Polarization-sensitive optical coherence elastography

Multiple scattering suppression for in vivo optical coherence tomography measurement using the B-scan-wise multi-focus averaging method

We demonstrate a method that reduces the noise caused by multi-scattering (MS) photons in an in vivo optical coherence tomography image. This method combines a specially designed image acquisition (i.e., optical coherence tomography scan) scheme and subsequent complex signal processing. For the acquisition, multiple cross-sectional images (frames) are sequentially acquired while the depth position of the focus is altered for each frame by an electrically tunable lens. In the signal processing, the frames are numerically defocus-corrected, and complex averaged. Because of the inconsistency in the MS-photon trajectories among the different electrically tunable lens-induced defocus, this averaging reduces the MS signal. Unlike the previously demonstrated volume-wise multi-focus averaging method, our approach requires the sample to remain stable for only a brief period, approximately 70 ms, thus making it compatible with in vivo imaging. This method was validated using a scattering phantom and in vivo unanesthetized small fish samples, and was found to reduce MS noise even for unanesthetized in vivo measurement.

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.

Neural-network based high-speed volumetric dynamic optical coherence tomography

We demonstrate deep-learning neural network (NN)-based dynamic optical coherence tomography (DOCT), which generates high-quality logarithmic-intensity-variance (LIV) DOCT images from only four OCT frames. The NN model is trained for tumor spheroid samples using a customized loss function: the weighted mean absolute error. This loss function enables highly accurate LIV image generation. The fidelity of the generated LIV images to the ground truth LIV images generated using 32 OCT frames is examined via subjective image observation and statistical analysis of image-based metrics. Fast volumetric DOCT imaging with an acquisition time of 6.55 s/volume is demonstrated using this NN-based method.

Polarization-artifact reduction and accuracy improvement of Jones-matrix polarization-sensitive optical coherence tomography by multi-focus-averaging based multiple scattering reduction

Polarization-sensitive optical coherence tomography (PS-OCT) is a promising biomedical imaging tool for the differentiation of various tissue properties. However, the presence of multiple-scattering (MS) signals can degrade the quantitative polarization measurement accuracy. We demonstrate a method to reduce MS signals and increase the measurement accuracy of Jones matrix PS-OCT. This method suppresses MS signals by averaging multiple Jones matrix volumes measured using different focal positions. The MS signals are decorrelated among the volumes by focus position modulation and are thus reduced by averaging. However, the single scattering signals are kept consistent among the focus-modulated volumes by computational refocusing. We validated the proposed method using a scattering phantom and a postmortem medaka fish. The results showed reduced artifacts in birefringence and degree-of-polarization uniformity measurements, particularly in deeper regions in the samples. This method offers a practical solution to mitigate MS-induced artifacts in PS-OCT imaging and improves quantitative polarization measurement accuracy.

Renal tubular function and morphology revealed in kidney without labeling using three-dimensional dynamic optical coherence tomography

Renal tubule has distinct metabolic features and functional activity that may be altered during kidney disease. In this paper, we present label-free functional activity imaging of renal tubule in normal and obstructed mouse kidney models using three-dimensional (3D) dynamic optical coherence tomography (OCT) ex vivo. To create an obstructed kidney model, we ligated the ureter of the left kidney for either 7 or 14 days. Two different dynamic OCT (DOCT) methods were implemented to access the slow and fast activity of the renal tubules: a logarithmic intensity variance (LIV) method and a complex-correlation-based method. Three-dimensional DOCT data were acquired with a 1.3 [Formula: see text]m swept-source OCT system and repeating raster scan protocols. In the normal kidney, the renal tubule appeared as a convoluted pipe-like structure in the DOCT projection image. Such pipe-like structures were not observed in the kidneys subjected to obstruction of the ureter for several days. Instead of any anatomical structures, a superficial high dynamics appearance was observed in the perirenal cortex region of the obstructed kidneys. These findings suggest that volumetric LIV can be used as a tool to investigate kidney function during kidney diseases.

Multi-focus averaging for multiple scattering suppression in optical coherence tomography

Multiple scattering is one of the main factors that limits the penetration depth of optical coherence tomography (OCT) in scattering samples. We propose a method termed multi-focus averaging (MFA) to suppress the multiple-scattering signals and improve the image contrast of OCT in deep regions. The MFA method captures multiple OCT volumes with various focal positions and averages them in complex form after correcting the varying defocus through computational refocusing. Because the multiple-scattering takes different trajectories among the different focal position configurations, this averaging suppresses the multiple-scattering signal. Meanwhile, the single-scattering takes a consistent trajectory regardless of the focal position configuration and is not suppressed. Hence, the MFA method improves the ratio between the single-scattering signal and multiple-scattering signal, resulting in an enhancement in the image contrast. A scattering phantom and a postmortem zebrafish were measured to validate the proposed method. The results showed that the contrast of intensity images of both the phantom and zebrafish were improved using the MFA method, such that they were better than the contrast provided by the standard single focus averaging method. The MFA method provides a cost-effective solution for contrast enhancement through multiple-scattering reduction in tissue imaging using OCT systems.

Dynamic optical coherence tomography for cell analysis [Invited]

Label-free live optical imaging of dynamic cellular and subcellular features has been made possible in recent years thanks to the advances made in optical imaging techniques, including dynamic optical coherence tomography (D-OCT) methods. These techniques analyze the temporal fluctuations of an optical signal associated with the active movements of intracellular organelles to obtain an ensemble metric recapitulating the motility and metabolic state of cells. They hence enable visualization of cells within compact, static environments and evaluate their physiology. These emerging microscopies show promise, in particular for the three-dimensional evaluation of live tissue samples such as freshly excised biopsies and 3D cell cultures. In this review, we compare the various techniques used for dynamic OCT. We give an overview of the range of applications currently being explored and discuss the future outlook and opportunities for the field.

Renal tubular function and morphology revealed in kidney without labeling using three-dimensional dynamic optical coherence tomography.. [DOI: 10.1101/2023.05.01.539010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Renal tubule has distinct metabolic features and functional activity that may be altered during kidney disease. In this paper, we present label-free functional activity imaging of renal tubule in normal and obstructed mouse kidney models using three-dimensional (3D) dynamic optical coherence tomography (OCT)ex vivo. To create an obstructed kidney model, we ligated the ureter of the left kidney for either 7 or 14 days. Two different dynamic OCT (DOCT) methods were implemented to access the slow and fast activity of the renal tubules: a logarithmic intensity variance (LIV) method and a complex-correlation-based method. Three-dimensional DOCT data were acquired with a 1.3 μm swept-source OCT system and repeating raster scan protocols. In the normal kidney, the renal tubule appeared as a convoluted pipe-like structure in the DOCT projection image. Such pipe-like structures were not observed in the kidneys subjected to obstruction of the ureter for several days. Instead of any anatomical structures, a superficial high dynamics appearance was observed in the perirenal cortex region of the obstructed kidneys. These findings suggest that volumetric DOCT can be used as a tool to investigate kidney function during kidney diseases.

Three-dimensional mechanical characterization of murine skeletal muscle using quantitative micro-elastography

Skeletal muscle function is governed by both the mechanical and structural properties of its constituent tissues, which are both modified by disease. Characterizing the mechanical properties of skeletal muscle tissue at an intermediate scale, i.e., between that of cells and organs, can provide insight into diseases such as muscular dystrophies. In this study, we use quantitative micro-elastography (QME) to characterize the micro-scale elasticity of ex vivo murine skeletal muscle in three-dimensions in whole muscles. To address the challenge of achieving high QME image quality with samples featuring uneven surfaces and geometry, we encapsulate the muscles in transparent hydrogels with flat surfaces. Using this method, we study aging and disease in quadriceps tissue by comparing normal wild-type (C57BL/6J) mice with dysferlin-deficient BLAJ mice, a model for the muscular dystrophy dysferlinopathy, at 3, 10, and 24 months of age (sample size of three per group). We observe a 77% decrease in elasticity at 24 months in dysferlin-deficient quadriceps compared to wild-type quadriceps.

Label-free metabolic imaging of non-alcoholic-fatty-liver-disease (NAFLD) liver by volumetric dynamic optical coherence tomography

Label-free metabolic imaging of non-alcoholic fatty liver disease (NAFLD) mouse liver is demonstrated ex vivo by dynamic optical coherence tomography (OCT). The NAFLD mouse is a methionine choline-deficient (MCD)-diet model, and two mice fed the MCD diet for 1 and 2 weeks are involved in addition to a normal-diet mouse. The dynamic OCT is based on repeating raster scan and logarithmic intensity variance (LIV) analysis that enables volumetric metabolic imaging with a standard-speed (50,000 A-lines/s) OCT system. Metabolic domains associated with lipid droplet accumulation and inflammation are clearly visualized three-dimensionally. Particularly, the normal-diet liver exhibits highly metabolic vessel-like structures of peri-vascular hepatic zones. The 1-week MCD-diet liver shows ring-shaped highly metabolic structures formed with lipid droplets. The 2-week MCD-diet liver exhibits fragmented vessel-like structures associated with inflammation. These results imply that volumetric LIV imaging is useful for visualizing and assessing NAFLD abnormalities.

Computational refocusing of Jones matrix polarization-sensitive optical coherence tomography and investigation of defocus-induced polarization artifacts

Here we demonstrate a long-depth-of-focus imaging method using polarization sensitive optical coherence tomography (PS-OCT). This method involves a combination of Fresnel-diffraction-model-based phase sensitive computational refocusing and Jones-matrix based PS-OCT (JM-OCT). JM-OCT measures four complex OCT images corresponding to four polarization channels. These OCT images are computationally refocused as preserving the mutual phase consistency. This method is validated using a static phantom, postmortem zebrafish, and ex vivo porcine muscle samples. All the samples demonstrated successful computationally-refocused birefringence and degree-of-polarization-uniformity (DOPU) images. We found that defocusing induces polarization artifacts, i.e., incorrectly high birefringence values and low DOPU values, which are substantially mitigated by computational refocusing.

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.

Label-free functional and structural imaging of liver microvascular complex in mice by Jones matrix optical coherence tomography

We demonstrate label-free imaging of the functional and structural properties of microvascular complex in mice liver. The imaging was performed by a custom-built Jones-matrix based polarization sensitive optical coherence tomography (JM-OCT), which is capable of measuring tissue's attenuation coefficient, birefringence, and tiny tissue dynamics. Two longitudinal studies comprising a healthy liver and an early fibrotic liver model were performed. In the healthy liver, we observed distinctive high dynamics beneath the vessel at the initial time point (0 h) and reappearance of high dynamics at 32-h time point. In the early fibrotic liver model, we observed high dynamics signal that reveals a clear network vascular structure by volume rendering. Longitudinal time-course imaging showed that these high dynamics signals faded and decreased over time.

Differentiation of breast tissue types for surgical margin assessment using machine learning and polarization-sensitive optical coherence tomography

We report an automated differentiation model for classifying malignant tumor, fibro-adipose, and stroma in human breast tissues based on polarization-sensitive optical coherence tomography (PS-OCT). A total of 720 PS-OCT images from 72 sites of 41 patients with H&E histology-confirmed diagnoses as the gold standard were employed in this study. The differentiation model is trained by the features extracted from both one standard OCT-based metric (i.e., intensity) and four PS-OCT-based metrics (i.e., phase difference between two channels (PD), phase retardation (PR), local phase retardation (LPR), and degree of polarization uniformity (DOPU)). Further optimized by forward searching and validated by leave-one-site-out-cross-validation (LOSOCV) method, the best feature subset was acquired with the highest overall accuracy of 93.5% for the model. Furthermore, to show the superiority of our differentiation model based on PS-OCT images over standard OCT images, the best model trained by intensity-only features (usually obtained by standard OCT systems) was also obtained with an overall accuracy of 82.9%, demonstrating the significance of the polarization information in breast tissue differentiation. The high performance of our differentiation model suggests the potential of using PS-OCT for intraoperative human breast tissue differentiation during the surgical resection of breast cancer.

Impact-induced cartilage damage assessed using polarisation-sensitive optical coherence tomography

Non-invasive determination of structural changes in articular cartilage immediately after impact and rehydration provides insight into the response and recovery of the soft tissue, as well as provides a potential methodology for clinicians to quantify early degenerative changes. In this study, we use polarisation-sensitive optical coherence tomography (PS-OCT) to examine subtle alterations of the optical properties in healthy and early-stage degenerate articular cartilage immediately after impact loading to identify structurally relevant metrics required for understanding the mechanical factors of osteoarthritic initiation and progression. A custom-designed impact testing rig was used to deliver 0.9 J and 1.4 J impact energies to bovine articular cartilage. A total of 52 (n=26 healthy, n=26 mildly degenerate) cartilage-on-bone samples were imaged before, immediately after, and 3 h after impact. PS-OCT images were analyzed to assess changes relating to surface irregularity, optical attenuation, and birefringence. Mildly degenerate cartilage exhibits a significant change in birefringence following 1.4 J impact energies compared to healthy samples which is believed to be attributable to degenerate cartilage being unable to fully utilise the fluid phase to distribute and dampen the energy. After rehydration, the polarisation-sensitive images appear to 'optically-recover' reducing the reliability of birefringence as an absolute metric. Surface irregularity and optical attenuation encode diagnostically relevant information and may serve as markers to predict the mechanical response of articular cartilage. PS-OCT with its ability to non-invasively image the sub-surface microstructural abnormalities of cartilage presents as an ideal modality for cartilage degeneration assessment and identification of mechanically vulnerable tissue.

Optical coherence tomography-based tissue dynamics imaging for longitudinal and drug response evaluation of tumor spheroids

We present optical coherence tomography (OCT)-based tissue dynamics imaging method to visualize and quantify tissue dynamics such as subcellular motion based on statistical analysis of rapid-time-sequence OCT signals at the same location. The analyses include logarithmic intensity variance (LIV) method and two types of OCT correlation decay speed analysis (OCDS). LIV is sensitive to the magnitude of the signal fluctuations, while OCDSs including early- and late-OCDS (OCDS e and OCDS l , respectively) are sensitive to the fast and slow tissue dynamics, respectively. These methods were able to visualize and quantify the longitudinal necrotic process of a human breast adenocarcinoma spheroid and its anti-cancer drug response. Additionally, the effects of the number of OCT signals and the total acquisition time on dynamics imaging are examined. Small number of OCT signals, e.g., five or nine suffice for dynamics imaging when the total acquisition time is suitably long.

Depth-resolved investigation of multiple optical properties and wrinkle morphology in eye-corner areas with multi-contrast Jones matrix optical coherence tomography

BACKGROUND

Multi-contrast Jones matrix optical coherence tomography (JM-OCT) can provide quantitative depth-resolved local optical properties by improving the measurement algorithm.

MATERIALS AND METHODS

We examined the relationship between depth-resolved local optical properties of eye-corner skin measured by JM-OCT and corresponding wrinkle morphology of aged women (n = 21; age range, 71.7 ± 1.7 years). Wrinkle morphology was analyzed by measuring the surface topography of three-dimensional replicas. The same regions were measured three-dimensionally by JM-OCT, and the local optical properties at each depth were computed.

RESULTS

Birefringence (BR) and mean wrinkle depth correlated significantly at a depth of 88.2-138.6 µm from the skin surface, and attenuation coefficient (AC) and mean wrinkle depth correlated significantly at a depth of 12.6-18.9 µm and 189-459.9 μm from the skin surface, although a degree of polarization uniformity (DOPU) did not. Stepwise multiple regression analysis demonstrated that a significant regression equation (R²  = 0.649, P < .001) for predicting mean wrinkle depth was determined by BR at 107.1 µm depth (BR _{107.1 µm} ), DOPU at 170.1 µm (DOPU _170.1µm ), and AC at 252 µm (AC _{252 µm} ) as independent variables and that these standardized beta regression coefficients were -0.860, -0.593, and -0.440, respectively, suggesting that BR, DOPU, and AC sufficiently explained mean wrinkle depth.

CONCLUSION

These results suggest that BR _{107.1 µm} , DOPU _{170.1 µm,} and AC _{252 µm} may indicate collagen-related structure in the papillary, upper-reticular dermis, and microstructure or tissue density in reticular dermis, respectively, and may be involved in wrinkle formation.