Automated, Depth-Resolved Estimation of the Attenuation Coefficient From Optical Coherence Tomography Data

A feasibility study on the use of an intraoral optical coherence tomography system for scanning the subgingival finish line for the fabrication of zirconia crowns: An evaluation of the marginal and internal fit

OBJECTIVES

This study aimed to evaluate the marginal and internal fit of zirconia crowns were fabricated using scan data from an intraoral optical coherence tomography (OCT) scanner and an intraoral scanner (IOS) for scanning the subgingival finish line.

METHODS

An extracted maxillary left central incisor was prepared for a zirconia crown. The prepared tooth was placed in artificial gingiva, created using silicone with a refractive index similar to that of the tooth, ensuring a subgingival depth of 0.50 to 0.70 mm from the labial finish line. Scanning data were obtained from four types of models as follows. (1) CAD reference model (CRM) excluding the gingiva and scanned using a laboratory scanner. (2) IOS group excluding the gingiva (IOS only, IOSO group). (3) IOS group with scanned attached artificial (IOS with gingiva, IOSG group). (4) OCT post-processed data of the subgingival finish line and IOSG data (OCT group). Zirconia crowns were fabricated based on these data, and their marginal and internal fit were evaluated using the silicone replica technique. Statistical analyses were conducted using one-way and two-way ANOVA (α = 0.05).

RESULTS

The OCT group exhibited a significantly smaller marginal gap than the IOSG group (P < 0.05). The marginal fit of the OCT group did not significantly differ from that of the CRM group (P > 0.05). The IOSG group exhibited a significantly larger chamfer gap, while both the IOSG and OCT groups had significantly larger axial gaps. Furthermore, the OCT group showed a significantly larger incisal gap (P < 0.05).

CONCLUSIONS

An intraoral OCT system can enhance the fabrication accuracy of zirconia crowns by achieving superior marginal fit for crowns with subgingival finish lines.

CLINICAL SIGNIFICANCE

The use of an IOS for subgingival finish lines without gingival displacement cords may result in a suboptimal marginal fit. However, integrating OCT technology can effectively address this issue, leading to improved clinical outcomes.

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.

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.

Multiparameter interferometric polarization-enhanced imaging differentiates carcinoma in situ from inflammation of the bladder: an ex vivo study

Significance

Successful differentiation of carcinoma in situ (CIS) from inflammation in the bladder is key to preventing unnecessary biopsies and enabling accurate therapeutic decisions. Current standard-of-care diagnostic imaging techniques lack the specificity needed to differentiate these states, leading to false positives.

Aim

We introduce multiparameter interferometric polarization-enhanced (MultiPIPE) imaging as a promising technology to improve the specificity of detection for better biopsy guidance and clinical outcomes.

Approach

In this ex vivo study, we extract tissue attenuation-coefficient-based and birefringence-based parameters from MultiPIPE imaging data, collected with a bench-top system, to develop a classifier for the differentiation of benign and CIS tissues. We also analyze morphological features from second harmonic generation imaging and histology slides and perform imaging-to-morphology correlation analysis.

Results

MultiPIPE enhances specificity to differentiate CIS from benign tissues by nearly 20% and reduces the false-positive rate by more than four-fold over clinical standards. We also show that the MultiPIPE measurements correlate well with changes in morphological features in histological assessments.

Conclusions

The results of our study show the promise of MultiPIPE imaging to be used for better differentiation of bladder inflammation from flat tumors, leading to a fewer number of unnecessary procedures and shorter operating room (OR) time.

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.

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.

QOCT-Net: A Physics-Informed Neural Network for Intravascular Optical Coherence Tomography Attenuation Imaging

Intravascular optical coherence tomography (IVOCT) provides high-resolution, depth-resolved images of coronary arterial microstructure by acquiring backscattered light. Quantitative attenuation imaging is important for accurate characterization of tissue components and identification of vulnerable plaques. In this work, we proposed a deep learning method for IVOCT attenuation imaging based on the multiple scattering model of light transport. A physics-informed deep network named Quantitative OCT Network (QOCT-Net) was designed to recover pixel-level optical attenuation coefficients directly from standard IVOCT B-scan images. The network was trained and tested on simulation and in vivo datasets. Results showed superior attenuation coefficient estimates both visually and based on quantitative image metrics. The structural similarity, energy error depth and peak signal-to-noise ratio are improved by at least 7%, 5% and 12.4%, respectively, compared with the state-of-the-art non-learning methods. This method potentially enables high-precision quantitative imaging for tissue characterization and vulnerable plaque identification.

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.

Accuracy and precision of depth-resolved estimation of attenuation coefficients in optical coherence tomography

Significance

Parametric imaging of the attenuation coefficient μ OCT using optical coherence tomography (OCT) is a promising approach for evaluating abnormalities in tissue. To date, a standardized measure of accuracy and precision of μ OCT by the depth-resolved estimation (DRE) method, as an alternative to least squares fitting, is missing.

Aim

We present a robust theoretical framework to determine accuracy and precision of the DRE of μ OCT .

Approach

We derive and validate analytical expressions for the accuracy and precision of μ OCT determination by the DRE using simulated OCT signals in absence and presence of noise. We compare the theoretically achievable precisions of the DRE method and the least-squares fitting approach.

Results

Our analytical expressions agree with the numerical simulations for high signal-to-noise ratios and qualitatively describe the dependence on noise otherwise. A commonly used simplification of the DRE method results in a systematic overestimation of the attenuation coefficient in the order of μ OCT 2 × Δ , where Δ is the pixel stepsize. When μ OCT · | AFR | ≲ 1.8 , μ OCT is reconstructed with higher precision by the depth-resolved method compared to fitting over the length of an axial fitting range | AFR | .

Conclusions

We derived and validated expressions for the accuracy and precision of DRE of μ OCT . A commonly used simplification of this method is not recommended as being used for OCT-attenuation reconstruction. We give a rule of thumb providing guidance in the choice of estimation method.

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.

Depth-resolved extraction of optical attenuation for glaucoma assessment in clinical settings: a pilot study

We assessed the ability of the optical attenuation coefficient (AC) to detect early-stage glaucoma with two AC estimation algorithms: retinal layer intensity ratio (LIR) and depth-resolved confocal (DRC). We also introduced new depth-dependent AC parameters for retinal nerve fiber layer assessment. Optical coherence tomography B-scans were collected from 44 eyes of age-similar participants with eye health ranging from healthy to severe glaucoma, including glaucoma suspect patients. Mean AC values estimated from the DRC method are comparable to ratio-extracted values (p > 0.5 for all study groups), and the depth-dependent AC_DRC parameters enhance the utility of the AC for detection of early-stage glaucoma.

Differentiation between normal and tumor mammary glands with depth-resolved attenuation coefficient from optical coherence tomography

Optical coherence tomography (OCT) is a well-established imaging technology for high-resolution, cross-sectional imaging of biological tissues. Imaging processing and light attenuation coefficient estimation allows to further improve the OCT diagnostic capability. In this paper we use a commercial OCT system, Telesto II-1325LR from Thorlabs, and demonstrate its ability to differentiate normal and tumor mammary mouse glands with the OCT attenuation coefficient. Using several OCT images of normal and tumor mammary mouse glands (n = 26), a statistical analysis was performed. The attenuation coefficient was calculated in depth, considering a slope of 0.5 mm. The normal glands present a median attenuation coefficient of 0.403 mm^-1, comparatively to 0.561 mm^-1obtained for tumor mammary glands. This translates in an attenuation coefficient approximately 39% higher for tumor mammary glands when compared to normal mammary glands. The OCT attenuation coefficient estimation eliminates the subjective analysis provided by direct visualization of the OCT images.

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.

Characterization and quantification of necrotic tissues and morphology in multicellular ovarian cancer tumor spheroids using optical coherence tomography

The three-dimensional (3D) tumor spheroid model is a critical tool for high-throughput ovarian cancer research and anticancer drug development in vitro. However, the 3D structure prevents high-resolution imaging of the inner side of the spheroids. We aim to visualize and characterize 3D morphological and physiological information of the contact multicellular ovarian tumor spheroids growing over time. We intend to further evaluate the distinctive evolutions of the tumor spheroid and necrotic tissue volumes in different cell numbers and determine the most appropriate mathematical model for fitting the growth of tumor spheroids and necrotic tissues. A label-free and noninvasive swept-source optical coherence tomography (SS-OCT) imaging platform was applied to obtain two-dimensional (2D) and 3D morphologies of ovarian tumor spheroids over 18 days. Ovarian tumor spheroids of two different initial cell numbers (5,000- and 50,000- cells) were cultured and imaged (each day) over the time of growth in 18 days. Four mathematical models (Exponential-Linear, Gompertz, logistic, and Boltzmann) were employed to describe the growth kinetics of the tumor spheroids volume and necrotic tissues. Ovarian tumor spheroids have different growth curves with different initial cell numbers and their growths contain different stages with various growth rates over 18 days. The volumes of 50,000-cells spheroids and the corresponding necrotic tissues are larger than that of the 5,000-cells spheroids. The formation of necrotic tissue in 5,000-cells numbers is slower than that in the 50,000-cells ones. Moreover, the Boltzmann model exhibits the best fitting performance for the growth of tumor spheroids and necrotic tissues. Optical coherence tomography (OCT) can serve as a promising imaging modality to visualize and characterize morphological and physiological features of multicellular ovarian tumor spheroids. The Boltzmann model integrating with 3D OCT data of ovarian tumor spheroids provides great potential for high-throughput cancer research in vitro and aiding in drug development.

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.

Method for parametric imaging of attenuation by intravascular optical coherence tomography

Catheter-based intravascular optical coherence tomography (IVOCT) is a powerful imaging modality for visualization of atherosclerosis with high resolution. Quantitative characterization of various tissue types by attenuation coefficient (AC) extraction has been proven to be a potentially significant application of OCT attenuation imaging. However, existing methods for AC extraction from OCT suffer from the challenge of variability in complex tissue types in IVOCT pullback data such as healthy vessel wall, mixed atherosclerotic plaques, plaques with a single component and stent struts, etc. This challenge leads to the ineffectiveness in the tissue differentiation by AC representation based on single scattering model of OCT signal. In this paper, we propose a novel method based on multiple scattering model for parametric imaging of optical attenuation by AC retrieval from IVOCT images conventionally acquired during cardiac catheterization. The OCT signal characterized by the AC is physically modeled by Monte Carlo simulation. Then, the pixel-wise AC retrieval is achieved by iteratively minimizing an error function regarding the modeled and measured backscattered signal. This method provides a general scheme for AC extraction from IVOCT without the premise of complete attenuation of the incident light through the imaging depths. Results of computer-simulated and clinical images demonstrate that the method can avoid overestimation at the end of the depth profile in comparison with the approaches based on the depth-resolved (DR) model. The energy error depth and structural similarity are improved by about 30% and 10% respectively compared with DR. It provides a useful way to differentiate and characterize arterial tissue types in IVOCT images.

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.

Improving the characterization of ex vivo human brain optical properties using high numerical aperture optical coherence tomography by spatially constraining the confocal parameters

Significance: The optical properties of biological samples provide information about the structural characteristics of the tissue and any changes arising from pathological conditions. Optical coherence tomography (OCT) has proven to be capable of extracting tissue's optical properties using a model that combines the exponential decay due to tissue scattering and the axial point spread function that arises from the confocal nature of the detection system, particularly for higher numerical aperture (NA) measurements. A weakness in estimating the optical properties is the inter-parameter cross-talk between tissue scattering and the confocal parameters defined by the Rayleigh range and the focus depth. Aim: In this study, we develop a systematic method to improve the characterization of optical properties with high-NA OCT. Approach: We developed a method that spatially parameterizes the confocal parameters in a previously established model for estimating the optical properties from the depth profiles of high-NA OCT. Results: The proposed parametrization model was first evaluated on a set of intralipid phantoms and then validated using a low-NA objective in which cross-talk from the confocal parameters is negligible. We then utilize our spatially parameterized model to characterize optical property changes introduced by a tissue index matching process using a simple immersion agent, 2,2'-thiodiethonal. Conclusions: Our approach improves the confidence of parameter estimation by reducing the degrees of freedom in the non-linear fitting model.

Three-dimensional mapping of the attenuation coefficient in optical coherence tomography to enhance breast tissue microarchitecture contrast

Effective intraoperative tumor margin assessment is needed to reduce re-excision rates in breast-conserving surgery (BCS). Mapping the attenuation coefficient in optical coherence tomography (OCT) throughout a sample to create an image (attenuation imaging) is one promising approach. For the first time, three-dimensional OCT attenuation imaging of human breast tissue microarchitecture using a wide-field (up to ~45 × 45 × 3.5 mm) imaging system is demonstrated. Representative results from three mastectomy and one BCS specimen (from 31 specimens) are presented with co-registered postoperative histology. Attenuation imaging is shown to provide substantially improved contrast over OCT, delineating nuanced features within tumors (including necrosis and variations in tumor cell density and growth patterns) and benign features (such as sclerosing adenosis). Additionally, quantitative micro-elastography (QME) images presented alongside OCT and attenuation images show that these techniques provide complementary contrast, suggesting that multimodal imaging could increase tissue identification accuracy and potentially improve tumor margin assessment.

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.

Platform for quantitative multiscale imaging of tissue composition

Changes in the multi-level physical structure of biological features going from cellular to tissue level composition is a key factor in many major diseases. However, we are only beginning to understand the role of these structural changes because there are few dedicated multiscale imaging platforms with sensitivity at both the cellular and macrostructural spatial scale. A single platform reduces bias and complications from multiple sample preparation methods and can ease image registration. In order to address these needs, we have developed a multiscale imaging system using a range of imaging modalities sensitive to tissue composition: Ultrasound, Second Harmonic Generation Microscopy, Multiphoton Microscopy, Optical Coherence Tomography, and Enhanced Backscattering. This paper details the system design, the calibration for each modality, and a demonstration experiment imaging a rabbit eye.

Quantitative research on the interaction between cerebral edema and peripheral cerebral blood perfusion using swept-source optical coherence tomography

Background

Ischemic cerebral edema (CE) is a major leading cause of death in patients with ischemic stroke. The CE progression is closely related to the local cerebral blood perfusion (LCBP) level surrounding the edema area. Quantitative studying the interaction between the CE and peripheral LCBP may provide new inspiration for control and even treatment of CE.

Methods

Photothrombosis ischemia mouse model was established and observed for 9 hours using swept-source optical coherence tomography (SS-OCT). OCT-based angiography and OCT-based attenuation imaging techniques were used to reconstruct the angiograms reflecting the cerebral blood perfusion (CBP) level and optical attenuation coefficient (OAC) maps reflecting the edema state. The influence of edema on LCBP was analyzed by quantifying the blood perfusion in different spatial locations around the edema tissue, and the influence of LCBP on CE progression was revealed by comparing the changes of the edema area and LCBP level over time.

Results

Preliminary studies show that the effect of edema tissue on LCBP is very significant, which shows a clear spatial dependence. LCBP near the edema tissue is 15-20% lower than that far away from the edema tissue. When the LCBP drops to around 60% of the initial value, the edema area increases sharply. In addition, the level of CBP in the contralateral hemisphere also decreases with time. When the contralateral CBP drops to around 60%, there is a certain probability that contralateral edema will occur.

Conclusions

CE progression is not only related to the LCBP around the edema tissue but also related to the CBP of non-edematous regions. Controlling the CBP level of non-edematous regions may play a positive role in the treatment of CE. This work provides a new method and inspiration for exploring the mechanism of ischemic CE progression.

Robust, accurate depth-resolved attenuation characterization in optical coherence tomography

Depth-resolved optical attenuation coefficient is a valuable tissue parameter that complements the intensity-based structural information in optical coherent tomography (OCT) imaging. Herein we systematically analyzed the under- and over-estimation bias of existing depth-resolved methods when applied to real biological tissues, and then proposed a new algorithm that remedies these issues and accommodates general OCT data that contain incomplete decay and noise floor, thereby affording consistent estimation accuracy for practical biological samples of different scattering properties. Compared with other algorithms, our method demonstrates remarkably improved estimation accuracy and numerical robustness, as validated via numerical simulations and on experimental OCT data obtained from both silicone-TiO₂ phantoms and human ventral tongue leukoplakia samples.

Simultaneous detection of cerebral blood perfusion and cerebral edema using swept-source optical coherence tomography

The progression of ischemic cerebral edema (CE) is closely related to the level of cerebral blood perfusion (CBP) and affects each other. Simultaneous detection of CBP and CE is helpful in understanding the mechanisms of ischemic CE development. In this article, a wide field of view swept-source optical coherence tomography system was used to detect CE status and CBP levels simultaneously in middle cerebral artery occlusion rats. Images reflecting these two physiological states can be reconstructed with only one C-scan. We quantify these two physiological states into four parameters, which contain two vascular parameters (vascular displacement distance and vascular perfusion density) and two edema parameters (optical attenuation coefficient and edema area). The association between the two vascular parameters and the two edema parameters was analyzed. The results show that there is a strong linear relationship between blood flow parameters and edema parameters. This work provides a new option for CE in vivo detection, and is very likely to play an important role in the development of relevant drugs or in selection of treatment options.

General model for depth-resolved estimation of the optical attenuation coefficients in optical coherence tomography

We present the proof of concept of a general model that uses the tissue sample transmittance as input to estimate the depth-resolved attenuation coefficient of tissue samples using optical coherence tomography (OCT). This method allows us to obtain an image of tissue optical properties instead of intensity contrast, guiding diagnosis and tissues differentiation, extending its application from thick to thin samples. The performance of our method was simulated and tested with the assistance of a home built single-layered and multilayered phantoms (~100 μm each layer) with known attenuation coefficient on the range of 0.9 to 2.32 mm^-1 . It is shown that the estimated depth-resolved attenuation coefficient recovers the reference values, measured by using an integrating sphere followed by the inverse adding doubling processing technique. That was corroborated for all situations when the correct transmittance value is used with an average difference of 7%. Finally, we applied the proposed method to estimate the depth-resolved attenuation coefficient for a thin biological sample, demonstrating the ability of our method on real OCT images.

Cerebral edema detection in vivo after middle cerebral artery occlusion using swept-source optical coherence tomography

Cerebral edema is a severe complication of ischemic cerebrovascular disease, which can lead to microcirculation compression resulting in additional ischemic damage. Real-time and continuous in vivo imaging techniques for edema detection are of great significance to basic research on cerebral edema. We attempted to monitor the cerebral edema status in rats with middle cerebral artery occlusion (MCAO) over time, using a wide field-of-view swept-source optical coherence tomography (SS-OCT) system. Optical attenuation coefficients (OACs) were calculated by an optimized depth-resolved estimation method, and en face OAC maps covering the whole cortex were obtained. Then, the tissue affected by edema was segmented from the OAC maps, and the cortical area affected by edema was estimated. Both magnetic resonance image (MRI) and brain water content measurements were used to verify the presence of cerebral edema. The results showed that the average OAC of the ischemic area gradually decreased as cerebral edema progressed, and the edema area detected by SS-OCT had high similarity in position and shape to that obtained by MRI. This work extends the application of OCT and provides an option for detecting cerebral edema in vivo after ischemic stroke.

Review of methods and applications of attenuation coefficient measurements with optical coherence tomography

The optical attenuation coefficient (AC), an important tissue parameter that measures how quickly incident light is attenuated when passing through a medium, has been shown to enable quantitative analysis of tissue properties from optical coherence tomography (OCT) signals. Successful extraction of this parameter would facilitate tissue differentiation and enhance the diagnostic value of OCT. In this review, we discuss the physical and mathematical basis of AC extraction from OCT data, including current approaches used in modeling light scattering in tissue and in AC estimation. We also report on demonstrated clinical applications of the AC, such as for atherosclerotic tissue characterization, malignant lesion detection, and brain injury visualization. With current studies showing AC analysis as a promising technique, further efforts in the development of methods to accurately extract the AC and to explore its potential use for more extensive clinical applications are desired.

Optimized depth-resolved estimation to measure optical attenuation coefficients from optical coherence tomography and its application in cerebral damage determination

The optical attenuation coefficient (OAC) reflects the optical properties of various tissues or tissues of the same type under different physiological conditions. Quantitative measurement of OAC from optical coherence tomography (OCT) signals can provide additional information and can increase the potential for OCT applications. We present an optimized depth-resolved estimation (ODRE) method that derives a precise mapping between the measured OCT signal and the OAC. In contrast to previous depth-resolved estimation (DRE) methods, the optimized method can estimate the OAC in any depth range and ignore whether the light is completely attenuated. Numerical simulations and phantom experiments are used to verify its validity, and this method is applied to detect cerebral damage. In combination with OCT angiography, real-time observation of the change of blood perfusion and the degree of cerebral damage in mice with focal cerebral ischemia provides important information to help us understand the temporal relationship between brain damage and ischemia.

Automatically Determining the Confocal Parameters From OCT B-Scans for Quantification of the Attenuation Coefficients

The attenuation coefficient is a relevant biomarker for many diagnostic medical applications. Recently, the Depth-Resolved Confocal (DRC) technique was developed to automatically estimate the attenuation coefficients from Optical Coherence Tomography (OCT) data with pixel-level resolution. However, DRC requires that the confocal function parameters (i.e., focal plane location and apparent Rayleigh range) be known a priori. In this paper, we present the autoConfocal algorithm: a simple, automatic method for estimating those parameters directly from OCT imagery when the focal plane is within the sample. We present autoConfocal+DRC results on phantom data, ex-vivo biological tissue data, and in-vivo clinical data.

Determination of confocal profile and curved focal plane for OCT mapping of the attenuation coefficient

The attenuation coefficient has proven to be a useful tool in numerous biological applications, but accurate calculation is dependent on the characterization of the confocal effect. This study presents a method to precisely determine the confocal effect and its focal plane within a sample by examining the ratio of two optical coherence tomography (OCT) images. The method can be employed to produce a single-value estimate, or a 2D map of the focal plane accounting for the curvature or tilt within the sample. Furthermore, this method is applicable to data obtained with both high numerical aperture (NA) and low-NA lenses, thereby furthering the applicability of the attenuation coefficient to high-NA OCT data. We test and validate this method using standard samples of Intralipid 20% and 5%, improving the accuracy to 99% from 65% compared to the traditional method and preliminarily show applicability to real biological data of glioblastoma acquired in vivo in a murine model.

Quantifying optical properties with visible and near-infrared optical coherence tomography to visualize esophageal microwave ablation zones

Microwave ablation is a minimally invasive image guided thermal therapy for cancer that can be adapted to endoscope use in the gastrointestinal (GI) tract. Microwave ablation in the GI tract requires precise control over the ablation zone that could be guided by high resolution imaging with quantitative contrast. Optical coherence tomography (OCT) provides ideal imaging resolution and allows for the quantification of tissue scattering properties to characterize ablated tissue. Visible and near-infrared OCT image analysis demonstrated increased scattering coefficients (μ_s ) in ablated versus normal tissues (Vis: 347.8%, NIR: 415.0%) and shows the potential for both wavelength ranges to provide quantitative contrast. These data suggest OCT could provide quantitative image guidance and valuable information about antenna performance in vivo.

Characterizing the optical properties of human brain tissue with high numerical aperture optical coherence tomography

Quantification of tissue optical properties with optical coherence tomography (OCT) has proven to be useful in evaluating structural characteristics and pathological changes. Previous studies primarily used an exponential model to analyze low numerical aperture (NA) OCT measurements and obtain the total attenuation coefficient for biological tissue. In this study, we develop a systematic method that includes the confocal parameter for modeling the depth profiles of high NA OCT, when the confocal parameter cannot be ignored. This approach enables us to quantify tissue optical properties with higher lateral resolution. The model parameter predictions for the scattering coefficients were tested with calibrated microsphere phantoms. The application of the model to human brain tissue demonstrates that the scattering and back-scattering coefficients each provide unique information, allowing us to differentially identify laminar structures in primary visual cortex and distinguish various nuclei in the midbrain. The combination of the two optical properties greatly enhances the power of OCT to distinguish intricate structures in the human brain beyond what is achievable with measured OCT intensity information alone, and therefore has the potential to enable objective evaluation of normal brain structure as well as pathological conditions in brain diseases. These results represent a promising step for enabling the quantification of tissue optical properties from high NA OCT.

Whole mouse brain imaging using optical coherence tomography: reconstruction, normalization, segmentation, and comparison with diffusion MRI

An automated massive histology setup combined with an optical coherence tomography (OCT) microscope was used to image a total of [Formula: see text] whole mouse brains. Each acquisition generated a dataset of thousands of OCT volumetric tiles at a sampling resolution of [Formula: see text]. This paper describes techniques for reconstruction and segmentation of the sliced brains. In addition to the measured OCT optical reflectivity, a single scattering photon model was used to compute the attenuation coefficients within each tissue slice. Average mouse brain templates were generated for both the OCT reflectivity and attenuation contrasts and were used with an [Formula: see text]-tissue segmentation algorithm. To better understand the brain tissue OCT contrast origin, one of the mouse brains was acquired using dMRI and coregistered to its corresponding assembled brain. Our results indicate that the optical reflectivity in a fiber bundle varies with its orientation, its fiber density, and the number of fiber orientations it contains. The OCT mouse brain template generation and coregistration to dMRI data demonstrate the potential of this massive histology technique to pursue cross-sectional, multimodal, and multisubject investigations of small animal brains.

Tissue characterization with depth-resolved attenuation coefficient and backscatter term in intravascular optical coherence tomography images

An important application of intravascular optical coherence tomography (IVOCT) for atherosclerotic tissue analysis is using it to estimate attenuation and backscatter coefficients. This work aims at exploring the potential of the attenuation coefficient, a proposed backscatter term, and image intensities in distinguishing different atherosclerotic tissue types with a robust implementation of depth-resolved (DR) approach. Therefore, the DR model is introduced to estimate the attenuation coefficient and further extended to estimate the backscatter-related term in IVOCT images, such that values can be estimated per pixel without predefining any delineation for the estimation. In order to exclude noisy regions with a weak signal, an automated algorithm is implemented to determine the cut-off border in IVOCT images. The attenuation coefficient, backscatter term, and the image intensity are further analyzed in regions of interest, which have been delineated referring to their pathology counterparts. Local statistical values were reported and their distributions were further compared with a two-sample t-test to evaluate the potential for distinguishing six types of tissues. Results show that the IVOCT intensity, DR attenuation coefficient, and backscatter term extracted with the reported implementation are complementary to each other on characterizing six tissue types: mixed, calcification, fibrous, lipid-rich, macrophages, and necrotic core.

Speckle-modulating optical coherence tomography in living mice and humans

Optical coherence tomography (OCT) is a powerful biomedical imaging technology that relies on the coherent detection of backscattered light to image tissue morphology in vivo. As a consequence, OCT is susceptible to coherent noise (speckle noise), which imposes significant limitations on its diagnostic capabilities. Here we show speckle-modulating OCT (SM-OCT), a method based purely on light manipulation that virtually eliminates speckle noise originating from a sample. SM-OCT accomplishes this by creating and averaging an unlimited number of scans with uncorrelated speckle patterns without compromising spatial resolution. Using SM-OCT, we reveal small structures in the tissues of living animals, such as the inner stromal structure of a live mouse cornea, the fine structures inside the mouse pinna, and sweat ducts and Meissner’s corpuscle in the human fingertip skin—features that are otherwise obscured by speckle noise when using conventional OCT or OCT with current state of the art speckle reduction methods.

Optical coherence tomography, a technique that can image inside tissue, is susceptible to speckle noise that limits its diagnostic potential. Here, Liba et al. show that speckle noise can be removed without effectively compromising resolution, revealing previously hidden small structures within tissue.

Reconstruction of stented coronary arteries from optical coherence tomography images: Feasibility, validation, and repeatability of a segmentation method

Optical coherence tomography (OCT) is an established catheter-based imaging modality for the assessment of coronary artery disease and the guidance of stent placement during percutaneous coronary intervention. Manual analysis of large OCT datasets for vessel contours or stent struts detection is time-consuming and unsuitable for real-time applications. In this study, a fully automatic method was developed for detection of both vessel contours and stent struts. The method was applied to in vitro OCT scans of eight stented silicone bifurcation phantoms for validation purposes. The proposed algorithm comprised four main steps, namely pre-processing, lumen border detection, stent strut detection, and three-dimensional point cloud creation. The algorithm was validated against manual segmentation performed by two independent image readers. Linear regression showed good agreement between automatic and manual segmentations in terms of lumen area (r>0.99). No statistically significant differences in the number of detected struts were found between the segmentations. Mean values of similarity indexes were >95% and >85% for the lumen and stent detection, respectively. Stent point clouds of two selected cases, obtained after OCT image processing, were compared to the centerline points of the corresponding stent reconstructions from micro computed tomography, used as ground-truth. Quantitative comparison between the corresponding stent points resulted in median values of ~150 μm and ~40 μm for the total and radial distances of both cases, respectively. The repeatability of the detection method was investigated by calculating the lumen volume and the mean number of detected struts per frame for seven repeated OCT scans of one selected case. Results showed low deviation of values from the median for both analyzed quantities. In conclusion, this study presents a robust automatic method for detection of lumen contours and stent struts from OCT as supported by focused validation against both manual segmentation and micro computed tomography and by good repeatability.

Tissue perfusion modelling in optical coherence tomography

Background

Optical coherence tomography (OCT) is a well established imaging technique with different applications in preclinical research and clinical practice. The main potential for its application lies in the possibility of noninvasively performing “optical biopsy”. Nevertheless, functional OCT imaging is also developing, in which perfusion imaging is an important approach in tissue function study. In spite of its great potential in preclinical research, advanced perfusion imaging using OCT has not been studied. Perfusion analysis is based on administration of a contrast agent (nanoparticles in the case of OCT) into the bloodstream, where during time it specifically changes the image contrast. Through analysing the concentration-intensity curves we are then able to find out further information about the examined tissue.

Methods

We have designed and manufactured a tissue mimicking phantom that provides the possibility of measuring dilution curves in OCT sequence with flow rates 200, 500, 1000 and 2000 μL/min. The methodology comprised of using bolus of 50 μL of gold nanorods as a contrast agent (with flow rate 5000 μL/min) and continuous imaging by an OCT system. After data acquisition, dilution curves were extracted from OCT intensity images and were subjected to a deconvolution method using an input–output system description. The aim of this was to obtain impulse response characteristics for our model phantom within the tissue mimicking environment. Four mathematical tissue models were used and compared: exponential, gamma, lagged and LDRW.

Results

We have shown that every model has a linearly dependent parameter on flow (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^2$$\end{document}R2 values from 0.4914 to 0.9996). We have also shown that using different models can lead to a better understanding of the examined model or tissue. The lagged model surpassed other models in terms of the minimisation criterion and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^2$$\end{document}R2 value.

Conclusions

We used a tissue mimicking phantom in our study and showed that OCT can be used for advanced perfusion analysis using mathematical model and deconvolution approach. The lagged model with three parameters is the most appropriate model. Nevertheless, further research have to be performed, particularly with real tissue.

Electronic supplementary material

The online version of this article (doi:10.1186/s12938-017-0320-4) contains supplementary material, which is available to authorized users.

Multimodal 3D cancer-mimicking optical phantom

Three-dimensional (3D) organ-mimicking phantoms provide realistic imaging environments for testing various aspects of optical systems, including for evaluating new probe designs, characterizing the diagnostic potential of new technologies, and assessing novel image processing algorithms prior to validation in real tissue. We introduce and characterize the use of a new material, Dragon Skin (Smooth-On Inc.), and fabrication technique, air-brushing, for fabrication of a 3D phantom that mimics the appearance of a real organ under multiple imaging modalities. We demonstrate the utility of the material and technique by fabricating the first 3D, hollow bladder phantom with realistic normal and multi-stage pathology features suitable for endoscopic detection using the gold standard imaging technique, white light cystoscopy (WLC), as well as the complementary imaging modalities of optical coherence tomography and blue light cystoscopy, which are aimed at improving the sensitivity and specificity of WLC to bladder cancer detection. The flexibility of the material and technique used for phantom construction allowed for the representation of a wide range of diseased tissue states, ranging from inflammation (benign) to high-grade cancerous lesions. Such phantoms can serve as important tools for trainee education and evaluation of new endoscopic instrumentation.