLUSIONS

This was the first systematic in vivo study on ET investigating several influencing parameters of the epidermal dimension in a reasonable study sample by means of OCT. The results presented here may serve as ET reference data in a variety of clinical and experimental matters.