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

Optical-coherence-tomography-based deep-learning scatterer-density estimator using physically accurate noise model

We demonstrate a deep-learning-based scatterer density estimator (SDE) that processes local speckle patterns of optical coherence tomography (OCT) images and estimates the scatterer density behind each speckle pattern. The SDE is trained using large quantities of numerically simulated OCT images and their associated scatterer densities. The numerical simulation uses a noise model that incorporates the spatial properties of three types of noise, i.e., shot noise, relative-intensity noise, and non-optical noise. The SDE's performance was evaluated numerically and experimentally using two types of scattering phantom and in vitro tumor spheroids. The results confirmed that the SDE estimates scatterer densities accurately. The estimation accuracy improved significantly when compared with our previous deep-learning-based SDE, which was trained using numerical speckle patterns generated from a noise model that did not account for the spatial properties of noise.

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.

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.

Multiparametric Quantitative Analysis of Photodamage to Skin Using Optical Coherence Tomography

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

Integrating a pressure sensor with an OCT handheld probe to facilitate imaging of microvascular information in skin tissue beds

Optical coherence tomography (OCT) and OCT angiography (OCTA) have been increasingly applied in skin imaging applications in dermatology, where the imaging is often performed with the OCT probe in contact with the skin surface. However, this contact mode imaging can introduce uncontrollable mechanical stress applied to the skin, inevitably complicating the interpretation of OCT/OCTA imaging results. There remains a need for a strategy for assessing local pressure applied on the skin during imaging acquisition. This study reports a handheld scanning probe integrated with built-in pressure sensors, allowing the operator to control the mechanical stress applied to the skin in real-time. With real time feedback information, the operator can easily determine whether the pressure applied to the skin would affect the imaging quality so as to obtain repeatable and reliable OCTA images for a more accurate investigation of skin conditions. Using this probe, imaging of palm skin was used in this study to demonstrate how the OCTA imaging would have been affected by different mechanical pressures ranging from 0 to 69 kPa. The results showed that OCTA imaging is relatively stable when the pressure is less than 11 kPa, and within this range, the change of vascular area density calculated from the OCTA imaging is below 0.13%. In addition, the probe was used to augment the OCT monitoring of blood flow changes during a reactive hyperemia experiment, in which the operator could properly control the amount of pressure applied to the skin surface and achieve full release after compression stimulation.

Depth-resolved visualization and automated quantification of hyperreflective foci on OCT scans using optical attenuation coefficients

An automated depth-resolved algorithm using optical attenuation coefficients (OACs) was developed to visualize, localize, and quantify hyperreflective foci (HRF) seen on OCT imaging that are associated with macular hyperpigmentation and represent an increased risk of disease progression in age related macular degeneration. To achieve this, we first transformed the OCT scans to linear representation, which were then contrasted by OACs. HRF were visualized and localized within the entire scan by differentiating HRF within the retina from HRF along the retinal pigment epithelium (RPE). The total pigment burden was quantified using the en face sum projection of an OAC slab between the inner limiting membrane (ILM) to Bruch's membrane (BM). The manual total pigment burden measurements were also obtained by combining manual outlines of HRF in the B-scans with the total area of hypotransmission defects outlined on sub-RPE slabs, which was used as the reference to compare with those obtained from the automated algorithm. 6×6 mm swept-source OCT scans were collected from a total of 49 eyes from 42 patients with macular HRF. We demonstrate that the algorithm was able to automatically distinguish between HRF within the retina and HRF along the RPE. In 24 test eyes, the total pigment burden measurements by the automated algorithm were compared with measurements obtained from manual segmentations. A significant correlation was found between the total pigment area measurements from the automated and manual segmentations (P < 0.001). The proposed automated algorithm based on OACs should be useful in studying eye diseases involving HRF.

Optimized OCT-based depth-resolved model for attenuation compensation using point-spread-function calibration

Optical coherence tomography (OCT) with a robust depth-resolved attenuation compensation method for a wide range of imaging applications is proposed and demonstrated. The proposed novel OCT attenuation compensation algorithm introduces an optimized axial point spread function (PSF) to modify existing depth-resolved methods and mitigates under and overestimation in biological tissues, providing a uniform resolution over the entire imaging range. The preliminary study is implemented using A-mode numerical simulation, where this method achieved stable and robust compensation results over the entire depth of samples. The experiment results using phantoms and corneal imaging exhibit agreement with the simulation result evaluated using signal-to-noise (SNR) and contrast-to-noise (CNR) metrics.

Optical coherence tomography and fluorescence microscopy dual-modality imaging for in vivo single-cell tracking with nanowire lasers

Emerging cell-based therapies such as stem cell therapy and immunotherapy have attracted broad attention in both biological research and clinical practice. However, a long-standing technical gap of cell-based therapies is the difficulty of directly assessing treatment efficacy via tracking therapeutically administered cells. Therefore, imaging techniques to follow the in vivo distribution and migration of cells are greatly needed. Optical coherence tomography (OCT) is a clinically available imaging technology with ultrahigh-resolution and excellent imaging depth. It also shows great potential for in vivo cellular imaging. However, due to the homogeneity of current OCT cell labeling contrast agents (such as gold and polymer nanoparticles), only the distribution of entire cell populations can be observed. Precise tracking of the trajectory of individual single cells is not possible with such conventional contrast agents. Microlasers may provide a route to track unique cell identifiers given their small size, high emission intensities, rich emission spectra, and narrow linewidths. Here, we demonstrate that nanowire lasers internalized by cells provide both OCT and fluorescence signal. In addition, cells can be individually identified by the unique lasing emission spectra of the nanowires that they carry. Furthermore, single cell migration trajectories can be monitored both in vitro and in vivo with OCT and fluorescence microscopy dual-modality imaging system. Our study demonstrates the feasibility of nanowire lasers combined with the dual-modality imaging system for in vivo single cell tracking with a high spatial resolution and identity verification, an approach with great utility for stem cell and immunomodulatory therapies.