This PDF file contains the front matter associated with SPIE Proceedings Volume 12830, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Preliminary data obtained with PS-OCT through the eyes of hypertensives suggests a mechanistic connection between arterial health and hypertension. In this study we want to determine whether arterial health may be more predictive of negative clinical outcomes than hypertension and blood glucose. Patients with various stages of hypertension, diabetes and coronary artery disease were recruited from Fiona Stanley Hospital (Perth). They were subsequently imaged with PS-OCT. The data were analyzed for retinal vessel wall thickness and vessel wall birefringence. We demonstrated that the combination of blood vessel wall tissue structure and wall thickness, a recognized clinical biomarker (Afsharan et al, BOE, 2021), could diagnose hypertension and diabetes with high sensitivity and specificity. PS-OCT measurements can detect the smallest changes related to cardiovascular disease in the retina before the disease manifests itself clinically. The method is cheap, noninvasive and easy to apply, which makes it highly suitable for screening, especially in underserved communities.

Age-related Macular Degeneration (AMD) is a major cause of global blindness, affecting millions worldwide. Certain forms of AMD cause neovascularizations (NVs), which form retinal-choroidal anastomoses, disrupting healthy hemodynamics. Early detection and treatment are crucial for preserving vision. We employ a custom-built OCT imaging system to investigate these NVs in a VLDLR−/− knockout mouse model. This included imaging the mouse before, during, and after contrast agent injection, aiming to enhance our understanding of the NV hemodynamics. Doppler signal analysis techniques were employed to calculate flow velocities within individual NVs. Flow rates pre- and post-injection were determined based on these velocity measurements. Particle tracking was performed on two NVs for a comparative analysis with the Doppler velocity measurements. Both methods of measuring flow velocities showed good agreement post-contrast injection. The analysis of post-injection flow rates from the NVs revealed diverse behaviors. Some NVs exhibited stable flow rates over time, while others showed signs of instability with flow rates changing substantially or even changing flow direction at different time points. Additionally, it was observed at multiple time points that flow from certain NVs moved from the choroid to the retina at the same time that others displayed flow in the opposite direction. These observations suggest complex interactions between choroidal and retinal vascular networks in disease model eyes like AMD. Further characterization using contrast-enhanced Doppler OCT can improve our understanding of neovascular hemodynamics.

We demonstrate the first broadband light source based on spectral combination of four superluminescent diodes (SLEDs) in the cyan-to-green wavelength range, suitable for high-resolution, visible optical coherence tomography (OCT). Two integrated combined-SLED sources, each comprising two wavelength-shifted green SLEDs, are realized through micro-optical module integration. Each of those two combined-SLED sources is delivering a highly polarized output spectrum at a polarization-maintaining (PM) fiber. The output of the two PM fibers is then spectrally combined with a free-space, micro-optical combiner module to a common, single-mode fiber output with a broadband output spectrum having a 10dB wavelength range from 481nm to 519nm, a 3dB bandwidth of 32nm and a coherence length of 4.5 microns in air.

Dispersion compensation is an important topic in optical coherence tomography (OCT) since the system- and sample-induced dispersion can often blur the image and degrade the axial resolution. Common numerical compensation methods rely on manual selection of the parameters and there is no universally accepted standard to determine the dispersion-free state. In this work, we propose a method that can automatically compensate the dispersion using fractional Fourier transform (FrFT) and provide a new insight on defining the sharpness metric. We exploit the sparsity of the image in the FrFT domain and thus find the optimal order of FrFT by minimizing the corresponding L1-norm. The effectiveness and robustness of the proposed method is confirmed in both numerical simulation and human skin and retina experiments.

We propose a new method to evaluate coherence properties of wavelength-swept light sources for the optical coherence tomography. The method relies on the depth variation of the noise floor and allows to estimate long coherence length with a limited electrical bandwidth unlike the conventional sensitivity roll-off method. By fitting the theoretically predicted noise-floor variation to the experimental data, we have successfully obtained coherence lengths of 1.6, 0.51, and 0.15m for a microelectromechanically tunable vertical-cavity surface-emitting laser with the sweeping rates of 100, 200, and 400kHz, respectively. The coherence lengths are comparable with those obtained with the roll-off method when the coherence lengths are relatively short.

This work reports the application of smoothed pseudo Wigner-Ville distribution for optical signal processing in spectral domain optical coherence tomography. Although traditional Fourier Transform methods have been successful in generating Axial scans, they are limited in fully exploiting the resolution of data captured by N-pixel detectors due to the complex conjugate symmetry property, resulting in redundant information over N/2 number of the pixels. To overcome this limitation, our proposed approach leverages smoothed pseudo Wigner- Ville distribution for precise frequency analysis across N samples and incorporates Kaiser windows to achieve effective frequency smoothing. This technique enables the generation of Axial scans over N pixels instead of N/2 pixels. Experimental verification validates the efficacy of the proposed technique, demonstrating a twofold improvement in longitudinal spatial resolution compared to the conventional Fourier based method.

Defocus in OCT can be removed by computational refocusing but with certain limitations. We theoretically investigate the limitations of the computational refocusing for standard point-scanning OCT and spatially coherence full-field OCT (SC-FFOCT). The Nyquist limit of the image sampling and the confocality define the maximum correctable defocus (MCD). The Nyquist limit becomes non-effectual limit with reasonable oversampling to the optical lateral resolution. The confocality is the main limiting factor of MCD for point-scanning OCT, while the SC-FFOCT does not have this limitation. SC-FFOCT was found to have virtually infinitely large MCD and is particularly suitable for optical coherence microscopy.

In Optical Coherence Tomography (OCT), speckle noise significantly hampers image quality, affecting diagnostic accuracy. Current methods, including traditional filtering and deep learning techniques, have limitations in noise reduction and detail preservation. Addressing these challenges, this study introduces a novel denoising algorithm, Block-Matching Steered-Mixture of Experts with Multi-Model Inference and Autoencoder (BM-SMoE-AE). This method combines block-matched implementation of the SMoE algorithm with an enhanced autoencoder architecture, offering efficient speckle noise reduction while retaining critical image details. Our method stands out by providing improved edge definition and reduced processing time. Comparative analysis with existing denoising techniques demonstrates the superior performance of BM-SMoE-AE in maintaining image integrity and enhancing OCT image usability for medical diagnostics.

Endoscopic optical coherence tomography (OCT) is progressively used in endoluminal imaging because of its high scanning speed and near-cellular spatial resolution. Scanning of the endoscopic probe is implemented mechanically to achieve circumferential rotation and axial pullback. However, this scanning suffers from nonuniform rotational distortion (NURD) due to mechanical friction between the rotating probe and protecting sheath, irregular motor rotation, and so on. Correction of NURD is a prerequisite for endoscopic OCT imaging and its functional extensions, such as angiography and elastography. Previous work requires time-consuming feature tracking or cross-correlation calculations and thus sacrifices temporal resolution. In this work, we propose a cross-attention learning method for accelerating the NURD correction in endoscopic OCT. Our method is inspired by the recent success of the self-attention mechanism in natural language processing and computer vision. By leveraging its ability to model long-range dependencies, we can directly obtain the correlation between OCT A-lines at any distance, thus accelerating the NURD correction. We develop an end-to- end stacked cross-attention network and design three types of optimization constraints. We compare our method with two traditional feature-based methods and a CNN-based method, on two publicly-available endoscopic OCT datasets and a private dataset collected on our home-built endoscopic OCT system. Our method achieved a ~3 times speedup to real-time (26±3 fps), and superior correction performance.

Proper vascular structure and function is critical to maintain healthy tissue. Vascular dysfunction is a hallmark in a number of diseases including but not limited to Alzheimer’s disease, diabetes, hypertension, and the normal process of aging. It has become clear than an early biomarker for these disparate diseases is dysfunction in retinal vascular structure and function. There is a growing computational toolbox for the analysis of vascular networks yet there are few easy to use graphical-user-interfaces that bring these tools to mere biologists. Here we present a suite of graphical-user-interfaces for the tracing, curation, and analysis of retinal vascular networks from 3D imaging datasets. The goal of these tools is to provide the needed link between continual advances in computational analysis with easy to use graphical-user-interfaces that will allow ground-truth results. We present an analysis of optical coherence tomography angiography (OCTA) images acquired in mice in vivo.

About half of all cancer patients receive radiation therapy throughout their illness, thus it continues to be a vital component of cancer treatment. However, a significant number of these patients suffer from radiation-induced skin damage or acute radiation dermatitis (ARD). Severe discomfort, difficulties with everyday tasks, a general decline in quality of life, and occasionally the need to forgo required radiation therapy are all side effects of ARD that have an adverse effect on survival rates. Unfortunately, research on the causes of ARD and prospective therapeutic methods has been hampered by the absence of biomarkers to quantitatively assess early changes related to ARD. In order to identify low-grade ARD, this study will use optical coherence tomography (OCT) images coupled with images from traditional image intensity and novel features. Twenty-two patients had imaging twice weekly during radiation therapy, producing a total of 1487 pictures. Each case's severity was assessed by an experienced oncologist. The preliminary results of the research show that a deep learning approach achieved an 88% accuracy in distinguishing between normal skin and early ARD. These findings provide a promising foundation for further studies aimed at creating a quantitative assessment tool to improve the management of ARD.

Refractive errors, such as myopia and hyperopia, are a major cause of visual impairment worldwide. The genetic basis of refractive errors is becoming increasingly understood, and the zebrafish has emerged as a powerful model organism for studying these disorders. In this study, we present evidence that establishes a connection between the mammalian connexin-36 (Cx36) ortholog gjd2b/Cx35.1, a key component of electrical synapses in zebrafish, as well as connexin-27(Cx27.5), and the occurrence of refractive errors. We investigated the morphological and behavioral changes in adult zebrafish. To assess these changes, we utilized a custom-developed 1310nm optical coherence tomography system for analysis of the entire eye. This analysis revealed development of hyperopic shifts in Cx35.1 knockouts, primarily due to a reduction in eye axial length, while no refractive anomalies were observed in Cx27.5 knockouts.

In recent years, endoscopic optical coherence tomography (OCT) has garnered widespread attention for non-invasive advantages in achieving three-dimensional visualization of internal organ cavities. In early-stage lesions, microvascular alterations occur before morphological tissue changes. Therefore, utilizing endoscopic OCTA for the detection of superficial capillaries serves as an adjunctive method for early disease screening. About ten years ago, the advantages of high-speed and stable operation of distal motorized catheters enabled the realization of endoscopic OCTA. However, the internal micro-motors lead to a larger outer diameter of distal imaging catheters, which restricts their clinical applicability for monitoring diseases in narrow luminal structures. Consequently, proximal imaging catheters, with their smaller size, have found its wide application in the commercial arena. However, due to limitations in external motor speed and susceptibility to external vibrations, there were no reports of proximal imaging catheters achieving endoscopic OCTA for a long time. Recently, we proposed the MB-scan scheme to mitigate the impact of external motion artifacts and achieve endoscopic OCTA based on a proximal catheter. The Singular Value Decomposition (SVD) algorithm was employed to eliminate static tissue information and obtain en face OCTA images of the murine rectum. In this study, we proposed a fast endoscopic OCTA using proximal scanning catheter based on B-scan scheme and a customed image registration algorithm. Image registration based on the similarity between adjacent B-scan frames was utilized to reduce the impact of external motor vibrations and improve image quality. Based on the registered images at the same scanning position, the speckle variance (SVAR) algorithm was employed to calculate variation of OCT intensity signals. Finally, en face OCTA images were generated. Collecting data from the mouse rectum, endoscopic OCTA images were obtained from the registered data using the SVAR algorithm.

Cellular-resolution in vivo imaging of human corneal microstructures plays an important role in the diagnosis and management of corneal disorders. It can also help evaluate the disease progression and the treatment response to different therapies. In this study, a new approach, polarization-dependent optical coherence microscope (POCM), was implemented to non-invasively image the microstructures of the human cornea in vivo. The approach leveraged the polarization propriety of light as well as the self-interference between the corneal surface and underlying layers to achieve high-contrast imaging of the human cornea. POCM achieved volumetric (500 x 500 x 2048 voxels) imaging of corneal microstructures over a field of view 0.5 x 0.5mm² with a lateral resolution of ~2.2μm and a volume rate of 1Hz. While the system achieved a ~2.4μm axial resolution (in the cornea) with its standard reference arm, the self-interference approach enabled the highest axial resolution of 1.4μm enabled by the source and detector, making it possible to achieve high-contrast imaging of microstructures of the anterior cornea free of degradations from dispersion mismatch, eye motion, and corneal curvature.

Optical coherence tomography (OCT) has been widely used in ophthalmology with its micron-resolution, depth-resolving capability in imaging bio-tissues in vivo. Recently, deep learning methods are emerging to achieve axial super-resolution (SR) in OCT, aimed to reduce the cost of broad-band light source. However, all of those deep learning methods were developed based on real-valued networks, ignoring the phase information of complex-valued OCT image which contains structural information. In this study, we proposed a complex-valued enhanced deep super-resolution network (Cv-EDSR) to obtain OCT axial super-resolution. We validated the superior performance of Cv-EDSR over the traditional EDSR on two datasets (swine esophagus and human retina), and demonstrated three benefits of Cv-EDSR: a) Cv-EDSR generated more realistic SR images, b) Cv-EDSR achieved an improved quality of SR images, c) Cv-EDSR possessed a better generalization performance.

Dynamic optical coherence tomography (DOCT) is developed to evaluate the functional activities of wide spectrum of tissues. However, the relation between the DOCT signals and the intracellular motion is not fully identified yet. This unidentified relationship inhibits further dissemination of DOCT signals. In this study, we proposed a theoretical and numerical framework to understand DOCT. It includes the classification of intracellular motility, their mathematical modeling, and numerical simulation. We classified intracellular motilities into six types: active transport, passive transport, jiggling, floating of dissociated cells, migration, and flow. Then, the motilities were modeled by three physical models: flow, random ballistic and diffusion. The sample motion and it resulting time-sequential OCT images were numerically simulated. Two DOCT contrasts were computed from the OCT time-sequence: logarithmic intensity variance of OCT (LIV) and temporal variance of complex OCT signals (complex variance). We considered the random ballistic motions measured by two different probing wavelengths of 840nm and 1310nm. Tessellated pattern of low and high LIV was found in LIV images. The LIV and complex variance increase within the velocity range of 4.5 to 270nm/s, while it becomes almost constant for larger velocities. Additionally, we found that both LIV and complex variance are higher when shorter wavelength is considered. Using the proposed theoretical model, we can better understand the specific intracellular tissue activities that contribute to the high DOCT signal.

Lichen sclerosus (LS) is a chronic inflammatory skin condition that has a predilection for the anogenital skin in women. The true prevalence of vulvar LS is unknown, underdiagnosed, and underreported [1]. Studies have estimated LS affects up to 3% of postmenopausal women, with a rising incidence [2]. The disease also affects premenopausal women and children. Overall, this is an underserved condition and the related delay in diagnosis can have a profound burden on patients’ quality of life and health outcomes, leading to irreversible scarring, infection, vulvar architectural distortion, genitourinary complications, itch, and pain syndromes [3]. There is a limited understanding of disease pathogenesis and no FDA-approved treatment options, with current guidelines recommending lifelong treatment. In the context of Vulvar Lichen Sclerosus, Skin biopsies are considered the standard method for detecting LS. However, they have certain drawbacks, as they are invasive, particularly in the sensitive vulvar area, and can be time-consuming. Approximately 5% of women with LS eventually develop vulvar squamous cell carcinoma (SCC), and half of all vulvar cancers arise in the presence of LS [4]. Therefore, patients need frequent monitoring, often requiring additional biopsies to assess the development of SCC or its precursors in long-standing LS lesions. Given the challenges associated with diagnosing VLS and monitoring SCC development in the context of an inflammatory skin condition, there is a high demand for noninvasive, high-sensitivity, real-time imaging techniques that can be performed in vivo. Hence, our study involves the design and development of a 1.7-μm optical coherence tomography angiography (OCTA) technique for diagnosing and monitoring of VLS lesions.

Optical coherence tomography (OCT) is a non-invasive, label-free, depth-resolved imaging and diagnostic technique with eclectic applications in medical and industrial domains. The typical resolution of structural changes detected by conventional depth-resolved OCT technique is about 1 to 15μm. Detection of nanoscale structural changes of biological tissues, aids in functional imaging of pathological processes which is not possible to detect using conventional intensity based OCT technique. The detection of biological tissues in nanoscale order is addressed in this work, using a SLED source of centre wavelength 930nm, a bandwidth of 102nm and a wavelength range of 874nm to 1027nm. This method helps in retaining high spatial frequency information and visualizing the structural changes occurring in biological tissues with spatial periods between 291nm to 343nm, without the need for excision as in the case of histological examination of morphological changes in the ultra-structures of biological tissues. A difference of 5 to 10nm in the spatial periods of biological structures were clearly observed from the nanosensitive OCT (nsOCT) results of in vivo nail and finger tissues.

A strong roll-off performance in Optical Coherence Tomography (OCT) is essential for imaging the inner ear, as it enables better depth resolution and penetration into the delicate structures within the temporal bone. This ensures higher-quality images and improved visualization of inner ear pathologies, thereby rendering OCT a valuable non-invasive tool for accurate diagnosis and assessment of inner ear conditions. In this work, we propose a spectral-domain OCT design that incorporates a frequency comb light source to enhance the penetration depth through improved roll-off performance. A broadband (~87nm at 3dB) comb source was developed centered near 1300nm, producing ~1000 lines spaced by a constant dk (~0.83cm^-1), which were coupled into a Mach-Zehnder interferometer and then detected by a spectrometer. Our initial results demonstrate an >80% improvement in 3-dB roll-off compared to the same system without the comb, i.e., with a broadband light source as used in the classical SD-OCT design.

Optical coherence tomography (OCT) has been shown to provide detailed images of the morphology and vibratory response in the living cochlea. As a part of the cochlea, the organ of Corti (OC) has a complex tissue structure including three rows of outer hair cells which act to amplify sound, supporting cells and one row of inner hair cells which transduce sound-induced vibrations into electrical signals. Unfortunately, OCT images of the OC have relatively low contrast, in spite of the fact that the microstructures have very different function and morphology. That fact has led us to explore alternative approaches to extracting contrast from these OCT images. In this paper, we propose a contrast-enhanced method based on spatial frequency to identify structures within the cochlea, including the OC. In total, 15 mice have been imaged with our customed OCT system and analyzed. A two-dimension spatial frequency analysis was performed over subregions of the images, using a sliding window. Then the power spectral density was fit to a 2-D Gaussian. Finally, we extracted several Gaussian fitting coefficients and constructed a coefficients map to enhance the visualization of the cochlea and identify structures within the OC. This method improves our ability to identify specific microstructures within the cochlea and ultimately map the functional vibratory response to these microstructures. Application of this approach can elucidate the micromechanical function of the cochlea.

Colorectal cancer (CRC) is one of the top causes of malignancy in both men and women. Although screening has significantly reduced CRC mortality, colonoscopy suffers from inadequate inspection and sampling of the tissue, a limitation that could be addressed by Optical Coherence Tomography (OCT). However, thus far, most studies have concentrated on the qualitative evaluation of morphological features and, only recently, the automatic classification of OCT images is being explored. To improve the classification of human tissues, manual or automatic, the spectral information in the OCT interferogram can be exploited. It can provide additional information regarding disease-related absorption and/or scattering changes in the tissue. In this study, we propose the use of multi-spectral analysis of OCT images, i.e. the utilization of images created from different bands of the available spectrum, to classify human colon polyps as normal or abnormal. Multiple, narrow-band, images, at different center wavelengths, were combined to create a “spectral score” for each pixel of the image. This fusion of information allowed both easier visual evaluation of the images as well as automatic classification (80 % accuracy per patient with leave-one-patient-out cross-validation). The proposed approach must be expanded to include more polyps and explore more sophisticated multi-spectral deep learning methods to improve its accuracy. However, these preliminary results provide evidence that this method has the potential to improve the accuracy of OCT and, in the future, enable clinical applications for colon cancer diagnosis.

Systemic sclerosis (SSc) is a complex autoimmune disease characterized by skin and internal organ fibrosis, with vascular dysfunction playing a critical role in its pathogenesis. This study utilizes optical coherence tomography angiography (OCTA) to explore vascular abnormalities in SSc patients. We imaged 26 SSc patients and 17 age- and sex-matched healthy volunteers. High-resolution OCTA images of the forearm, hand, finger, and nailbed skin vasculature were obtained using a swept-source OCT system, with a central wavelength of 1300 nm, a scan range of 108 nm, a scan rate of 100 kHz. Post-processing was achieved using Matlab and QuPath, where a Hessian filter-based approach was utilized to enhance blood vessel contrast and connectivity in 2D projections. These tools were also employed for vessel lumen width (VLW) calculation, with group comparisons made using Mann-Whitney U-test. The results showed a significant decrease in VLW in SSc patients compared to healthy controls across all imaged regions (p<0.001 for all locations: finger, hand, forearm, and nailbed). These findings suggest that OCTA is a valuable tool for detecting and quantifying vascular abnormalities in SSc skin, potentially offering new insights for disease management.

Magnetic Resonance Imaging and x-ray Computed Tomography have limitations when applied to diseases of the human inner ear due to insufficient resolution. Key morphological features of the inner ear are below the resolving power of both modalities; thus, they are unable to measure functional aspects of the microstructures in the cochlea. Furthermore, general access to the cochlea is a challenge due to its location in the inner ear and its bony encapsulation. These limitations cause clinicians to rely on clinical history when diagnosing and managing hearing loss in patients, which is not ideal. This paper explores the application of Optical Coherence Tomography (OCT) as a diagnostic tool for inner ear diseases. OCT’s high spatial and temporal resolution allows for detailed imaging of inner ear structures and their function. To address the challenge of accessing the cochlea in humans, a hand-held endoscopic OCT device has been developed that can image through the round window membrane. The technology has been tested in cadaver temporal bone, enabling functional and morphological imaging of the cochlea when navigated to the round window. Alongside the device, we are developing an algorithm to perform subsequent stitching of volumes to overcome limitations with a small field of view. Applying this algorithm on cadaver tissue serves as a preliminary step before advancing to live human cochlear imaging. By utilizing our hand-held OCT endoscope, clinicians will have the ability to record changes in morphological and functional information, thereby improving the approach to diagnosing and treating patients with inner ear diseases.

Optical coherence tomography (OCT) of the human cochlea has potential to reveal pathophysiological details of hearing disorders and cochlear function via vibrometry and angiography. However, the ability of 1.3μm OCT to image the detailed microanatomy inside the cochlea is limited by light scattering in the tympanic membrane and otic capsule. Since light scattering in biological tissues is reduced at longer wavelengths, we investigated the use of a 1.7μm swept-source laser for OCT imaging of an ex-vivo human cochlea to compare with 1.3μm OCT imaging. We found that 1.7μm OCT could provide sharper details and greater contrast inside the cochlea compared to 1.3μm OCT due to reduced multiple scattering from the bony otic capsule. These results support the continued development of 1.7μm OCT for cochlear imaging.

In this study we demonstrated the effectiveness of dynamic light scattering (DLS) in enhancing the resolution of optical coherence tomography (OCT) images of static samples. By carefully analyzing the movement of particles within the sample, utilizing the autocorrelation function of the backscattered light and performing averaging of OCT images captured at different time points, we were able to effectively suppress spatial coherence and achieve improved transverse resolution in the images. Additionally, this technique holds the potential for providing valuable insights into the internal movements of biological samples, such as blood flow. To validate our method, we conducted experiments using an OCT system and introduced scatterers exhibiting random Brownian motion. The enhanced spatial resolution was clearly demonstrated through the visualization of cross-sections of bars and the analysis of B-scans. Our findings pave the way for further advancements in OCT imaging techniques and offer promising applications in the study of static biological samples.

Dynamic optical coherence tomography (DOCT) is a method to visualize intratissue activities by analyzing the time sequence of OCT images. We previously established two DOCT contrasts, logarithmic intensity variance (LIV) and late OCT correlation decay speed (OCDS_l), and applied them to several medical and pharmaceutical studies. However, these DOCT contrasts have two problems, which are a measurement time dependency of LIV and a difficulty of interpretation of OCDS_l. Here we present a new DOCT algorithm which solves these two problems. The new method first computes several LIV values with multiple time window sizes. This LIV shows a monotonically increasing saturation curve. The saturation level and saturation speed, which are named authentic LIV (ALIV) and swiftness, are obtained by fitting the LIVs with a saturation function. Numerical simulation revealed that ALIV is sensitive to the occupancy of the dynamic scatterers over all dynamic and static scatterers, while swiftness is sensitive to the speed of the dynamic scatterers. According to the principle and experimental results using tumor spheroids, ALIV and swiftness are more quantitative and easier to interpret than our previous DOCT methods.

Ocular aberrometry with a wide dynamic range for assessing vision performance and anterior segment imaging that provides anatomical details of the eye are both essential for vision research and clinical applications. Defocus error is a major limitation of digital wavefront aberrometry (DWA) as the blurring of the detected point spread function (PSF) results in a significant reduction of SNR beyond ±3 D range. With the aid of Badal-like precompensation of defocus, the dynamic defocus range of the captured aberrated PSFs can be effectively extended. We demonstrate a dual-modality MHz VCSEL-based swept-source OCT (SS-OCT) system, with an easy switch between DWA and OCT imaging mode. The system is capable of measuring aberrations with defocus dynamic range of D as well as providing fast anatomical imaging of the anterior segment at an A-scan rate of 1.6 MHz. The dual-mode system stands out for its modular design wherein simple hardware additions to an SS-OCT system enable the aberration measurement in DWA mode. In DWA mode, a diffraction-limited stationary spot is formed at the retina by a narrow illumination beam. The reflected light passes then through the full pupil of the eye, thereby the single path optical aberrations are captured. The OCT detection leads to volumetric PSFs, which are post-processed using the digital lateral shearing-based digital adaptive optics technique (DLS-DAO) to reconstruct the wavefront error. Capturing both optical and anatomical information of the eye can be potentially helpful for improved diagnosis and targeted treatment of ocular diseases.

High-resolution optical imaging is accompanied by a limited depth of field, making it challenging to obtain non-stitched, high-resolution images of samples with uneven surfaces without performing Z-axis scanning. To solve this problem, we introduced diffractive optical elements into the conventional OCT system and develop a needle-shaped beam OCT system with both long DOF and high resolution, which maintains 8μm lateral resolution over a depth range of 620μm. The system was then employed to perform a 10-day cortical blood perfusion observation after stroke, providing visual and mechanistic insight into stroke, deepening our understanding of the brain response after stroke.

Accurate measurement of the microcirculation dynamics, including the blood vessel 3D structure, blood flow velocity and the blood flow transit time can not only improve our understanding of the pathology of microcirculation dysfunction-related disease, but also provide important parameters for disease diagnosis, prevention, and early treatment. In this work, we introduce a comprehensive optical coherence tomography (OCT)-based functional imaging technology for the 3D measurement of the micro vessel networks’ structure, blood flow velocity, and the blood flow transit time. The M-mode data acquisition (repeated A-scans) was employed in this technique. For blood vessel 3D structure imaging, we developed a first order field autocorrelation function (g1)-based adaptive analysis method to suppress the blood vessel tail artifacts and enhance the blood flow in small vessels. For blood flow velocity 3D imaging, we developed a set of quantitative dynamic analysis methods to measure both the axial and total blood flow velocity of the complex vessel network. We further developed a graphing method to obtain the 3D topological parameters of the 3D vessel network, including the vessel skeleton, branching, vessel diameter, and the blood flow speed at each location. With those information, we are able to, to the best of our knowledge, obtain the 3D blood transit time in the complex vessel network for the first of time. The proposed technique has the advantage of obtaining these three important blood flow biomarkers from a single data acquisition, which greatly simplifies the experiment procedure. The proposed OCT approach has a wide application in the field of microcirculation dysfunction-related disease studies.

Despite improvements in the ability to treat cancer, first-line chemotherapy in standard-of-care treatments still fail to elicit a response from about half of cancer patients. This limitation signals a pressing need for practical methods to select personalized cancer therapies. Biodynamic imaging (BDI; a form of dynamic-contrast OCT with low-coherence digital holography) on living cancer biopsies from patients shows potential as a method to guide personalized selection of cancer therapy. However, building a library of signatures for different types of cancer has been a practical obstacle. Here, a comparative preclinical/clinical trial with two-species (human and canine) and two-cancers (esophageal carcinoma and B-cell lymphoma) demonstrates the general applicability of BDI as a method of chemoresistance prediction and as a viable tool for personalized medicine. This study identifies a set of drug response phenotypes that span species and cancer type, suggesting the existence of universal characteristics, which would reduce the burden of library construction needed for the method to be useful for doctors and their patients.

Many embryonic developmental processes are inherently mechanical, such as elongation, neural tube closure, and cardiogenesis. Any disruption or failure of these events can lead to debilitating or even fatal pathologies, e.g., anencephaly. While much is known about the genetic and molecular mechanisms underlying these processes, there remains a significant knowledge gap about the associated biomechanical parameters due to the lack of noninvasive high-resolution mechanical imaging techniques, particularly in live samples. In this work, we demonstrate completely noninvasive, label-free, high-resolution, and three-dimensional mapping of mouse embryo stiffness at several critical stages of embryogenesis based on reverberant shear wave optical coherence elastography (Rev-OCE). Mouse embryos at various developmental stages (embryonic day 9.5, 10.0, 10.5, 11.0, and 11.5) were dissected out and placed on an optical window during imaging. The samples were encompassed in embryo culture media to preserve the integrity of the delicate embryo tissues. The optical window was attached to a piezoelectric bender, which vibrated the optical window at 1kHz. M-C-mode imaging was performed with a phase-sensitive spectral domain OCT system operating in the common-path configuration. Standard reverberant OCE processing steps were applied, and the local autocorrelation was fitted to the analytical solution of the reverberant shear field. The local shear wave speed was then mapped in 3D. The results show that the stiffness of the spine, heart, and brain all increased as the embryo developed.

We report dynamic optical coherence tomography (D-OCT) images of the organ of Corti (ooC) in ex vivo mouse cochleas. The ooC is responsible for transducing sound-evoked mechanical vibrations and amplifying them in the process of hearing. Thorough knowledge of the micromechanical properties of the ooC is required for understanding how hearing functions. Recently, OCT has emerged as a safe and effective tool to probe the inner workings of the cochlea and ooC. However, OCT is limited in its ability to directly resolve cellular architecture due to limited optical scattering-based contrast between different cell types. D-OCT is a label-free method capable of probing sub-resolution movements by analyzing speckle and phase information from standard OCT data as a function of time. We show that key structures in the ooC can be identified with D-OCT versus standard OCT, and that D-OCT has the potential to characterize the ooC and advance our understanding of the process of hearing.

Dynamic optical coherence tomography (DOCT) is a label-free technique that visualizes tissue dynamics by analyzing a long-time sequence of OCT images. Although it was successful for in vitro and ex vivo imaging, it is still challenging for in vivo imaging because of the sample motion. We address this issue by developing hardware- and software-based motion suppression methods and demonstrating in vivo DOCT imaging of human skin. The hardware method is a sample fixation spacer. The software method is an image-registration based motion correction. We used logarithmic intensity variance (LIV) method to image the tissue dynamics. LIV was calculated from 32 sequential OCT frames taken within a 6.35s time window. The interframe time interval was 204.8ms and the entire DOCT volume was measured in 52.4s. Furthermore, we measured OCT angiography (OCTA) by standard raster scan with four frame repeats. To quantitively analyzing the improvement of proposed methods, three regions of interests (ROIs), each measuring 176μm (in depth) × 217μm (in lateral direction), was select from one B-scan to calculate the mean LIV. The improvement was assessed by paired t-test. The motion correction methods significantly reduced the high-LIV artifacts and revealed very fine capillary structures that had been buried by motion artefacts. The paired t-test results showed that the combination of fixation spacer and the software correction significantly reduced LIV artifacts (p=0.0052, 0.0137 and 0.0068 for three ROIs).

In the presence of strong reflecting surfaces, the detector in SS-OCT may saturate, leading to loss of information within affected A-scans and potentially disturbing axial artifacts in affected B-scans or volumes. In this work, we trained an image-based neural network to detect and remove such artifacts and restore the underlying structure by means of image inpainting. For this purpose, sets of paired images were generated from raw OCT spectra, with one image intact and the other suffering from simulated detector saturation. We demonstrate the effectiveness of the proposed method qualitatively and quantitatively.

We present a neural network able to fully linearise an OCT image without any a priori knowledge about the spectrometer characteristics or the extent of dispersion in the interferometer and the object. Unlike the earlier solutions, this blind line-arisation is not biased towards a specific object, nor its dispersion characteristics, and in the future can be made independent of the light source parameters.