Quantitative measurement of attenuation coefficients of weakly scattering media using optical coherence tomography

Determination of confocal parameters of OCT imaging for eliminating confocal effect on attenuation coefficient estimation

Optical coherence tomography (OCT) provides three-dimensional images of biological tissues based on low-coherence optical interference. Attenuation coefficient estimation is one of the important functional extensions of OCT and has received many research efforts as attenuation coefficient has been found to be associated with histopathological transformation of human tissues. However, attenuation coefficient estimation accuracy is deteriorated by the confocal effect on OCT A-scan. Thus, it is desired to eliminate the confocal effect, which requires accurate determination of the confocal parameters. In this study, we propose what we believe to be a novel method for confocal parameter extraction, called dual NA ratio fitting (DNRF). DNRF requires a repetition of B-scan with varied numerical apertures (NA), altering the Rayleigh length of B-scan but keeping the focal depth fixed. Then, the focal depth and Rayleigh length can be determined by fitting an A-scan ratio function from the two repeated B-scans. The NA tuning was achieved by adding a beam expansion module into the sample arm. The method was evaluated on intralipid samples and multi-layer phantoms. The results demonstrate that our method is capable of determine the confocal parameters with good accuracy. With the extracted confocal parameters, the confocal effect was removed effectively, upon which attenuation coefficient estimation using traditional depth-resolved method appeared to be more accurate than the confocal parameter extraction based on the A-scan ratio function of two repeated B-scans with varied focal depths. Last, our method was tested on human skin in vivo, yielding attenuation coefficients consistent with literature. This indicates good potential of our method to be used for clinical applications.

Basis function model to extract the combined confocal and fall-off function from multiple optical coherence tomography A-scans

Significance

Many derivatives of optical coherence tomography (OCT) rely on the depth-dependent information of the sample in the image. System depth-dependent effects, such as the confocal effect and the sensitivity fall-off, should be corrected to improve the accuracy of the images and information derived from them.

Aim

We developed a new single-shot method to extract the combined confocal and fall-off functions and remove system-generated depth-dependent effects from OCT images.

Approach

The combined function is modeled as a linear combination of basis functions whose coefficients are found from two or more A-scans (or B-scans) of a sample that are vertically shifted within the imaging range. No prior knowledge of the OCT system parameters or assumed form for the confocal and fall-off functions is needed.

Results

The method was derived and validated with simulations and OCT images of a phantom, a biological sample, and human retina. Improvement over the Ratio Fit method was demonstrated.

Conclusions

The improvement in the extraction of the combined confocal and fall-off effects by this method should lead to improved medical diagnosis through more accurate attenuation coefficient calculations. The method enables future applications of OCT where precise removal of all depth-dependent effects on OCT images is critical.

Research progress on the use of the optical coherence tomography system for the diagnosis and treatment of central nervous system tumors

In central nervous system (CNS) surgery, the accurate identification of tumor boundaries, achieving complete resection of the tumor, and safeguarding healthy brain tissue remain paramount challenges. Despite the expertise of neurosurgeons, the infiltrative nature of the tumors into the surrounding brain tissue often hampers intraoperative differentiation between tumorous and non-tumorous tissue, thus hindering total tumor removal. Optical coherence tomography (OCT), with its unique advantages of high-resolution imaging, efficient image acquisition, real-time intraoperative detection, and radiation-free and noninvasive properties, offers accurate diagnostic capabilities and invaluable intraoperative guidance for minimally invasive CNS tumor diagnosis and treatment. Various OCT systems have been employed in neurological tumor research, including polarization-sensitive OCT systems, orthogonal polarization OCT systems, Doppler OCT systems, and OCT angiography systems. In addition, OCT-based diagnostic and therapeutic techniques have been explored for the surgical resection of CNS tumors. This review aims to compile and evaluate the research progress surrounding the principles of OCT systems and their applications in CNS tumors, providing insights into potential future research avenues and clinical applications.

Deep learning classification of ex vivo human colon tissues using spectroscopic optical coherence tomography

Screening for colorectal cancer (CRC) with colonoscopy has improved patient outcomes; however, it remains the third leading cause of cancer-related mortality, novel strategies to improve screening are needed. Here, we propose an optical biopsy technique based on spectroscopic optical coherence tomography (OCT). Depth resolved OCT images are analyzed as a function of wavelength to measure optical tissue properties and used as input to machine learning algorithms. Previously, we used this approach to analyze mouse colon polyps. Here, we extend the approach to examine human biopsied colonic epithelial tissue samples ex vivo. Optical properties are used as input to a novel deep learning architecture, producing accuracy of up to 97.9% in discriminating tissue type. SOCT parameters are used to create false colored en face OCT images and deep learning classifications are used to enable visual classification by tissue type. This study advances SOCT toward clinical utility for analysis of colonic epithelium.

Automatic renal carcinoma biopsy guidance using forward-viewing endoscopic optical coherence tomography and deep learning

Percutaneous renal biopsy is commonly used for kidney cancer diagnosis. However, the biopsy procedure remains challenging in sampling accuracy. Here we introduce a forward-viewing optical coherence tomography probe for differentiating tumor and normal tissues, aiming at precise biopsy guidance. Totally, ten human kidney samples, nine of which had malignant renal carcinoma and one had benign oncocytoma, were used for system evaluation. Based on their distinct imaging features, carcinoma could be efficiently distinguished from normal renal tissues. Additionally, oncocytoma could be differentiated from carcinoma. We developed convolutional neural networks for tissue recognition. Compared to the conventional attenuation coefficient method, convolutional neural network models provided more accurate carcinoma predictions. These models reached a tissue recognition accuracy of 99.1% on a hold-out set of four kidney samples. Furthermore, they could efficiently distinguish oncocytoma from carcinoma. In conclusion, our convolutional neural network-aided endoscopic imaging platform could enhance carcinoma diagnosis during percutaneous renal biopsy procedures.

Adaptive contour-tracking to aid wide-field swept-source optical coherence tomography imaging of large objects with uneven surface topology

High-speed and wide-field optical coherence tomography (OCT) imaging is increasingly essential for clinical applications yet faces challenges due to its inherent sensitivity roll-off and limited depth of focus, particularly when imaging samples with significant variations in surface contour. Here, we propose one innovative solution of adaptive contour tracking and scanning methods to address these challenges. The strategy integrates an electrically tunable lens and adjustable optical delay line control with real-time surface contour information, enabling dynamic optimization of imaging protocols. It rapidly pre-scans the sample surface to acquire a comprehensive contour map. Using this map, it generates a tailored scanning protocol by partitioning the entire system ranging distance into depth-resolved segments determined by the optical Raleigh length of the objective lens, ensuring optimal imaging at each segment. Employing short-range imaging mode along the sample contour minimizes data storage and post-processing requirements, while adaptive adjustment of focal length and reference optical delay line maintains high imaging quality throughout. Experimental demonstrations show the effectiveness of the adaptive contour tracking OCT in maintaining high contrast and signal-to-noise ratio across the entire field of view, even in samples with significantly uneven surface curvatures. Notably, this approach achieves these results with reduced data volume compared to traditional OCT methods. This advancement holds promise for enhancing OCT imaging in clinical settings, particularly in applications requiring rapid, wide-field imaging of tissue structures and blood flow.

Towards non-invasive tissue hydration measurements with optical coherence tomography

The attenuation coefficient ( μ OCT ) measured by optical coherence tomography (OCT) has been used to determine tissue hydration. Previous dual-wavelength OCT systems could not attain the needed precision, which we attribute to the absence of wavelength-dependent scattering of tissue in the underlying model. Assuming that scattering can be described using two parameters, we propose a triple/quadrupole-OCT system to achieve clinically relevant precision in water volume fraction. In this study, we conduct a quantitative analysis to determine the necessary precision of μ OCT measurements and compare it with numerical simulation. Our findings emphasize that achieving a clinically relevant assessment of a 2% water fraction requires determining the attenuation coefficient with a remarkable precision of 0.01 m m - 1 . This precision threshold is influenced by the chosen wavelength for attenuation measurement and can be enhanced through the inclusion of a fourth wavelength range.

Diagnosis of dental caries based on attenuation coefficients analysis of optical coherence tomography images

Quantitative analysis of optical attenuation based on optical coherence tomography images will offer an effective method to enhance diagnostic capabilities. In this paper, the optical attenuation in demineralized caries specimens was calculated to distinguish between normal teeth and carious teeth and further to differentiate the severity of caries, and thus come to the half-automated diagnosis of dental caries. Results show that the attenuation coefficient in carious regions is approximately 4.97 mm - 1 ± 0.206 , while that of normal teeth is about 3.69 mm - 1 ± 0.231 . Attenuation coefficient of carious regions is 35% higher than that of normal teeth. Moreover, five classes of caries were qualified and classified based on the optical attenuation coefficient. Compared with the healthy teeth, there is a noticeable disparity in the attenuation coefficients of carious teeth, both on the surface and at the dentinoenamel junction. This study provides a method for accurate caries diagnosis, particularly in detection of early lesions and subtle structural changes.

Tissue characterization using axicon probe-assisted common-path optical coherence tomography

In this work, a common-path optical coherence tomography (OCT) system is demonstrated for characterizing the tissue in terms of some optical properties. A negative axicon structure chemically etched inside the fiber tip is employed as optical probe in the OCT. This probe generates a quality Bessel beam owning a large depth-of-field, ∼700 µm and small central spot size, ∼3 µm. The OCT system is probing the sample without using any microscopic lens. For experimental validation, the OCT imaging of chicken tissue has been obtained along with estimation of its refractive index and optical attenuation coefficient. Afterwards, the cancerous tissue is differentiated from the normal tissue based on the OCT imaging, refractive index, and optical attenuation coefficient. The respective tissue samples are collected from the human liver and pancreas. This probe could be a useful tool for endoscopic or minimal-invasive inspection of malignancy inside the tissue either at early-stage or during surgery.

Optical clearing of human skin: Molecular modeling and in vivo OCT study

The results of in vivo immersion optical clearing of human skin under the action of two different optical clearing agents (OCAs), such as an aqueous sucrose solution and a radiographic contrast agent Omnipaque™ 300 (iohexol), were obtained with the use of optical coherence tomography (OCT) method. The rate of reduction of light scattering coefficient, obtained through an averaged A-scan of the OCT image in the region of dermis within the depths from 350 to 700 μm, were determined to evaluate the efficiency of optical clearing (EOC). The correlations between the EOC and the energy of intermolecular interaction of OCAs with a fragment of collagen peptide have been established as a result of molecular modeling by quantum chemistry methods HF/STO3G/DFT/B3LYP/6-311G(d) of a number of OCAs (glycerol, iohexol, sucrose, ribose, fructose, glucose) with mimetic peptide of collagen (GPH)3 .

BCC and Immunocryosurgery scar differentiation through computational resolution-enhanced OCT images and skin optical attenuation: A proof-of-concept study

Monitoring medical therapy remains a challenging task across all non-surgical skin cancer treatment modalities. In addition, confirmation of residual tumours after treatment is essential for the early detection of potential relapses. Optical coherence tomography (OCT), a non-invasive method for real-time cross-sectional imaging of living tissue, is a promising imaging approach for assessing relatively flat, near-surface skin lesions, such as those that occur in most basal cell carcinomas (BCCs), at the time of diagnosis. However, the skin's inherent property of strong light scattering impedes the implementation of OCT in these cases due to the poor image quality. Furthermore, translating OCT's optical parameters into practical use in routine clinical settings is complicated due to substantial observer subjectivity. In this retrospective pilot study, we developed a workflow based on the upscale of the OCT images resolution using a deep generative adversarial network and the estimation of the skin optical attenuation coefficient. At the site of immunocryosurgery-treated BCC, the proposed methodology can extract optical parameters and discriminate objectively between tumour foci and scar tissue.

Depth-resolved method for attenuation coefficient calculation from optical coherence tomography data for improved biological structure visualization

Optical coherence tomography (OCT) is a promising tool for intraoperative tissue morphology determination. Several studies suggest that attenuation coefficient derived from the OCT images, can differentiate between tissues of different morphology, such as normal and pathological structures of the brain, skin, and other tissues. In the present study, the depth-resolved method for attenuation coefficient calculation was adopted for the real-world situation of the depth-dependent OCT sensitivity and additive imaging noise with nonzero mean. It was shown that in the case of sharp focusing (~10 μm spot full width at half maximum [FWHM] or smaller at 1.3 μm central wavelength) only the proposed method for depth-dependent sensitivity compensation does not introduce misleading artifacts into the calculated attenuation coefficient distribution. At the same time, the scanning beam focus spot with FWHM greater than 10 μm at 1.3 μm central wavelength allows one to use multiple approaches to the attenuation coefficient calculation without introducing noticeable bias. This feature may hinder the need for robust corrections for the depth-resolved attenuation coefficient estimations from the community.

Automatic renal carcinoma biopsy guidance using forward-viewing endoscopic optical coherence tomography and deep learning

Percutaneous renal biopsy (PRB) is commonly used for kidney cancer diagnosis. However, current PRB remains challenging in sampling accuracy. This study introduces a forward-viewing optical coherence tomography (OCT) probe for differentiating tumor and normal tissues, aiming at precise PRB guidance. Five human kidneys and renal carcinoma samples were used to evaluate the performance of our probe. Based on their distinct OCT imaging features, tumor and normal renal tissues can be accurately distinguished. We examined the attenuation coefficient for tissue classification and achieved 98.19% tumor recognition accuracy, but underperformed for distinguishing normal tissues. We further developed convolutional neural networks (CNN) and evaluated two CNN architectures: ResNet50 and InceptionV3, yielding 99.51% and 99.48% accuracies for tumor recognition, and over 98.90% for normal tissues recognition. In conclusion, combining OCT and CNN significantly enhanced the PRB guidance, offering a promising guidance technology for improved kidney cancer diagnosis.

Quantitative Evaluation of Caries and Calculus with Ultrahigh-Resolution Optical Coherence Tomography

Dental caries on the crown's surface is caused by the interaction of bacteria and carbohydrates, which then gradually alter the tooth's structure. In addition, calculus is the root of periodontal disease. Optical coherence tomography (OCT) has been considered to be a promising tool for identifying dental caries; however, diagnosing dental caries in the early stage still remains challenging. In this study, we proposed an ultrahigh-resolution OCT (UHR-OCT) system with axial and transverse resolutions of 2.6 and 1.8 μm for differentiating the early-stage dental caries and calculus. The same teeth were also scanned by a conventional spectral-domain OCT (SD-OCT) system with an axial resolution of 7 μm. The results indicated that early-stage carious structures such as small cavities can be observed using UHR-OCT; however, the SD-OCT system with a lower resolution had difficulty identifying it. Moreover, the estimated surface roughness and the scattering coefficient of enamel were proposed for quantitatively differentiating the different stages of caries. Furthermore, the thickness of the calculus can be estimated from the UHR-OCT results. The results have demonstrated that UHR-OCT can detect caries and calculus in their early stages, showing that the proposed method for the quantitative evaluation of caries and calculus is potentially promising.

A new method for in vivo assessment of corneal transparency using spectral-domain OCT

Corneal transparency is essential to provide a clear view into and out of the eye, yet clinical means to assess such transparency are extremely limited and usually involve a subjective grading of visible opacities by means of slit-lamp biomicroscopy. Here, we describe an automated algorithm allowing extraction of quantitative corneal transparency parameters with standard clinical spectral-domain optical coherence tomography (SD-OCT). Our algorithm employs a novel pre-processing procedure to standardize SD-OCT image analysis and to numerically correct common instrumental artifacts before extracting mean intensity stromal-depth (z) profiles over a 6-mm-wide corneal area. The z-profiles are analyzed using our previously developed objective method that derives quantitative transparency parameters directly related to the physics of light propagation in tissues. Tissular heterogeneity is quantified by the Birge ratio Br and the photon mean-free path (ls) is determined for homogeneous tissues (i.e., Br~1). SD-OCT images of 83 normal corneas (ages 22-50 years) from a standard SD-OCT device (RTVue-XR Avanti, Optovue Inc.) were processed to establish a normative dataset of transparency values. After confirming stromal homogeneity (Br <10), we measured a median ls of 570 μm (interdecile range: 270-2400 μm). By also considering corneal thicknesses, this may be translated into a median fraction of transmitted (coherent) light Tcoh(stroma) of 51% (interdecile range: 22-83%). Excluding images with central saturation artifact raised our median Tcoh(stroma) to 73% (interdecile range: 34-84%). These transparency values are slightly lower than those previously reported, which we attribute to the detection configuration of SD-OCT with a relatively small and selective acceptance angle. No statistically significant correlation between transparency and age or thickness was found. In conclusion, our algorithm provides robust and quantitative measurements of corneal transparency from standard SD-OCT images with sufficient quality (such as 'Line' and 'CrossLine' B-scan modes without central saturation artifact) and addresses the demand for such an objective means in the clinical setting.

Confocal corrected attenuation coefficient imaging in phantoms and in vivo using chromatic focal shift calibration

Optical coherence tomography (OCT) is conventionally used for structural imaging of tissue. Calibrating the intensity values of OCT images can give information on the tissue's inherent optical properties, such as the attenuation coefficient, which can provide an additional parameter to quantify possible pathological changes. To obtain calibrated intensity values, the focus position and Rayleigh length of the incident beam need to be known. We explore the feasibility of extracting the focus position from an OCT scan acquired with a single focus setting using the chromatic aberration of the system. The chromatic focal shift of an OCT system is exploited to achieve different focus positions for sub-spectrum reconstructed OCT images. The ratios of these images are used to estimate the focus position. Reconstruction of a high-resolution B-scan from coherent addition of sub-spectrum confocal function corrected B-scans and subsequent high-resolution OCT attenuation coefficient imaging is demonstrated. Furthermore, we introduce a method to experimentally determine the chromatic focal shifts of an OCT system in phantoms and an in vivo human retina. These shifts are compared to the theoretically expected shifts calculated with ray tracing.

Deep learning classification of ex vivo human colon tissues using spectroscopic OCT

Screening programs for colorectal cancer (CRC) have had a profound impact on the morbidity and mortality of this disease by detecting and removing early cancers and precancerous adenomas with colonoscopy. However, CRC continues to be the third leading cause of cancer-related mortality in both men and woman, partly because of limitations in colonoscopy-based screening. Thus, novel strategies to improve the efficiency and effectiveness of screening colonoscopy are urgently needed. Here, we propose to address this need using an optical biopsy technique based on spectroscopic optical coherence tomography (OCT). The depth resolved images obtained with OCT are analyzed as a function of wavelength to measure optical tissue properties. The optical properties can be used as input to machine learning algorithms as a means to classify adenomatous tissue in the colon. In this study, biopsied tissue samples from the colonic epithelium are analyzed ex vivo using spectroscopic OCT and tissue classifications are generated using a novel deep learning architecture, informed by machine learning methods including LSTM and KNN. The overall classification accuracy obtained was 88.9%, 76.0% and 97.9% in discriminating tissue type for these methods. Further, we apply an approach using false coloring of en face OCT images based on SOCT parameters and deep learning predictions to enable visual identification of tissue type. This study advances the spectroscopic OCT towards clinical utility for analyzing colonic epithelium for signs of adenoma.

Depth-dependent attenuation and backscattering characterization of optical coherence tomography by stationary iterative method

Significance

Extracting optical properties of tissue [e.g., the attenuation coefficient (μ ) and the backscattering fraction] from the optical coherence tomography (OCT) images is a valuable tool for parametric imaging and related diagnostic applications. Previous attenuation estimation models depend on the assumption of the uniformity of the backscattering fraction (R ) within layers or whole samples, which does not accurately represent real-world conditions.

Aim

Our aim is to develop a robust and accurate model that calculates depth-wise values of attenuation and backscattering fractions simultaneously from OCT signals. Furthermore, we aim to develop an attenuation compensation model for OCT images that utilizes the optical properties we obtained to improve the visual representation of tissues.

Approach

Using the stationary iteration method under suitable constraint conditions, we derived the approximated solutions of μ and R on a single scattering model. During the iteration, the estimated value of μ can be rectified by introducing the large variations of R , whereas the small ones were automatically ignored. Based on the calculation of the structure information, the OCT intensity with attenuation compensation was deduced and compared with the original OCT profiles.

Results

The preliminary validation was performed in the OCT A-line simulation and Monte Carlo modeling, and the subsequent experiment was conducted on multi-layer silicone-dye-TiO 2 phantoms and ex vivo cow eyes. Our method achieved robust and precise estimation of μ and R for both simulated and experimental data. Moreover, corresponding OCT images with attenuation compensation provided an improved resolution over the entire imaging range.

Conclusions

Our proposed method was able to correct the estimation bias induced by the variations of R and provided accurate depth-resolved measurements of both μ and R simultaneously. The method does not require prior knowledge of the morphological information of tissue and represents more real-life tissues. Thus, it has the potential to help OCT imaging based disease diagnosis of complex and multi-layer biological tissue.

Mapping optical scattering properties to physical particle information in singly and multiply scattering samples

Optical coherence tomography (OCT) leverages light scattering by biological tissues as endogenous contrast to form structural images. Light scattering behavior is dictated by the optical properties of the tissue, which depend on microstructural details at the cellular or sub-cellular level. Methods to measure these properties from OCT intensity data have been explored in the context of a number of biomedical applications seeking to access this sub-resolution tissue microstructure and thereby increase the diagnostic impact of OCT. Most commonly, the optical attenuation coefficient, an analogue of the scattering coefficient, has been used as a surrogate metric linking OCT intensity to subcellular particle characteristics. To record attenuation coefficient data that is accurately representative of the underlying physical properties of a given sample, it is necessary to account for the impact of the OCT imaging system itself on the distribution of light intensity in the sample, including the numerical aperture (NA) of the system and the location of the focal plane with respect to the sample surface, as well as the potential contribution of multiple scattering to the reconstructed intensity signal. Although these considerations complicate attenuation coefficient measurement and interpretation, a suitably calibrated system may potentiate a powerful strategy for gaining additional information about the scattering behavior and microstructure of samples. In this work, we experimentally show that altering the OCT system geometry minimally impacts measured attenuation coefficients in samples presumed to be singly scattering, but changes these measurements in more highly scattering samples. Using both depth-resolved attenuation coefficient data and layer-resolved backscattering coefficients, we demonstrate the retrieval of scattering particle diameter and concentration in tissue-mimicking phantoms, and the impact of presumed multiple scattering on these calculations. We further extend our approach to characterize a murine brain tissue sample and highlight a tumor-bearing region based on increased scattering particle density. Through these methods, we not only enhance conventional OCT attenuation coefficient analysis by decoupling the independent effects of particle size and concentration, but also discriminate areas of strong multiple scattering through minor changes to system topology to provide a framework for assessing the accuracy of these measurements.

Intraoperative application of optical coherence tomography for lung tumor

On-site instant determination of benign or malignant tumors for deciding the types of resection is crucial during pulmonary surgery. We designed a portable spectral-domain optical coherence tomography (SD-OCT) system to do real-time scanning intraoperatively for the distinction of fresh tumor specimens in the lung. A total of 12 ex vivo lung specimens from six patients were enrolled. Three patients were diagnosed with invasive adenocarcinoma (IA), while the others were benign. After OCT-imaged reconstruction, we compared the qualitative morphology of OCT and histology among malignant, benign, and normal tissues. In addition, through analysis of the quantitative data, a discrete difference in optical attenuation coefficients around the junctional surface was shown by our data processing. This study demonstrated a feasible OCT-assisted resection guide by a rapid on-site tumor diagnosis. The results indicate that future deep learning of OCT-captured image systems able to improve diagnostic and therapeutic efficiency is warranted.

Signal-Decay Based Approach for Visualization of Buried Defects in 3-D Printed Ceramic Components Imaged with Help of Optical Coherence Tomography

We propose the use of Optical Coherence Tomography (OCT) as a tool for the quality control of 3-D-printed ceramics. Test samples with premeditated defects, namely single- and two-component samples of zirconia, titania, and titanium suboxides, were printed by stereolithography-based DLP (Digital Light Processing) processes. The OCT tomograms obtained on the green samples showed the capability of the method to visualize variations in the layered structure of the samples as well as the presence of cracks and inclusions at depths up to 130 µm, as validated by SEM images. The structural information was visible in cross-sectional images as well as in plan-view images. The optical signal measured from the printed zirconia oxide and titanium oxide samples showed strong attenuation with depth and could be fit with an exponential decay curve. The variations of the decay parameter correlated very well with the presence of defects and material variation. When used as an imaging quantity, the decay parameter projects the position of the defects into 2-D (X,Y) coordinates. This procedure can be used in real time, it reduces the data volume up to 1000 times, and allows for faster subsequent data analysis and transfer. Tomograms were also obtained on sintered samples. The results showed that the method can detect changes in the optical properties of the green ceramics caused by sintering. Specifically, the zirconium oxide samples became more transparent to the light used, whereas the titanium suboxide samples became entirely opaque. In addition, the optical response of the sintered zirconium oxide showed variations within the imaged volume, indicating material density variations. The results presented in this study show that OCT provides sufficient structural information on 3-D-printed ceramics and can be used as an in-line tool for quality control.

Arterial pulsation modulates the optical attenuation coefficient of skin

Photoplethysmographic (PPG) signals arise from the modulation of light reflectivity on the skin due to changes of physiological origin. Imaging plethysmography (iPPG) is a video-based PPG method that can remotely monitor vital signs in a non-invasive manner. iPPG signals result from skin reflectivity modulation. The origin of such reflectivity modulation is still a subject of debate. Here, we have used optical coherence tomography (OCT) imaging to find whether iPPG signals may result from skin optical properties being directly or indirectly modulated by arterial transmural pressure propagation. The light intensity across the tissue was modeled through a simple exponential decay (Beer-Lambert law) to analyze in vivo the modulation of the optical attenuation coefficient of the skin by arterial pulsation. The OCT transversal images were acquired from a forearm of three subjects in a pilot study. The results show that the optical attenuation coefficient of skin changes at the same frequency as the arterial pulsation due to transmural pressure propagation (local ballistographic effect), but we cannot discard the contribution of global ballistographic effects.

The neurosurgical benefit of contactless in vivo optical coherence tomography regarding residual tumor detection: A clinical study

Purpose

In brain tumor surgery, it is crucial to achieve complete tumor resection while conserving adjacent noncancerous brain tissue. Several groups have demonstrated that optical coherence tomography (OCT) has the potential of identifying tumorous brain tissue. However, there is little evidence on human in vivo application of this technology, especially regarding applicability and accuracy of residual tumor detection (RTD). In this study, we execute a systematic analysis of a microscope integrated OCT-system for this purpose.

Experimental design

Multiple 3-dimensional in vivo OCT-scans were taken at protocol-defined sites at the resection edge in 21 brain tumor patients. The system was evaluated for its intraoperative applicability. Tissue biopsies were obtained at these locations, labeled by a neuropathologist and used as ground truth for further analysis. OCT-scans were visually assessed with a qualitative classifier, optical OCT-properties were obtained and two artificial intelligence (AI)-assisted methods were used for automated scan classification. All approaches were investigated for accuracy of RTD and compared to common techniques.

Results

Visual OCT-scan classification correlated well with histopathological findings. Classification with measured OCT image-properties achieved a balanced accuracy of 85%. A neuronal network approach for scan feature recognition achieved 82% and an auto-encoder approach 85% balanced accuracy. Overall applicability showed need for improvement.

Conclusion

Contactless in vivo OCT scanning has shown to achieve high values of accuracy for RTD, supporting what has well been described for ex vivo OCT brain tumor scanning, complementing current intraoperative techniques and even exceeding them in accuracy, while not yet in applicability.

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

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

Using beam-offset optical coherence tomography to reconstruct backscattered photon profiles in scattering media

Raster scanning imaging technologies capture least scattered photons (LSPs) and reject multiple scattered photons (MSPs) in backscattered photons to image the underlying structures of a scattering medium. However, MSPs can still squeeze into the images, resulting in limited imaging depth, degraded contrast, and significantly reduced lateral resolution. Great efforts have been made to understand how MSPs affect imaging performance through modeling, but the techniques for visualizing the backscattered photon profile (BSPP) in scattering media during imaging are unavailable. Here, a method of reconstructing BSPP is demonstrated using beam-offset optical coherence tomography (OCT), in which OCT images are acquired at offset positions from the illumination beam. The separation of LSPs and MSPs based on the BSPP enables quantification of imaging depth, contrast, and lateral resolution, as well as access to the depth-resolved modulated transfer function (MTF). This approach presents great opportunities for better retrieving tissue optical properties, correctly interpreting images, or directly using MTF as the feedback for adaptive optical imaging.

Differentiation of different stages of brain tumor infiltration using optical coherence tomography: Comparison of two systems and histology

The discrimination of tumor-infiltrated tissue from non-tumorous brain tissue during neurosurgical tumor excision is a major challenge in neurosurgery. It is critical to achieve full tumor removal since it directly correlates with the survival rate of the patient. Optical coherence tomography (OCT) might be an additional imaging method in the field of neurosurgery that enables the classification of different levels of tumor infiltration and non-tumorous tissue. This work investigated two OCT systems with different imaging wavelengths (930 nm/1310 nm) and different resolutions (axial (air): 4.9 μm/16 μm, lateral: 5.2 μm/22 μm) in their ability to identify different levels of tumor infiltration based on freshly excised ex vivo brain samples. A convolutional neural network was used for the classification. For both systems, the neural network could achieve classification accuracies above 91% for discriminating between healthy white matter and highly tumor infiltrated white matter (tumor infiltration >60%) .This work shows that both OCT systems with different optical properties achieve similar results regarding the identification of different stages of brain tumor infiltration.

Precision of attenuation coefficient measurements by optical coherence tomography

SIGNIFICANCE

Optical coherence tomography (OCT) is an interferometric imaging modality, which provides tomographic information on the microscopic scale. Furthermore, OCT signal analysis facilitates quantification of tissue optical properties (e.g., the attenuation coefficient), which provides information regarding the structure and organization of tissue. However, a rigorous and standardized measure of the precision of the OCT-derived optical properties, to date, is missing.

AIM

We present a robust theoretical framework, which provides the Cramér -Rao lower bound σμOCT for the precision of OCT-derived optical attenuation coefficients.

APPROACH

Using a maximum likelihood approach and Fisher information, we derive an analytical solution for σμOCT when the position and depth of focus are known. We validate this solution, using simulated OCT signals, for which attenuation coefficients are extracted using a least-squares fitting procedure.

RESULTS

Our analytical solution is in perfect agreement with simulated data without shot noise. When shot noise is present, we show that the analytical solution still holds for signal-to-noise ratios (SNRs) in the fitting window being above 20 dB. For other cases (SNR&lt;20 dB, focus position not precisely known), we show that the numerical calculation of the precision agrees with the σμOCT derived from simulated signals.

CONCLUSIONS

Our analytical solution provides a fast, rigorous, and easy-to-use measure for OCT-derived attenuation coefficients for signals above 20 dB. The effect of uncertainties in the focal point position on the precision in the attenuation coefficient, the second assumption underlying our analytical solution, is also investigated by numerical calculation of the lower bounds. This method can be straightforwardly extended to uncertainty in other system parameters.

Noninvasive hemoglobin sensing and imaging: optical tools for disease diagnosis

SIGNIFICANCE

Measurement and imaging of hemoglobin oxygenation are used extensively in the detection and diagnosis of disease; however, the applied instruments vary widely in their depth of imaging, spatiotemporal resolution, sensitivity, accuracy, complexity, physical size, and cost. The wide variation in available instrumentation can make it challenging for end users to select the appropriate tools for their application and to understand the relative limitations of different methods.

AIM

We aim to provide a systematic overview of the field of hemoglobin imaging and sensing.

APPROACH

We reviewed the sensing and imaging methods used to analyze hemoglobin oxygenation, including pulse oximetry, spectral reflectance imaging, diffuse optical imaging, spectroscopic optical coherence tomography, photoacoustic imaging, and diffuse correlation spectroscopy.

RESULTS

We compared and contrasted the ability of different methods to determine hemoglobin biomarkers such as oxygenation while considering factors that influence their practical application.

CONCLUSIONS

We highlight key limitations in the current state-of-the-art and make suggestions for routes to advance the clinical use and interpretation of hemoglobin oxygenation information.

Spectroscopic optical coherence tomography for classification of colorectal cancer in a mouse model

Noninvasive diagnosis of the malignant potential of colon polyps can improve prevention of colorectal cancer without the need for time-consuming and expensive biopsies. This study examines the use of spectroscopic optical coherence tomography (OCT) to classify tissue from genetically engineered mouse models of early-stage adenoma (APC) and advanced adenocarcinoma (AKP) in which tumors are induced in the distal colon. The optical tissue properties of scattering power and scattering attenuation coefficient are evaluated by analyzing the imaging data collected from tissues. Classifications are generated using 2D linear discriminant analysis with high levels of discrimination obtained. The overall classification accuracy obtained was 91.5%, with 100% sensitivity and 96.7% specificity in separating tumors from benign tissue, and 77.8% sensitivity and 99.4% specificity in separating adenocarcinoma from nonmalignant tissue. Thus, this study demonstrates the clinical potential of using spectroscopic OCT for rapid detection of colon adenoma and colorectal cancer.

Optical Coherence Tomography Measurements of the Retinal Pigment Epithelium to Bruch Membrane Thickness Around Geographic Atrophy Correlate With Growth

PURPOSE

The retinal pigment epithelium (RPE) to Bruch membrane (BM) distance around geographic atrophy (GA) was measured using an optical attenuation coefficient (OAC) algorithm to determine whether this measurement could serve as a clinical biomarker to predict the annual square root enlargement rate (ER) of GA.

DESIGN

A retrospective analysis of a prospective, observational case series.

METHODS

Eyes with GA secondary to age-related macular degeneration (AMD) were imaged with swept-source OCT (SS-OCT) using a 6 × 6-mm scan pattern. GA lesions were identified and measured using customized en face OCT images, and GA annual square root ERs were calculated. At baseline, the OACs were calculated from OCT datasets to generate customized en face OAC images for GA visualization. RPE-BM distances were measured using OAC data from different subregions around the GA.

RESULTS

A total of 38 eyes from 27 patients were included in this study. Measured RPE-BM distances were the highest in the region closest to GA. The RPE-BM distances immediately around the GA were significantly correlated with GA annual square root ERs (r = 0.595, P < .001 for a 0- to 300-µm rim around the GA). No correlations were found between RPE-BM distances and previously published choriocapillaris (CC) flow deficits in any subregions.

CONCLUSIONS

RPE-BM distances from regions around the GA significantly correlate with the annual ERs of GA. These results suggest that an abnormally thickened RPE/BM complex contributes to GA growth and that this effect is independent of CC perfusion deficits.

Automatic geographic atrophy segmentation using optical attenuation in OCT scans with deep learning

A deep learning algorithm was developed to automatically identify, segment, and quantify geographic atrophy (GA) based on optical attenuation coefficients (OACs) calculated from optical coherence tomography (OCT) datasets. Normal eyes and eyes with GA secondary to age-related macular degeneration were imaged with swept-source OCT using 6 × 6 mm scanning patterns. OACs calculated from OCT scans were used to generate customized composite en face OAC images. GA lesions were identified and measured using customized en face sub-retinal pigment epithelium (subRPE) OCT images. Two deep learning models with the same U-Net architecture were trained using OAC images and subRPE OCT images. Model performance was evaluated using DICE similarity coefficients (DSCs). The GA areas were calculated and compared with manual segmentations using Pearson's correlation and Bland-Altman plots. In total, 80 GA eyes and 60 normal eyes were included in this study, out of which, 16 GA eyes and 12 normal eyes were used to test the models. Both models identified GA with 100% sensitivity and specificity on the subject level. With the GA eyes, the model trained with OAC images achieved significantly higher DSCs, stronger correlation to manual results and smaller mean bias than the model trained with subRPE OCT images (0.940 ± 0.032 vs 0.889 ± 0.056, p = 0.03, paired t-test, r = 0.995 vs r = 0.959, mean bias = 0.011 mm vs mean bias = 0.117 mm). In summary, the proposed deep learning model using composite OAC images effectively and accurately identified, segmented, and quantified GA using OCT scans.

Fast and accurate spectral-estimation axial super-resolution optical coherence tomography

Spectral-estimation OCT (SE-OCT) is a computational method to enhance the axial resolution beyond the traditional bandwidth limit. However, it has not yet been used widely due to its high computational load, dependency on user-optimized parameters, and inaccuracy in intensity reconstruction. In this study, we implement SE-OCT using a fast implementation of the iterative adaptive approach (IAA). This non-parametric spectral estimation method is optimized for use on OCT data. Both in simulations and experiments we show an axial resolution improvement with a factor between 2 and 10 compared to standard discrete Fourier transform. Contrary to parametric methods, IAA gives consistent peak intensity and speckle statistics. Using a recursive and fast reconstruction scheme the computation time is brought to the sub-second level for a 2D scan. Our work shows that SE-OCT can be used for volumetric OCT imaging in a reasonable computation time, thus paving the way for wide-scale implementation of super-resolution OCT.

Investigation of methods to extract confocal function parameters for the depth resolved determination of attenuation coefficients using OCT in intralipid samples, titanium oxide phantoms, and in vivo human retinas

The attenuation coefficient provides a quantitative parameter for tissue characterization and can be calculated from optical coherence tomography (OCT) data, but accurate determination requires compensation for the confocal function. We present extensive measurement series for extraction of the focal plane and the apparent Rayleigh length from the ratios of OCT images acquired with different focus depths and compare these results with two alternative approaches. By acquiring OCT images for a range of different focus depths the optimal focus plane difference is determined for intralipid and titanium oxide (TiO₂) phantoms with different scatterer concentrations, which allows for calculation of the attenuation coefficient corrected for the confocal function. The attenuation coefficient is determined for homogeneous intralipid and TiO₂ samples over a wide range of concentrations. We further demonstrate very good reproducibility of the determined attenuation coefficient of layers with identical scatter concentrations in a multi-layered phantom. Finally, this method is applied to in vivo retinal data.

Three-dimensional dynamics optical coherence tomography for tumor spheroid evaluation

We present a completely label-free three-dimensional (3D) optical coherence tomography (OCT)-based tissue dynamics imaging method for visualization and quantification of the metabolic and necrotic activities of tumor spheroid. Our method is based on a custom 3D scanning protocol that is designed to capture volumetric tissue dynamics tomography images only in a few tens of seconds. The method was applied to the evaluation of a tumor spheroid. The time-course viability alteration and anti-cancer drug response of the spheroid were visualized qualitatively and analyzed quantitatively. The similarity between the OCT-based dynamics images and fluorescence microscope images was also demonstrated.

Investigation of the scattering and attenuation properties of cataracts formed in mouse eyes with 1060-nm and 1310-nm swept-source optical coherence tomography

Cataracts are the leading cause of blindness worldwide. Here we propose optical coherence tomography (OCT) as a quantitative method for investigating cataracts. OCT provides volumetric and non-invasive access to the lens and makes it possible to rapidly observe the formation of opacifications in animal models such as mice. We compared the performance of two different wavelengths - 1060 nm and 1310 nm - for OCT imaging in cataract research. In addition, we present multi-contrast OCT capable of mapping depth-resolved scattering and average anterior cortical attenuation properties of the crystalline lens and quantitatively characterize induced cataract development in the mouse eye. Lastly, we also propose a novel method based on the retinal OCT projection image for quantifying and mapping opacifications in the lens, which showed a good correlation with scattering and attenuation characteristics simultaneously analyzed during the process of cataract formation in the lens.

Random laser as a potential tool for the determination of the scattering coefficient

The determination of the optical properties of a turbid medium is a major topic in the field of optics. Generally, they comprise the parameters µ _a , µ _s , g and n. There is, however, a lack of techniques for the direct determination of the scattering coefficient µ _s . This study, therefore, proposes the random laser (RL) as a tool to directly measure µ _s - and not μ s ' . Evidence is found that it is possible to determine µ _s in the diffusive regime by means of the RL. Based on these findings, a local model of the RL is developed and presented in this study.

Identification of oral precancerous and cancerous tissue by swept source optical coherence tomography

BACKGROUND AND OBJECTIVES

Distinguishing cancer from precancerous lesions is critical and challenging in oral medicine. As a noninvasive method, optical coherence tomography (OCT) has the advantages of real-time, in vivo, and large-depth imaging. Texture information hidden in OCT images can provide an important auxiliary effect for improving diagnostic accuracy. The aim of this study is to explore a reliable and accurate OCT-based method for the screening and diagnosis of human oral diseases, especially oral cancer.

MATERIALS AND METHODS

Fresh ex vivo oral tissues including normal mucosa, leukoplakia with epithelial hyperplasia (LEH), and oral squamous cell carcinoma (OSCC) were imaged intraoperatively by a homemade OCT system, and 58 texture features were extracted to create computational models of these tissues. A principal component analysis algorithm was employed to optimize the combination of texture feature vectors. The identification based on artificial neural network (ANN) was proposed and the sensitivity/specificity was calculated statistically to evaluate the classification performance.

RESULTS

A total of 71 sites of three types of oral tissues were measured, and 5176 OCT images of three types of oral tissues were used in this study. The superior classification result based on ANN was obtained with an average accuracy of 98.17%. The sensitivity and specificity of normal mucosa, LEH, and OSCC are 98.17% / 98.38%, 93.81% / 98.54%, and 98.11% / 99.04%, respectively.

CONCLUSION

It is demonstrated from the high accuracies, sensitivities, and specificities that texture-based analysis can be used to identify oral precancerous and cancerous tissue in OCT images, and it has the potential to help surgeons in diseases screening and diagnosis effectively.

Noninvasive OCT angiography-based blood attenuation measurements correlate with blood glucose level in the mouse retina

In this study, we investigated the correlation of the blood optical attenuation coefficient (OAC) and the blood glucose concentration (BGC). The blood OAC was measured in mouse retina in vivo by analyzing the depth attenuation of backscattered light under the guidance of OCT angiography (OCTA) vascular mapping, and then its correlation to the BGC was further investigated. The optical attenuation of the blood components presented a more reliable correlation to BGC than that of the background tissues. The arteries and veins presented a blood OAC change of ∼0.05-0.07 mm^-1 per 10 mg/dl and a significant (P < 0.001) elevation of blood OAC in diabetic mice was observed. Furthermore, different kinds of vessels also presented different performances. The veins had a higher correlation coefficient (R=0.86) between the measured blood OAC and BGC than that of the arteries (R=0.73). Besides, the blood OAC changes of the specific vessels occur without any obvious change in the vascular morphology in the retina. The blood OAC-BGC correlation suggests a concept of non-invasive OCTA-based glucometry, allowing a fast assessment of the blood glucose of specific vessels with superior motion immunity. A direct glucometry of the retina would be helpful for accurately monitoring the progression of diabetic retinopathy.

Layer-based, depth-resolved computation of attenuation coefficients and backscattering fractions in tissue using optical coherence tomography

Structural optical coherence tomography (OCT) images of tissue stand to benefit from greater functionalization and quantitative interpretation. The OCT attenuation coefficient µ, an analogue of the imaged sample's scattering coefficient, offers potential functional contrast based on the relationship of µ to sub-resolution physical properties of the sample. Attenuation coefficients are computed either by fitting a representative µ over several depth-wise pixels of a sample's intensity decay, or by using previously-developed depth-resolved attenuation algorithms by Girard et al. [Invest. Ophthalmol. Vis. Sci.52, 7738 (2011). 10.1167/iovs.10-6925] and Vermeer et al. [Biomed. Opt. Express5, 322 (2014). 10.1364/BOE.5.000322]. However, the former method sacrifices axial information in the tomogram, while the latter relies on the stringent assumption that the sample's backscattering fraction, another optical property, does not vary along depth. This assumption may be violated by layered tissues commonly observed in clinical imaging applications. Our approach preserves the full depth resolution of the attenuation map but removes its dependence on backscattering fraction by performing signal analysis inside individual discrete layers over which the scattering properties (e.g., attenuation and backscattering fraction) vary minimally. Although this approach necessitates the detection of these layers, it removes the constant-backscattering-fraction assumption that has constrained quantitative attenuation coefficient analysis in the past, and additionally yields a layer-resolved backscattering fraction, providing complementary scattering information to the attenuation coefficient. We validate our approach using automated layer detection in layered phantoms, for which the measured optical properties were in good agreement with theoretical values calculated with Mie theory, and show preliminary results in tissue alongside corresponding histological analysis. Together, accurate backscattering fraction and attenuation coefficient measurements enable the estimation of both particle density and size, which is not possible from attenuation measurements alone. We hope that this improvement to depth-resolved attenuation coefficient measurement, augmented by a layer-resolved backscattering fraction, will increase the diagnostic power of quantitative OCT imaging.

In vivo measurement of the attenuation coefficient of the sclera and ciliary muscle

We acquired 1325 nm OCT images of the sclera and ciliary muscle of human subjects. The attenuation coefficients of the sclera and ciliary muscle were determined from a curve fit of the average intensity profile of about 100 A-lines in a region of interest after correction for the effect of beam geometry, using a single scattering model. The average scleral attenuation coefficient was 4.13 ± 1.42 mm-1 with an age-related decrease that was near the threshold for statistical significance (p = 0.053). The average ciliary muscle attenuation coefficient was 1.72 ± 0.88 mm-1, but this value may be an underestimation due to contributions from multiple scattering. Overall, the results suggest that inter-individual variations in scleral attenuation contribute to variability in the quality of transscleral OCT images of the ciliary muscle and the outcome of transscleral laser therapies.

Applying machine learning to optical coherence tomography images for automated tissue classification in brain metastases

Purpose

A precise resection of the entire tumor tissue during surgery for brain metastases is essential to reduce local recurrence. Conventional intraoperative imaging techniques all have limitations in detecting tumor remnants. Therefore, there is a need for innovative new imaging methods such as optical coherence tomography (OCT). The purpose of this study is to discriminate brain metastases from healthy brain tissue in an ex vivo setting by applying texture analysis and machine learning algorithms for tissue classification to OCT images.

Methods

Tumor and healthy tissue samples were collected during resection of brain metastases. Samples were imaged using OCT. Texture features were extracted from B-scans. Then, a machine learning algorithm using principal component analysis (PCA) and support vector machines (SVM) was applied to the OCT scans for classification. As a gold standard, an experienced pathologist examined the tissue samples histologically and determined the percentage of vital tumor, necrosis and healthy tissue of each sample. A total of 14.336 B-scans from 14 tissue samples were included in the classification analysis.

Results

We were able to discriminate vital tumor from healthy brain tissue with an accuracy of 95.75%. By comparing necrotic tissue and healthy tissue, a classification accuracy of 99.10% was obtained. A generalized classification between brain metastases (vital tumor and necrosis) and healthy tissue was achieved with an accuracy of 96.83%.

Conclusions

An automated classification of brain metastases and healthy brain tissue is feasible using OCT imaging, extracted texture features and machine learning with PCA and SVM. The established approach can prospectively provide the surgeon with additional information about the tissue, thus optimizing the extent of tumor resection and minimizing the risk of local recurrences.

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.

Attenuation coefficient estimation in Fourier-domain OCT of multi-layered phantoms

Optical properties, such as the attenuation coefficients of multi-layer tissue samples, could be used as a biomarker for diagnosis and disease progression in clinical practice. In this paper, we present a method to estimate the attenuation coefficients in a multi-layer sample by fitting a single scattering model for the OCT signal to the recorded OCT signal. In addition, we employ numerical simulations to obtain the theoretically achievable precision and accuracy of the estimated parameters under various experimental conditions. Finally, the method is applied to two sets of measurements obtained from a multi-layer phantom by two experimental OCT systems: one with a large and one with a small Rayleigh length. Numerical and experimental results show an accurate estimation of the attenuation coefficients when using multiple B-scans.

Attenuation corrected-optical coherence tomography for quantitative assessment of skin wound healing and scar morphology

Imaging the structural modifications of underlying tissues is vital to monitor wound healing. Optical coherence tomography (OCT) images high-resolution sub-surface information, but suffers a loss of intensity with depth, limiting quantification. Hence correcting the attenuation loss is important. We performed swept source-OCT of full-thickness excision wounds for 300 days in mice skin. We used single-scatter attenuation models to determine and correct the attenuation loss in the images. The phantom studies established the correspondence of corrected-OCT intensity (reflectivity) with matrix density and hydration. We histologically validated the corrected-OCT and measured the wound healing rate. We noted two distinct phases of healing-rapid and steady-state. We also detected two compartments in normal scars using corrected OCT that otherwise were not visible in the OCT scans. The OCT reflectivity in the scar compartments corresponded to distinct cell populations, mechanical properties and composition. OCT reflectivity has potential applications in evaluating the therapeutic efficacy of healing and characterizing scars.

Characterizing thrombus with multiple red blood cell compositions by optical coherence tomography attenuation coefficient

Embolectomy is one of the emergency procedures performed to remove emboli. Assessing the composition of human blood clots is an important diagnostic factor and could provide guidance for an appropriate treatment strategy for interventional physicians. Immunostaining has been used to identity compositions of clots as a gold-standard procedure, but it is time-consuming and cannot be performed in situ. Here, we proposed that the optical attenuation coefficient of optical coherence tomography (OCT) can be a reliable indicator as a new imaging modality to differentiate clot compositions. Fifteen human blood clots with multiple red blood cell (RBC) compositions from 21% to 95% were prepared using healthy human whole blood. A homogeneous gelatin phantom experiment and numerical simulation based on the Lambert-Beer's law were examined to verify the validity of the attenuation coefficient estimation. The results displayed that optical attenuation coefficients were strongly correlated with RBC compositions. We reported that attenuation coefficients could be a promising biomarker to guide the choice of an appropriate interventional device in a clinical setting and assist in characterizing blood clots.

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.

Bayesian analysis of depth resolved OCT attenuation coefficients

Optical coherence tomography (OCT) is an optical technique which allows for volumetric visualization of the internal structures of translucent materials. Additional information can be gained by measuring the rate of signal attenuation in depth. Techniques have been developed to estimate the rate of attenuation on a voxel by voxel basis. This depth resolved attenuation analysis gives insight into tissue structure and organization in a spatially resolved way. However, the presence of speckle in the OCT measurement causes the attenuation coefficient image to contain unrealistic fluctuations and makes the reliability of these images at the voxel level poor. While the distribution of speckle in OCT images has appeared in literature, the resulting voxelwise corruption of the attenuation analysis has not. In this work, the estimated depth resolved attenuation coefficient from OCT data with speckle is shown to be approximately exponentially distributed. After this, a prior distribution for the depth resolved attenuation coefficient is derived for a simple system using statistical mechanics. Finally, given a set of depth resolved estimates which were made from OCT data in the presence of speckle, a posterior probability distribution for the true voxelwise attenuation coefficient is derived and a Bayesian voxelwise estimator for the coefficient is given. These results are demonstrated in simulation and validated experimentally.

Quantitative Analysis of Macular Retina Using Light Reflection Indices Derived from SD-OCT for Pituitary Adenoma

Purpose

To quantitatively investigate the macular retinal light reflection characteristic using optical property indices derived from spectral-domain optical coherence tomography (SD-OCT) scans with depth attenuation compensation for pituitary adenoma.

Methods

This study included 38 patients (mean age 44.66 ± 13.77 years old) with diagnosis of pituitary adenoma and 43 age-matched controls. All SD-OCT scans were light attenuation compensated by a depth-resolved model. Attenuation coefficient, the corrected intensity, and the retinal layer thickness were deduced for macular retinal nerve fiber layer (RNFL) and ganglion cell layer combined with inner plexiform layer (GCIPL), as well as comparing between patients and controls by statistical methods.

Results

Attenuation coefficients of RNFL and GCIPL among patients were significantly lower compared to the controls with P values equal to or less than 0.001. The mean values of the corrected optical intensity were decreased in the patients without universally significant differences. Significant decreases in thickness existing in the RNFL of patients, especially in the superonasal (SN) quadrant and inferonasal (IN) quadrant (decrease ratio = 9.64% and 13.02%, both with P < 0.001). The thickness of RNFL was significantly associated with the attenuation coefficient (standardized beta = 0.335, P=0.002). The performances of attenuation coefficient were better than the corrected optical intensity and the thickness (the values of the areas under the receiver operating characteristic curves = 0.751 and 0.758, both with P < 0.001) in discriminating pituitary adenoma patients from controls.

Conclusions

The retinal light reflection characteristics were debilitated in patients with pituitary adenoma. The potential of attenuation coefficients of RNFL and GCIPL in distinguishing patients with pituitary adenoma from controls was validated by the comparison of the derived optical property indices.

Analysis of attenuation coefficient estimation in Fourier-domain OCT of semi-infinite media

The attenuation coefficient (AC) is an optical property of tissue that can be estimated from optical coherence tomography (OCT) data. In this paper, we aim to estimate the AC accurately by compensating for the shape of the focused beam. For this, we propose a method to estimate the axial PSF model parameters and AC by fitting a model for an OCT signal in a homogenous sample to the recorded OCT signal. In addition, we employ numerical analysis to obtain the theoretical optimal precision of the estimated parameters for different experimental setups. Finally, the method is applied to OCT B-scans obtained from homogeneous samples. The numerical and experimental results show accurate estimations of the AC and the focus location when the focus is located inside the sample.

Integrated effects of fractional laser microablation and sonophoresis on skin immersion optical clearing in vivo

This study is aimed to find an approach for effective skin optical clearing in vivo using polyethylene glycol 300 (PEG-300) as an optical clearing agent in combination with physical enhancers: fractional laser microablation (FLMA) and/or low-frequency sonophoresis. In this study albino outbred rats were used. Light attenuation coefficient and optical clearing potential (OCP) of these approaches were evaluated in upper (from ~70 to ~200 μm) and middle (from ~200 to ~400 μm) dermis separately using optical coherence tomography. In 30 minutes, OCP of sonophoresis in combination with FLMA and PEG-300 in the upper dermis was the maximal (2.3 ± 0.4) in comparison with other treatments in this time point. The most effective approach for optical clearing of middle dermis was PEG-300 and sonophoresis; but the maximal value of OCP (1.6 ± 0.1) was achieved only in 90 minutes.