Conventional Optical Coherence Tomography Research Articles

Enhancement of OCTen faceimages by unsupervised deep learning.

The quality of optical coherence tomography (OCT) en face images is crucial for clinical visualization of early disease. As a three dimensional and coherent imaging, defocus and speckle noise are inevitable, which seriously affect evaluation of microstructure of bio-samples in OCT images. The deep learning has demonstrated great potential in OCT refocusing and denoising, but it is limited by the difficulty of sufficient paired training data. We proposed an unsupervised deep learning-based pipeline to enhance the quality of OCT en face images in this paper. The unregistered defocused conventional OCT images and focused speckle-free OCT images were collected by a home-made speckle modulating OCT system to construct the dataset. The image enhancement model was trained with the cycle training strategy. Finally, the speckle noise and defocus were both effectively improved. The experimental results on complex bio-samples indicated that the proposed method is effective and generalized in enhancing the quality of OCT en face images. The proposed unsupervised deep learning method helps to reduce the complexity of data construction, which is conducive to practical applications in OCT bio-sample imaging.&#xD.

Retinal Nerve Fiber Layer Damage Assessment in Glaucomatous Eyes Using Retinal Retardance Measured by Polarization-Sensitive Optical Coherence Tomography.

To assess the diagnostic performance and structure-function association of retinal retardance (RR), a customized metric measured by a prototype polarization-sensitive optical coherence tomography (PS-OCT), across various stages of glaucoma. This cross-sectional pilot study analyzed 170eyes from 49 healthy individuals and 68 patients with glaucoma. The patients underwent PS-OCT imaging and conventional spectral-domain optical coherence tomography (SD-OCT), as well as visual field (VF) tests. Parameters including RR and retinal nerve fiber layer thickness (RNFLT) were extracted from identical circumpapillary regions of the fundus. Glaucomatous eyes were categorized into early, moderate, or severe stages based on VF mean deviation (MD). The diagnostic performance of RR and RNFLT in discriminating glaucoma from controls was assessed using receiver operating characteristic (ROC) curves. Correlations among VF-MD, RR, and RNFLT were evaluated and compared within different groups of disease severity. The diagnostic performance of both RR and RNFLT was comparable for glaucoma detection (RR AUC = 0.98, RNFLT AUC = 0.97; P = 0.553). RR showed better structure-function association with VF-MD than RNFLT (RR VF-MD = 0.68, RNFLT VF-MD = 0.58; z = 1.99; P = 0.047) in glaucoma cases, especially in severe glaucoma, where the correlation between VF-MD and RR (r = 0.73) was significantly stronger than with RNFLT (r = 0.43, z = 1.96, P = 0.050). In eyes with early and moderate glaucoma, the structure-function association was similar when using RNFLT and RR. RR and RNFLT have similar performance in glaucoma diagnosis. However, in patients with glaucoma especially severe glaucoma, RR showed a stronger correlation with VF test results. Further research is needed to validate RR as an indicator for severe glaucoma evaluation and to explore the benefits of using PS-OCT in clinical practice. We demonstrated that PS-OCT has the potential to evaluate the status of RNFL structural damage in eyes with severe glaucoma, which is currently challenging in clinics.

Vitreous mobility during the posterior vitreous detachment initiation demonstrated by pseudo-motion optical coherence tomography

PurposeTo document the anatomical changes occurring at the vitreoretinal interface during early posterior vitreous detachment (PVD). MethodsWide-angle and pseudo-motion optical coherence tomography (OCT) were obtained on 27 normal eyes during the early stages of age-related PVD. The wide-angle examination in a static phase consisted of montaged conventional OCT images. GIF-formatted pseudo-animation was generated with OCT images acquired initially in a static eye state, followed by scans immediately after ocular excursions. ResultsInitial stages of PVD included peripheral PVD with (stage 1a) or without (stage 1b) interposed material between the posterior vitreous cortex and the retina, and perifoveal PVD expanding to the periphery (stage 2). All stage 1 PVDs presented anterior to the papillomacular vitreous liquefaction. All eyes demonstrated mobility of the vitreous gel at the anterior face of the vitreous liquefaction; however, the adherent cortical vitreous layer comprising the posterior wall of the lacuna showed no mobility. Mobility of the posterior vitreous cortex was not present in eyes with stage 1a PVD and increased with the progression of the stage of PVD (p = 3.60×10−6). ConclusionDuring nonpathological PVD, macula is protected from tractional insults conveyed by mobile vitreous due to overlying vitreous liquefaction. However, the vitreoretinal interface anterior to the lacunae experiences tractional forces until vitreoretinal separation occurs. These observations reinforce the hypothesis that vitreous liquefaction, vitreous mobility, and vitreoschisis formation contribute to PVD initiation and support that premacular lacunae protect the macula during PVD initiation and early progression.

Comparing Three-Dimensional Digitally Enabled Intraoperative OCT With Conventional Microscope-Integrated OCT in Vitreoretinal Surgery: A Post Hoc Analysis of the DISCOVER Study.

This study compared the surgeon experience between conventional microscope-integrated intraoperative optical coherence tomography (iOCT) and digitally enabled microscope-integrated iOCT in vitreoretinal surgery. This is a post hoc case-control analysis of the DISCOVER study. Conventional microscope-integrated iOCT (Rescan 700, Zeiss) was compared with digitally enabled iOCT (Artevo 800, Zeiss). Compared variables included surgical field-based visualization (ie, ocular heads-up display in the conventional group; three-dimensional screen-based visualization in the digital iOCT group) and non-surgical field-based visualization (ie, review on the external two-dimensional monitor). A total of 200 patients were included. Surgical field-based visualization of iOCT was significantly higher in the digitally enabled group (P < 0.0001). Required endoillumination level was significantly lower in the digital iOCT group (P < 0.0001). Surgeons reported "significant" back discomfort and headache more frequently when using conventional iOCT (P = 0.003 and P = 0.001, respectively). Digitally enabled iOCT resulted in greater surgical visualization efficiency, appeared to require a lower illumination level, and may provide advantages for ergonomic-related discomfort. [Ophthalmic Surg Lasers Imaging Retina 2024;55:270-277.].

High-Sensitivity Polarization Sensitive Optical Coherence Tomography Based on Numerical Correction for Perfect Circularly Polarized Light

Polarization sensitive optical coherence tomography (PSOCT) makes use of the birefringence information of the sample to compensate for the lack of internal tissue-specific contrast in conventional optical coherence tomography (OCT). Circularly polarized light is always used as an incident beam in PSOCT, but it is difficult to have perfect in practice. The manual calibration method of circularly polarized light suffers from the problems of complicated calibration operation and lack of stability. This study proposes a simple method to enhance the imaging of PSOCT without altering the system. A numerical calibration of circularly polarized light can be implemented using the original system setup, ensuring that the system’s complexity remains unchanged. Enhancements in imaging quality can be achieved through an algorithmic analysis of the captured interference fringe data. This calibration is applied in the field map of interference data before being quadrature-assembled. Notably, the proposed approach achieves high sensitivity in PSOCT. The birefringence image shows a more obvious layered structure. Improvements in the signal-to-noise ratio (SNR) were demonstrated for chicken breast, pork, and beef imaging at about 20 dB.

Deep learning-based label-free imaging of lymphatics and aqueous veins in the eye using optical coherence tomography

We demonstrate an adaptation of deep learning for label-free imaging of the micro-scale lymphatic vessels and aqueous veins in the eye using optical coherence tomography (OCT). The proposed deep learning-based OCT lymphangiography (DL-OCTL) method was trained, validated and tested, using OCT scans (23 volumetric scans comprising 19,736 B-scans) from 11 fresh ex vivo porcine eyes with the corresponding vessel labels generated by a conventional OCT lymphangiography (OCTL) method based on thresholding with attenuation compensation. Compared to conventional OCTL, the DL-OCTL method demonstrates comparable results for imaging lymphatics and aqueous veins in the eye, with an Intersection over Union value of 0.79 ± 0.071 (mean ± standard deviation). In addition, DL-OCTL mitigates the imaging artifacts in conventional OCTL where the OCT signal modelling was corrupted by the tissue heterogeneity, provides ~ 10 times faster processing based on a rough comparison and does not require OCT-related knowledge for correct implementation as in conventional OCTL. With these favorable features, DL-OCTL promises to improve the practicality of OCTL for label-free imaging of lymphatics and aqueous veins for preclinical and clinical imaging applications.

Clinical Utilisation of Wide-Field Optical Coherence Tomography and Angiography: A Narrative Review.

Many important abnormalities of the vitreous, retina and choroid are predominantly located in the peripheral retina. In some retinal diseases with both central and peripheral manifestations, pathological structural or vascular changes can be apparent in the periphery before they are detectable in the central retina. Conventional optical coherence tomography (OCT) and optical coherence tomography angiography (OCT-A) imaging only cover the most posterior 30° of the retina. Wide-field OCT (WF-OCT), though offering detailed cross-sectional imaging of the peripheral retina, is not yet systematically used in clinical practice. This narrative review provides a presentation of the utilisation of WF-OCT and WF-OCT-A in the diagnosis and monitoring of a variety of ophthalmological diseases and discusses the advantages and limitations of the technology. With the rapidly developing technology, multiple WF-OCT and WF-OCT-A devices are now commercially available and enable the clinician to obtain scans within a field of view up to 200°. As detailed in this review, several studies have shown promising results in the application of WF-OCT and WF-OCT-A in diseases of the retina, choroid and vitreous, such as retinal vein occlusion, diabetic retinopathy, ocular oncology, paediatric ophthalmology, uveitis and lesions of the vitreo-retinal interface. In conclusion, WF-OCT and WF-OCT-A can reliably produce high-quality, non-invasive images of the vitreous, retinal, and choroidal structures and vascularity covering the posterior pole as well as the mid and far periphery. These methods can be a valuable part of a multimodal imaging approach in the management of a variety of ocular conditions. Future studies are warranted to investigate the patient outcome benefits of implementation of WF-OCT and WF-OCT-A imaging in a real-life clinical setting.

Study of dispersion extraction for optical coherence tomography imaging.

Dispersion mismatch of optical coherence tomography (OCT), caused by inherent dispersion of biological sample, leads to axial resolution degradation and image blurring. However, the dispersion of biological samples may carry characteristic information of itself. Therefore, it is useful and important to extract dispersion as an additional parameter of biological samples. Here, we study and compare five categories of conventional OCT dispersion extraction methods first. The results show that the iterative method has the best accuracy and stability. Furthermore, we propose an improved iterative method, which achieves higher accuracy and stability in simulation compared with conventional methods. Then, the dispersion values of optical glasses are extracted experimentally utilizing the proposed method. The extracted values are consistent well with reference values. Furthermore, we apply the proposed method for extracting the dispersion characteristics of zebrafish eye. With the proposed method, OCT-based analysis of dispersion characteristics could be a powerful tool in clinical practice.

Computer-Aided Discrimination of Glaucoma Patients from Healthy Subjects Using the RETeval Portable Device.

Glaucoma is a chronic, progressive eye disease affecting the optic nerve, which may cause visual damage and blindness. In this study, we present a machine-learning investigation to classify patients with glaucoma (case group) with respect to normal participants (control group). We examined 172 eyes at the Ophthalmology Clinic of the "Elpis" General Hospital of Athens between October 2022 and September 2023. In addition, we investigated the glaucoma classification in terms of the following: (a) eye selection and (b) gender. Our methodology was based on the features extracted via two diagnostic optical systems: (i) conventional optical coherence tomography (OCT) and (ii) a modern RETeval portable device. The machine-learning approach comprised three different classifiers: the Bayesian, the Probabilistic Neural Network (PNN), and Support Vectors Machines (SVMs). For all cases examined, classification accuracy was found to be significantly higher when using the RETeval device with respect to the OCT system, as follows: 14.7% for all participants, 13.4% and 29.3% for eye selection (right and left, respectively), and 25.6% and 22.6% for gender (male and female, respectively). The most efficient classifier was found to be the SVM compared to the PNN and Bayesian classifiers. In summary, all aforementioned comparisons demonstrate that the RETeval device has the advantage over the OCT system for the classification of glaucoma patients by using the machine-learning approach.

Early inner plexiform layer thinning and retinal nerve fiber layer thickening in excitotoxic retinal injury using deep learning-assisted optical coherence tomography

Excitotoxicity from the impairment of glutamate uptake constitutes an important mechanism in neurodegenerative diseases such as Alzheimer’s, multiple sclerosis, and Parkinson's disease. Within the eye, excitotoxicity is thought to play a critical role in retinal ganglion cell death in glaucoma, diabetic retinopathy, retinal ischemia, and optic nerve injury, yet how excitotoxic injury impacts different retinal layers is not well understood. Here, we investigated the longitudinal effects of N-methyl-D-aspartate (NMDA)-induced excitotoxic retinal injury in a rat model using deep learning-assisted retinal layer thickness estimation. Before and after unilateral intravitreal NMDA injection in nine adult Long Evans rats, spectral-domain optical coherence tomography (OCT) was used to acquire volumetric retinal images in both eyes over 4 weeks. Ten retinal layers were automatically segmented from the OCT data using our deep learning-based algorithm. Retinal degeneration was evaluated using layer-specific retinal thickness changes at each time point (before, and at 3, 7, and 28 days after NMDA injection). Within the inner retina, our OCT results showed that retinal thinning occurred first in the inner plexiform layer at 3 days after NMDA injection, followed by the inner nuclear layer at 7 days post-injury. In contrast, the retinal nerve fiber layer exhibited an initial thickening 3 days after NMDA injection, followed by normalization and thinning up to 4 weeks post-injury. Our results demonstrated the pathological cascades of NMDA-induced neurotoxicity across different layers of the retina. The early inner plexiform layer thinning suggests early dendritic shrinkage, whereas the initial retinal nerve fiber layer thickening before subsequent normalization and thinning indicates early inflammation before axonal loss and cell death. These findings implicate the inner plexiform layer as an early imaging biomarker of excitotoxic retinal degeneration, whereas caution is warranted when interpreting the ganglion cell complex combining retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses in conventional OCT measures. Deep learning-assisted retinal layer segmentation and longitudinal OCT monitoring can help evaluate the different phases of retinal layer damage upon excitotoxicity.

Bond-selective full-field optical coherence tomography.

Optical coherence tomography (OCT) is a label-free, non-invasive 3D imaging tool widely used in both biological research and clinical diagnosis. Conventional OCT modalities can only visualize specimen tomography without chemical information. Here, we report a bond-selective full-field OCT (BS-FF-OCT), in which a pulsed mid-infrared laser is used to modulate the OCT signal through the photothermal effect, achieving label-free bond-selective 3D sectioned imaging of highly scattering samples. We first demonstrate BS-FF-OCT imaging of 1 µm PMMA beads embedded in agarose gel. Next, we show 3D hyperspectral imaging of up to 75 µm of polypropylene fiber mattress from a standard surgical mask. We then demonstrate BS-FF-OCT imaging on biological samples, including cancer cell spheroids and C. elegans. Using an alternative pulse timing configuration, we finally demonstrate the capability of BS-FF-OCT on imaging a highly scattering myelinated axons region in a mouse brain tissue slice.

Abstract 11731: Efficacy of a New Generation Fast-Pullback, High-Frequency Intracoronary Optical Coherence Tomography Imaging on the Reduction of Contrast Medium in Clinical Practice

Introduction: Intracoronary optical coherence tomography (OCT) is an imaging modality that uses near-infrared light to generate high-resolution images, and now plays an important role in research and clinical practice as it provides insights into vascular biology and diagnostic guidance for percutaneous intervention (PCI). An existing concern is that OCT imaging could increase the total amount of contrast media administered during the procedure, resulting in adverse outcomes such as impairment of renal function or worsening of heart failure in some patients. Aims: We sought to investigate whether a novel, fast-pullback, high-frequency OCT (HF-OCT) enables acquisitions with a reduced amount of contrast agents while retaining the same qualitative and quantitative lesion assessment to conventional OCT. Methods: This study is a single-center, prospective, observational study including 10 patients with stable coronary artery disease. A total of 28 individual coronary arteries were assessed by both fast-pullback HF-OCT and by conventional OCT. The fast-pullback, HF-OCT system consists of a 1.8-Fr Vis-Rx® Micro-Imaging Catheter and an HF-OCT Imaging console (Gentuity LLC, Sudbury, MA). Results: The contrast volume used in each OCT run for the HF-OCT system was significantly lower than for the conventional OCT system (5.0±0.0 vs. 7.8±0.7ml, P&lt;0.001). No significant difference was found in the median value of the clear image length between the 2 OCT systems (74 mm [IQR; 63, 81], 74 mm [IQR; 71, 75], P=0.89). Fast-pullback HF-OCT showed comparable measurements to conventional OCT, including minimum lumen area (3.27±1.53 vs. 3.21±1.53 mm2, P=0.27), proximal reference area (7.03±2.28 vs. 7.03±2.34 mm2, P=0.96), and distal reference area (5.93±1.96 vs. 6.03±2.02 mm2, P=0.23). Qualitative OCT findings were comparable between the fast-pullback HF-OCT runs and conventional OCT with respect to identifying lipid-rich plaques, calcifications, layered plaques, macrophages, and cholesterol crystals. Conclusions: With the fast pullback function of a novel HF-OCT imaging system, we acquired OCT images using a significantly lower amount of contrast volume while retaining a comparable qualitative and quantitative lesion assessment to conventional OCT.

Nondestructive volumetric optical analysis of corroded copper oxidation using 1700nm swept-source optical coherence microscopy.

This study presents a novel nondestructive analysis method for precise characterization of corroded copper oxidation using optical coherence microscopy (OCM). By exploiting the partial light transmission through metallic oxide layers, we employed a specialized OCM system with a wavelength of 1700nm and enhanced the analysis accuracy compared to conventional optical coherence tomography (OCT). The developed OCM system featured a numerical aperture (NA) of 0.15, providing improved surface profiling and higher lateral resolution than OCT. we developed a peak-finding algorithm to accurately determine the thickness of the copper oxide layer from the acquired interference data with zero padding. Our method was validated by comparing the measured thickness profiles with those obtained from scanning electron microscope (SEM) images of corroded metals. The copper oxidation specimens were prepared after heat treatment for 1, 2, 4, and 8 h in an alumina tube furnace at a temperature of 900 °C to find the correlation between the OCM thickness measurement. Additionally, the acquired enface 3D images enabled the identification of local corrosion distribution within a 4 mm × 4 mm area. The en-face mapping images are utilized to analyze the uniformity of the metal oxidation process across the imaging area of the copper oxidation specimens. With an increase in heat treatment time, the median value of the thickness histogram for the copper oxide within the area consistently remained around 10 µm. However, the thickness variation ranged from -2 µm to 5 µm. This indicates that as the heat treatment time progresses, the thickness of the copper oxide becomes more non-uniform. Our technique holds great potential for nondestructive and noncontact detection of metal corrosion and assessment of corrosion rates in various industrial applications. Future research efforts could focus on expanding the application of OCM to different metals and exploring its commercialization prospects for practical implementation in diverse industries.

Optical beam scanner with reconfigurable non-mechanical control of beam position, angle, and focus for low-cost whole-eye OCT imaging.

Whole-eye optical coherence tomography (OCT) imaging is a promising tool in ocular biometry for cataract surgery planning, glaucoma diagnostics and myopia progression studies. However, conventional OCT systems are set up to perform either anterior or posterior eye segment scans and cannot easily switch between the two scan configurations without adding or exchanging optical components to account for the refraction of the eye's optics. Even in state-of-the-art whole-eye OCT systems, the scan configurations are pre-selected and cannot be dynamically reconfigured. In this work, we present the design, optimization and experimental validation of a reconfigurable and low-cost optical beam scanner based on three electro-tunable lenses, capable of non-mechanically controlling the beam position, angle and focus. We derive the analytical theory behind its control. We demonstrate its use in performing alternate anterior and posterior segment imaging by seamlessly switching between a telecentric focused beam scan to an angular collimated beam scan. We characterize the corresponding beam profiles and record whole-eye OCT images in a model eye and in an ex vivo rabbit eye, observing features comparable to those obtained with conventional anterior and posterior OCT scanners. The proposed beam scanner reduces the complexity and cost of other whole-eye scanners and is well suited for 2-D ocular biometry. Additionally, with the added versatility of seamless scan reconfiguration, its use can be easily expanded to other ophthalmic applications and beyond.

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

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

Automated robot-assisted wide-field optical coherence tomography using structured light camera.

Optical coherence tomography (OCT) is a promising real-time and non-invasive imaging technology widely utilized in biomedical and material inspection domains. However, limited field of view (FOV) in conventional OCT systems hampers their broader applicability. Here, we propose an automated system integrating a structured light camera and robotic arm for large-area OCT scanning. The system precisely detects tissue contours, automates scan path generation, and enables accurate scanning of expansive sample areas. The proposed system consists of a robotic arm, a three-dimensional (3D) structured light camera, and a customized portable OCT probe. The 3D structured light camera is employed to generate a precise 3D point cloud of the sample surface, enabling automatic planning of the scanning path for the robotic arm. Meanwhile, the OCT probe is mounted on the robotic arm, facilitating scanning of the sample along the predetermined path. Continuous OCT B-scans are acquired during the scanning process, facilitating the generation of high-resolution and large-area 3D OCT reconstructions of the sample. We conducted position error tests and presented examples of 3D macroscopic imaging of different samples, such as ex vivo kidney, skin and leaf blade. The robotic arm can accurately reach the planned positions with an average absolute error of approximately 0.16 mm. The findings demonstrate that the proposed system enables the acquisition of 3D OCT images covering an area exceeding 20 cm2, indicating wide-ranging potential for utilization in diverse domains such as biomedical, industrial, and agricultural fields.

Feasibility of deep learning-based polarization-sensitive optical coherence tomography angiography for imaging cutaneous microvasculature.

Polarization-sensitive optical coherence tomography (PS-OCT) measures the polarization states of the backscattered light from tissue that can improve angiography based on conventional optical coherence tomography (OCT). We present a feasibility study on PS-OCT integrated with deep learning for PS-OCT angiography (PS-OCTA) imaging of human cutaneous microvasculature. Two neural networks were assessed for PS-OCTA, including the residual dense network (RDN), which previously showed superior performance for angiography with conventional OCT and the upgraded grouped RDN (GRDN). We also investigated different protocols to process the multiple signal channels provided by the Jones matrices from the PS-OCT system to achieve optimal PS-OCTA performance. The training and testing of the deep learning-based PS-OCTA were performed using PS-OCT scans collected from 18 skin locations comprising 16,600 B-scan pairs. The results demonstrated a moderately improved performance of GRDN over RDN, and of the use of the combined signal from the Jones matrix elements over the separate use of the elements, as well as a similar image quality to that provided by speckle decorrelation angiography. GRDN-based PS-OCTA also showed ∼2-3 times faster processing and improved mitigation of tissue motion as compared to speckle decorrelation angiography, and enabled fully automatic processing. Deep learning-based PS-OCTA can be used for imaging cutaneous microvasculature, which may enable easy adoption of PS-OCTA for preclinical and clinical applications.

Optical coherence tomography split-spectrum amplitude-decorrelation optoretinography.

This pilot study reports the development of optical coherence tomography (OCT) split-spectrum amplitude-decorrelation optoretinography (SSADOR) that measures spatially resolved photoreceptor response to light stimuli. Using spectrally multiplexed narrowband OCT, SSADOR improves sensitivity to microscopic changes without the need for cellular resolution or optical phase detection. Therefore, a large field of view (up to 3 × 1 mm2 demonstrated) using conventional OCT instrument design can be achieved, paving the way for clinical translation. SSADOR promises a fast, objective, and quantifiable functional biomarker for photoreceptor damage in the macula.

SNR-Net OCT: brighten and denoise low-light optical coherence tomography images via deep learning.

Low-light optical coherence tomography (OCT) images generated when using low input power, low-quantum-efficiency detection units, low exposure time, or facing high-reflective surfaces, have low bright and signal-to-noise rates (SNR), and restrict OCT technique and clinical applications. While low input power, low quantum efficiency, and low exposure time can help reduce the hardware requirements and accelerate imaging speed; high-reflective surfaces are unavoidable sometimes. Here we propose a deep-learning-based technique to brighten and denoise low-light OCT images, termed SNR-Net OCT. The proposed SNR-Net OCT deeply integrated a conventional OCT setup and a residual-dense-block U-Net generative adversarial network with channel-wise attention connections trained using a customized large speckle-free SNR-enhanced brighter OCT dataset. Results demonstrated that the proposed SNR-Net OCT can brighten low-light OCT images and remove the speckle noise effectively, with enhancing SNR and maintaining the tissue microstructures well. Moreover, compared to the hardware-based techniques, the proposed SNR-Net OCT can be of lower cost and better performance.

Endoscopic optical coherence tomography angiography using an externally driving catheter.

Endoscopic optical coherence tomography (OCT) is an imaging modality that enables cross-sectional subsurface imaging of tubular organs and cavities. Recently, endoscopic OCT angiography (OCTA) was successfully achieved in distal scanning systems using an internal-motor-driving catheter. In conventional OCT systems using externally driving catheters, the mechanical instability in the proximal actuation causes difficulties for differentiating capillaries in tissues. In this study, OCTA in an endoscopic OCT system using an external-motor-driving catheter was proposed. Blood vessels were visualized by using a high-stability inter-A-scan scheme and the spatiotemporal singular value decomposition algorithm. It is not limited by nonuniform rotation distortion caused by the catheter and physiological motion artifacts. Results show that microvasculature in a custom-made microfluidic phantom and the submucosal capillaries in the mouse rectum are successfully visualized. Furthermore, OCTA using a catheter with a small size (outer diameter less than 1 mm) makes it possible for early diagnosis of narrow lumens, such as pancreatic and bile duct cancers.