Optical coherence tomography

Dynamics of drying colloidal suspensions, measured by optical coherence tomography

Colloidal suspensions are the basis of a wide variety of coatings, prepared as liquids and then dried into solid films. The processes at play during film formation, however, are difficult to observe directly. Here, we demonstrate that optical coherence tomography (OCT) can provide fast, non-contact, precise profiling of the dynamics within a drying suspension. Using a scanning Michelson interferometer with a broadband laser source, OCT creates cross-sectional images of the optical stratigraphy of a sample. With this method, we observed the drying of colloidal silica in Hele-Shaw cells with 10 μm transverse and 1.8 μm depth resolution, over a 1 cm scan line and a 15 s sampling period. The resulting images were calibrated to show how the concentration of colloidal particles varied with position and drying time. This gives access to important transport properties, for example, of how collective diffusion depends on particle concentration. Looking at early-time behaviours, we also show how a drying front initially develops, and how the induction time before the appearance of a solid film depends on the balance of diffusion and evaporation-driven motion. Pairing these results with optical microscopy and particle tracking techniques, we find that film formation can be significantly delayed by any density-driven circulation occurring near the drying front.

Dynamic contrast optical coherence tomography (DyC-OCT) for label-free live cell imaging

Dynamic contrast optical coherence tomography (DyC-OCT), an emerging imaging method, utilizes fluctuation patterns in OCT signals to enhance contrast, thereby enabling non-invasive label-free volumetric live cell imaging. In this mini review, we explain the core concepts behind DyC-OCT image formation and its system configurations, serving as practical guidance for future DyC-OCT users. Subsequently, we explore its applications in delivering high-quality, contrast-enhanced images of cellular morphology, as well as in monitoring changes in cellular activity/viability assay experiments.

Coherent light scattering from cellular dynamics in living tissues

This review examines the biological physics of intracellular transport probed by the coherent optics of dynamic light scattering from optically thick living tissues. Cells and their constituents are in constant motion, composed of a broad range of speeds spanning many orders of magnitude that reflect the wide array of functions and mechanisms that maintain cellular health. From the organelle scale of tens of nanometers and upward in size, the motion inside living tissue is actively driven rather than thermal, propelled by the hydrolysis of bioenergetic molecules and the forces of molecular motors. Active transport can mimic the random walks of thermal Brownian motion, but mean-squared displacements are far from thermal equilibrium and can display anomalous diffusion through Lévy or fractional Brownian walks. Despite the average isotropic three-dimensional environment of cells and tissues, active cellular or intracellular transport of single light-scattering objects is often pseudo-one-dimensional, for instance as organelle displacement persists along cytoskeletal tracks or as membranes displace along the normal to cell surfaces, albeit isotropically oriented in three dimensions. Coherent light scattering is a natural tool to characterize such tissue dynamics because persistent directed transport induces Doppler shifts in the scattered light. The many frequency-shifted partial waves from the complex and dynamic media interfere to produce dynamic speckle that reveals tissue-scale processes through speckle contrast imaging and fluctuation spectroscopy. Low-coherence interferometry, dynamic optical coherence tomography, diffusing-wave spectroscopy, diffuse-correlation spectroscopy, differential dynamic microscopy and digital holography offer coherent detection methods that shed light on intracellular processes. In health-care applications, altered states of cellular health and disease display altered cellular motions that imprint on the statistical fluctuations of the scattered light. For instance, the efficacy of medical therapeutics can be monitored by measuring the changes they induce in the Doppler spectra of livingex vivocancer biopsies.

Glaucoma detection model by exploiting multi-region and multi-scan-pattern OCT images with dynamical region score

Currently, deep learning-based methods have achieved success in glaucoma detection. However, most models focus on OCT images captured by a single scan pattern within a given region, holding the high risk of the omission of valuable features in the remaining regions or scan patterns. Therefore, we proposed a multi-region and multi-scan-pattern fusion model to address this issue. Our proposed model exploits comprehensive OCT images from three fundus anatomical regions (macular, middle, and optic nerve head regions) being captured by four scan patterns (radial, volume, single-line, and circular scan patterns). Moreover, to enhance the efficacy of integrating features across various scan patterns within a region and multiple regional features, we employed an attention multi-scan fusion module and an attention multi-region fusion module that auto-assign contribution to distinct scan-pattern features and region features adapting to characters of different samples, respectively. To alleviate the absence of available datasets, we have collected a specific dataset (MRMSG-OCT) comprising OCT images captured by four scan patterns from three regions. The experimental results and visualized feature maps both demonstrate that our proposed model achieves superior performance against the single scan-pattern models and single region-based models. Moreover, compared with the average fusion strategy, our proposed fusion modules yield superior performance, particularly reversing the performance degradation observed in some models relying on fixed weights, validating the efficacy of the proposed dynamic region scores adapted to different samples. Moreover, the derived region contribution scores enhance the interpretability of the model and offer an overview of the model's decision-making process, assisting ophthalmologists in prioritizing regions with heightened scores and increasing efficiency in clinical practice.

Long-range optical coherence tomography of pediatric airway during drug induced sleep endoscopy: A preliminary report

OBJECTIVE

Drug induced sleep endoscopy (DISE) is often performed for pediatric obstructive sleep apnea (OSA) when initial diagnostic studies do not provide adequate information for therapy. However, DISE scoring is subjective and with limitations. This proof-of-concept study demonstrates the use of a novel long-range optical coherence tomography (LR-OCT) system during DISE of two pediatric patients.

METHODS

LR-OCT was used to visualize the airway of pediatric patients during DISE. At the conclusion of DISE, the OCT probe was guided in the airway under endoscopic visual guidance, and cross-sectional images were acquired at the four VOTE locations. Data processing involved image resizing and alignment, followed by rendering of three-dimensional (3D) volumetric models of the airways.

RESULTS

Two patients were included in this study. Patient one had 18.4%, 20.9%, 72.3%, and 97.3% maximal obstruction at velum, oropharynx, tongue base, and epiglottis, while patient two had 40.2%, 41.4%, 8.0%, and 17.5% maximal obstruction at these regions, respectively. Three-dimensional reconstructions of patients' airways were also constructed from the OCT images.

CONCLUSION

This proof-of-concept study demonstrates the successful evaluation of pediatric airway during DISE using LR-OCT, which accurately identified sites and degrees of obstruction with respective 3D airway reconstruction.

Assessing cell viability with dynamic optical coherence microscopy

Assessing cell viability is important in many fields of research. Current optical methods to assess cell viability typically involve fluorescent dyes, which are often less reliable and have poor permeability in primary tissues. Dynamic optical coherence microscopy (dOCM) is an emerging tool that provides label-free contrast reflecting changes in cellular metabolism. In this work, we compare the live contrast obtained from dOCM to viability dyes, and for the first time to our knowledge, demonstrate that dOCM can distinguish live cells from dead cells in murine syngeneic tumors. We further demonstrate a strong correlation between dOCM live contrast and optical redox ratio by metabolic imaging in primary mouse liver tissue. The dOCM technique opens a new avenue to apply label-free imaging to assess the effects of immuno-oncology agents, targeted therapies, chemotherapy, and cell therapies using live tumor tissues.

Contemporary Mechanics of Conductive Hearing Loss

The middle ear plays a critical role for the conversion of acoustic energy to mechanical vibrations that subsequently enter the cochlea. It is middle ear impedance matching through ossicular coupling that has enabled land-dwelling vertebrates to hear soft airborne sounds. Conductive hearing loss may result from damage to the delicate middle ear structures following infection, trauma or rapid pressure changes. An understanding of the mechanics of the middle ear significantly improves the oto-surgeon's ability to effectively diagnose conductive hearing loss, localize the responsible lesion and then effectively correct the conduction abnormality. This article reviews some of the basic knowledge of middle ear mechanics for sound transmission, highlights recent advances in developing new techniques to assist in diagnosis of middle ear disease, and finally sheds light on future research aimed at improving the diagnosis and management of middle ear pathology.

Self-attention CNN for retinal layer segmentation in OCT

The structure of the retinal layers provides valuable diagnostic information for many ophthalmic diseases. Optical coherence tomography (OCT) obtains cross-sectional images of the retina, which reveals information about the retinal layers. The U-net based approaches are prominent in retinal layering methods, which are usually beneficial to local characteristics but not good at obtaining long-distance dependence for contextual information. Furthermore, the morphology of retinal layers with the disease is more complex, which brings more significant challenges to the task of retinal layer segmentation. We propose a U-shaped network combining an encoder-decoder architecture and self-attention mechanisms. In response to the characteristics of retinal OCT cross-sectional images, a self-attentive module in the vertical direction is added to the bottom of the U-shaped network, and an attention mechanism is also added in skip connection and up-sampling to enhance essential features. In this method, the transformer's self-attentive mechanism obtains the global field of perception, thus providing the missing context information for convolutions, and the convolutional neural network also efficiently extracts local features, compensating the local details the transformer ignores. The experiment results showed that our method is accurate and better than other methods for segmentation of the retinal layers, with the average Dice scores of 0.871 and 0.820, respectively, on two public retinal OCT image datasets. To perform the layer segmentation of retinal OCT image better, the proposed method incorporates the transformer's self-attention mechanism in a U-shaped network, which is helpful for ophthalmic disease diagnosis.

Artifacts in OCT Retinal Nerve Fiber Layer Imaging in Patients with Boston Keratoprosthesis Type 1

PURPOSE

To determine the clinical utility of OCT retinal nerve fiber layer (OCT RNFL) imaging for glaucoma evaluation in patients with Boston keratoprosthesis type 1 (KPro) by investigating imaging artifacts.

DESIGN

Case-control study.

SUBJECTS

Patients with KPro and without KPro (controls) matched for age, gender, and glaucoma diagnosis.

METHODS

The most recent Cirrus OCT RNFL scan from 1 eye was categorized as having good signal strength (SS; ≥ 6 out of 10) or poor SS (< 6). Those with good SS were analyzed by 2 independent reviewers for artifacts. Images with good SS and no artifacts affecting the scanning circle were considered useful for glaucoma evaluation.

MAIN OUTCOME MEASURES

The incidence of poor SS and artifacts in OCT RNFL images; patient characteristics associated with useful scans.

RESULTS

Sixty-five patients with KPro and 75 controls were included; 89.2% of KPro patients and 89.3% of control subjects had glaucoma (P = 0.98). Forty percent of KPro patients and 5.3% of controls had poor SS (P < 0.001). The proportion of images with either poor SS or artifacts was similar in KPro (76.9%) vs. controls (72.0%, P = 0.51). The most common artifacts in both groups were missing data (43.6%, 53.2%, respectively, P = 0.32) and motion artifact (25.6%, 19.7%, respectively, P = 0.47). Images were useful for glaucoma evaluation in 43.1% of KPro patients and in 69.3% of controls (P = 0.002). In the KPro group, patients with useful OCT scans, compared with those without, had better visual acuity (0.4 ± 0.3 vs. 0.9 ± 0.7 logarithm of the minimum angle of resolution, P = 0.004), and did not have congenital corneal pathologies (0.0% vs. 24.3%, P = 0.008). A multivariate analysis showed that KPro patients with older age had higher odds of useful OCT images (odds ratio, 1.05; P = 0.03). Among KPro patients with useful OCT scans, retinal nerve fiber layer thickness correlated with observed cup-to-disc ratio (Pearson correlation: r = -0.42, P = 0.03).

CONCLUSIONS

The rate of OCT RNFL images with either poor signal strength or artifacts in the KPro and control population was comparable. In patients with KPro, where intraocular pressure measurements are difficult and glaucoma is highly prevalent and often severe, OCT RNFL imaging can be useful for glaucoma evaluation.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Retinal Thinning in Adults with Autism Spectrum Disorder

Since the retina shares its embryological origin with the central nervous system, optical coherence tomography (OCT), an imaging technique frequently employed in ophthalmology to analyze the macula and intraretinal layer thicknesses and volumes, has recently become increasingly important in psychiatric research. We examined 34 autistic and 31 neurotypical adults (NT) using OCT. Autistic adults had reduced overall macular and outer nuclear layer (ONL) thickness and volume compared to NT. Both macular and ONL thickness showed significant inverse associations with the severity of autistic symptoms measured with the Social Responsiveness Scale 2 (SRS-2). Longitudinal studies across different age groups are required to clarify whether retinal changes may represent a possible trait marker.

Advanced nanomaterials for imaging of eye diseases

Background and purpose

Vision impairment and blindness present significant global challenges, with common causes including age-related macular degeneration, diabetes, retinitis pigmentosa, and glaucoma. Advanced imaging tools, such as optical coherence tomography, fundus photography, photoacoustic microscopy, and fluorescence imaging, play a crucial role in improving therapeutic interventions and diagnostic methods. Contrast agents are often employed with these tools to enhance image clarity and signal detection. This review aims to explore the commonly used contrast agents in ocular disease imaging.

Experimental approach

The first section of the review delves into advanced ophthalmic imaging techniques, outlining their importance in addressing vision-related issues. The emphasis is on the efficacy of therapeutic interventions and diagnostic methods, establishing a foundation for the subsequent exploration of contrast agents.

Key results

This review focuses on the role of contrast agents, with a specific emphasis on gold nanoparticles, particularly gold nanorods. The discussion highlights how these contrast agents optimize imaging in ocular disease diagnosis and monitoring, emphasizing their unique properties that enhance signal detection and imaging precision.

Conclusion

The final section, we explores both organic and inorganic contrast agents and their applications in specific conditions such as choroidal neovascularization, retinal neovascularization, and stem cell tracking. The review concludes by addressing the limitations of current contrast agent usage and discussing potential future clinical applications. This comprehensive exploration contributes to advancing our understanding of contrast agents in ocular disease imaging and sets the stage for further research and development in the field.

Visual outcome measures in clinical trials of remyelinating drugs

One of the most promising approaches to delay, prevent or reverse disability progression in multiple sclerosis (MS) is to enhance endogenous remyelination and limit axonal degeneration. In clinical trials of remyelinating drugs, there is a need for reliable, sensitive and clinically relevant outcome measures. The visual pathway, which is frequently affected by MS, provides a unique model system to evaluate remyelination of acute and chronic MS lesions in vivo and non-invasively. In this review, we discuss the different measures that have been used and scrutinise visual outcome measure selection in current and future remyelination trials.

Digital image correlation-assisted phase-sensitive optical coherence tomography

In this Letter, we introduce a digital image correlation-assisted (DIC-assisted) method to tackle the challenges of phase decorrelation and the inability to measure lateral displacement in phase-sensitive optical coherence tomography (PhS-OCT). This DIC-assisted PhS-OCT (DIC-PhS-OCT) first employs DIC to track displacements from the measured amplitude spectra and subsequently uses these tracked displacements to correct supra-pixel displacement offsets in the measured phase spectra. As a result, it effectively mitigates phase decorrelation resulting from both axial and lateral displacements while enabling the acquisition of sub-pixel-level lateral displacements during the DIC computation. Our experiments demonstrate the effectiveness of DIC-PhS-OCT in addressing these challenges while retaining the ultrahigh sensitivity of conventional PhS-OCT.

Super-resolution of Retinal Optical Coherence Tomography Images Using Statistical Modeling

Background

Optical coherence tomography (OCT) imaging has emerged as a promising diagnostic tool, especially in ophthalmology. However, speckle noise and downsampling significantly degrade the quality of OCT images and hinder the development of OCT-assisted diagnostics. In this article, we address the super-resolution (SR) problem of retinal OCT images using a statistical modeling point of view.

Methods

In the first step, we utilized Weibull mixture model (WMM) as a comprehensive model to establish the specific features of the intensity distribution of retinal OCT data, such as asymmetry and heavy tailed. To fit the WMM to the low-resolution OCT images, expectation-maximization algorithm is used to estimate the parameters of the model. Then, to reduce the existing noise in the data, a combination of Gaussian transform and spatially constraint Gaussian mixture model is applied. Now, to super-resolve OCT images, the expected patch log-likelihood is used which is a patch-based algorithm with multivariate GMM prior assumption. It restores the high-resolution (HR) images with maximum a posteriori (MAP) estimator.

Results

The proposed method is compared with some well-known super-resolution algorithms visually and numerically. In terms of the mean-to-standard deviation ratio (MSR) and the equivalent number of looks, our method makes a great superiority compared to the other competitors.

Conclusion

The proposed method is simple and does not require any special preprocessing or measurements. The results illustrate that our method not only significantly suppresses the noise but also successfully reconstructs the image, leading to improved visual quality.

Recurrent and Concurrent Prediction of Longitudinal Progression of Stargardt Atrophy and Geographic Atrophy

Stargardt disease and age-related macular degeneration are the leading causes of blindness in the juvenile and geriatric populations, respectively. The formation of atrophic regions of the macula is a hallmark of the end-stages of both diseases. The progression of these diseases is tracked using various imaging modalities, two of the most common being fundus autofluorescence (FAF) imaging and spectral-domain optical coherence tomography (SD-OCT). This study seeks to investigate the use of longitudinal FAF and SD-OCT imaging (month 0, month 6, month 12, and month 18) data for the predictive modelling of future atrophy in Stargardt and geographic atrophy. To achieve such an objective, we develop a set of novel deep convolutional neural networks enhanced with recurrent network units for longitudinal prediction and concurrent learning of ensemble network units (termed ReConNet) which take advantage of improved retinal layer features beyond the mean intensity features. Using FAF images, the neural network presented in this paper achieved mean (± standard deviation, SD) and median Dice coefficients of 0.895 (± 0.086) and 0.922 for Stargardt atrophy, and 0.864 (± 0.113) and 0.893 for geographic atrophy. Using SD-OCT images for Stargardt atrophy, the neural network achieved mean and median Dice coefficients of 0.882 (± 0.101) and 0.906, respectively. When predicting only the interval growth of the atrophic lesions with FAF images, mean (± SD) and median Dice coefficients of 0.557 (± 0.094) and 0.559 were achieved for Stargardt atrophy, and 0.612 (± 0.089) and 0.601 for geographic atrophy. The prediction performance in OCT images is comparably good to that using FAF which opens a new, more efficient, and practical door in the assessment of atrophy progression for clinical trials and retina clinics, beyond widely used FAF. These results are highly encouraging for a high-performance interval growth prediction when more frequent or longer-term longitudinal data are available in our clinics. This is a pressing task for our next step in ongoing research.

In vivo dynamic volumetric imaging of mouse testis and epididymis with optical coherence tomography†

The implementation of live imaging in reproductive research is crucial for studying the physiological dynamics. Sperm transport is a highly dynamic process regulated by tubular contractions and luminal flows within the male reproductive tract. However, due to the lack of imaging techniques to capture these dynamics in vivo, there is little information on the physiological and biomechanical regulation of sperm transport through the male reproductive tract. Here, we present a functional in vivo imaging approach using optical coherence tomography, enabling live, label-free, depth-resolved, three-dimensional, high-resolution visualization of the mouse testis and epididymis. With this approach, we spatiotemporally captured tubular contractility in mouse testis and epididymis, as well as microstructures of these reproductive organs. Our findings demonstrated that the contraction frequency varies significantly depending on the epididymal regions, suggesting the spatial regulation of epididymal contractility. Furthermore, we implemented quantitative measurements of the contraction wave and luminal transport through the epididymal duct, revealing the physiological dynamics within the male reproductive tract. The results show that the contraction wave propagates along the epididymal duct and the wave propagation velocity was estimated in vivo. In conclusion, this is the first study to develop in vivo dynamic volumetric imaging of the male reproductive tract, which allows for quantitative analysis of the dynamics associated with sperm transport. This study sets a platform for various studies investigating normal and abnormal male reproductive physiology as well as the pharmacological and environmental effects on reproductive functions in mouse models, ultimately contributing to a comprehensive understanding of male reproductive disorders.

Fourier Ptychographic Microscopy 10 Years on: A Review

Fourier ptychographic microscopy (FPM) emerged as a prominent imaging technique in 2013, attracting significant interest due to its remarkable features such as precise phase retrieval, expansive field of view (FOV), and superior resolution. Over the past decade, FPM has become an essential tool in microscopy, with applications in metrology, scientific research, biomedicine, and inspection. This achievement arises from its ability to effectively address the persistent challenge of achieving a trade-off between FOV and resolution in imaging systems. It has a wide range of applications, including label-free imaging, drug screening, and digital pathology. In this comprehensive review, we present a concise overview of the fundamental principles of FPM and compare it with similar imaging techniques. In addition, we present a study on achieving colorization of restored photographs and enhancing the speed of FPM. Subsequently, we showcase several FPM applications utilizing the previously described technologies, with a specific focus on digital pathology, drug screening, and three-dimensional imaging. We thoroughly examine the benefits and challenges associated with integrating deep learning and FPM. To summarize, we express our own viewpoints on the technological progress of FPM and explore prospective avenues for its future developments.

Polarization-Sensitive Optical Coherence Tomography for Monitoring De- and Remineralization of Bovine Enamel In Vitro

Early caries diagnosis still challenges dentistry. Polarization-sensitive optical coherence tomography (PS-OCT) is promising to detect initial lesions non-invasively in depth-resolved cross-sectional visualization. PS-OCT with determined degree of polarization (DOP) imaging provides an intuitive demineralization contrast. The aim of this study is to evaluate the suitability of DOP-based PS-OCT imaging to monitor controlled de- and remineralization progression for the first time and to introduce it as a valid, non-destructive in vitro detection method. Twelve standardized bovine enamel specimens were divided in different groups and demineralized with hydrochloric acid (HCl) as well as partly remineralized with fluoride over a 14-day pH-cycling experiment. The specimens were stored in artificial saliva and sodium chloride (NaCl), respectively. Progress measurements with PS-OCT were made with polarization-sensitive en faceand B-scan mode for qualitative evaluation. The specimens demineralized in HCl showed the most pronounced surface change (lowest DOP) and the most significant increase in depolarization. Additional fluoride treatment and the storage in artificial saliva resulted in the opposite (highest DOP). Therefore, DOP-based PS-OCT imaging appears to be a valuable technique for visualization and monitoring of enamel demineralization and remineralization processes in vitro. However, these findings need to be confirmed in human teeth ex vivo or in situ.

Spatio-spectral 4D coherent ranging using a flutter-wavelength-swept laser

Coherent light detection and ranging (LiDAR), particularly the frequency-modulated continuous-wave LiDAR, is a robust optical imaging technology for measuring long-range distance and velocity in three dimensions (3D). We propose a spatio-spectral coherent LiDAR based on a unique wavelength-swept laser to enable both axial coherent ranging and lateral spatio-spectral beam scanning simultaneously. Instead of the conventional unidirectional wavelength-swept laser, a flutter-wavelength-swept laser (FWSL) successfully decoupled bidirectional wavelength modulation and continuous wavelength sweep, which overcame the measurable distance limited by the sampling process. The decoupled operation in FWSL enabled sequential sampling of flutter-wavelength modulation across its wide spectral bandwidth of 160 nm and, thus, allowed simultaneous distance and velocity measurement over an extended measurable distance. Herein, complete four-dimensional (4D) imaging, combining real-time 3D distance and velocity measurements, was implemented by solid-state beam scanning. An acousto-optic scanner was synchronized to facilitate the other lateral beam scanning, resulting in an optimized solid-state coherent LiDAR system. The proposed spatio-spectral coherent LiDAR system achieved high-resolution coherent ranging over long distances and real-time 4D imaging with a frame rate of 10 Hz, even in challenging environments.

Enhancing epidural needle guidance using a polarization-sensitive optical coherence tomography probe with convolutional neural networks

Epidural anesthesia helps manage pain during different surgeries. Nonetheless, the precise placement of the epidural needle remains a challenge. In this study, we developed a probe based on polarization-sensitive optical coherence tomography (PS-OCT) to enhance the epidural anesthesia needle placement. The probe was tested on six porcine spinal samples. The multimodal imaging guidance used the OCT intensity mode and three distinct PS-OCT modes: (1) phase retardation, (2) optic axis, and (3) degree of polarization uniformity (DOPU). Each mode enabled the classification of different epidural tissues through distinct imaging characteristics. To further streamline the tissue recognition procedure, convolutional neural network (CNN) were used to autonomously identify the tissue types within the probe's field of view. ResNet50 models were developed for all four imaging modes. DOPU imaging was found to provide the highest cross-testing accuracy of 91.53%. These results showed the improved precision by PS-OCT in guiding epidural anesthesia needle placement.

Polarization-sensitive optical coherence tomography for renal tumor detection in ex vivo human kidneys

Kidney cancer is a kind of high mortality cancer because of the difficulty in early diagnosis and the high metastatic dissemination in treatments. The surgical resection of tumors is the most effective treatment for renal cancer patients. However, precise assessment of tumor margins is a challenge during surgical resection. The objective of this study is to demonstrate an optical imaging tool in precisely distinguishing kidney tumor borders and identifying tumor zones from normal tissues to assist surgeons in accurately resecting tumors from kidneys during the surgery. 30 samples from six human kidneys were imaged using polarization-sensitive optical coherence tomography (PS-OCT). Cross-sectional, enface, and spatial information of kidney samples were obtained for microenvironment reconstruction. Polarization parameters (phase retardation, optic axis direction, and degree of polarization uniformity (DOPU) and Stokes parameters (Q, U, and V) were utilized for multi-parameter analysis. To verify the detection accuracy of PS-OCT, H&E histology staining and dice-coefficient was utilized to quantify the performance of PS-OCT in identifying tumor borders and regions. In this study, tumor borders were clearly identified by PS-OCT imaging, which outperformed the conventional intensity-based OCT. With H&E histological staining as golden standard, PS-OCT precisely identified the tumor regions and tissue distributions at different locations and different depths based on polarization and Stokes parameters. Compared to the traditional attenuation coefficient quantification method, PS-OCT demonstrated enhanced contrast of tissue characteristics between normal and cancerous tissues due to the birefringence effects. Our results demonstrated that PS-OCT was promising to provide imaging guidance for the surgical resection of kidney tumors and had the potential to be used for other human kidney surgeries in clinics such as renal biopsy.

Real-time line-field optical coherence tomography for cellular resolution imaging of biological tissue

A real-time line-field optical coherence tomography (LF-OCT) system is demonstrated with image acquisition rates of up to 5000 B-frames or 2.5 million A-lines per second for 500 A-lines per B-frame. The system uses a high-speed low-cost camera to achieve continuous data transfer rates required for real-time imaging, allowing the evaluation of future applications in clinical or intraoperative environments. The light source is an 840 nm super-luminescent diode. Leveraging parallel computing with GPU and high speed CoaXPress data transfer interface, we were able to acquire, process, and display OCT data with low latency. The studied system uses anamorphic beam shaping in the detector arm, optimizing the field of view and sensitivity for imaging biological tissue at cellular resolution. The lateral and axial resolution measured in air were 1.7 µm and 6.3 µm, respectively. Experimental results demonstrate real-time inspection of the trabecular meshwork and Schlemm's canal on ex vivo corneoscleral wedges and real-time imaging of endothelial cells of human subjects in vivo.

High-accuracy 3D segmentation of wet age-related macular degeneration via multi-scale and cross-channel feature extraction and channel attention

Wet age-related macular degeneration (AMD) is the leading cause of visual impairment and vision loss in the elderly, and optical coherence tomography (OCT) enables revolving biotissue three-dimensional micro-structure widely used to diagnose and monitor wet AMD lesions. Many wet AMD segmentation methods based on deep learning have achieved good results, but these segmentation results are two-dimensional, and cannot take full advantage of OCT's three-dimensional (3D) imaging characteristics. Here we propose a novel deep-learning network characterizing multi-scale and cross-channel feature extraction and channel attention to obtain high-accuracy 3D segmentation results of wet AMD lesions and show the 3D specific morphology, a task unattainable with traditional two-dimensional segmentation. This probably helps to understand the ophthalmologic disease and provides great convenience for the clinical diagnosis and treatment of wet AMD.

Cardiac Optical Coherence Tomography: History, Current Status, and Perspective

For more than 2 decades since the first imaging procedure was performed in a living patient, intravascular optical coherence tomography (OCT), with its unprecedented image resolution, has made significant contributions to cardiovascular medicine in the realms of vascular biology research and percutaneous coronary intervention. OCT has contributed to a better understanding of vascular biology by providing insights into the pathobiology of atherosclerosis, including plaque phenotypes and the underlying mechanisms of acute coronary syndromes such as plaque erosion, neoatherosclerosis, stent thrombosis, and myocardial infarction with nonobstructive coronary arteries. Moreover, OCT has been used as an adjunctive imaging tool to angiography for the guidance of percutaneous coronary intervention procedures to optimize outcomes. However, broader application of OCT has faced challenges, including subjective interpretation of the images and insufficient clinical outcome data. Future developments including artificial intelligence-assisted interpretation, multimodality catheters, and micro-OCT, as well as large prospective outcome studies could broaden the impact of OCT on cardiovascular medicine.

MCOCT: an experimentally and numerically validated, open-source Monte Carlo simulator for optical coherence tomography

Here, we present MCOCT, a Monte Carlo simulator for optical coherence tomography (OCT), incorporating a Gaussian illumination scheme and bias to increase backscattered event collection. MCOCT optical fluence was numerically compared and validated to an established simulator (MCX) and showed concordance at the focus while diverging slightly with distance to it. MCOCT OCT signals were experimentally compared and validated to OCT signals acquired in tissue-mimicking phantoms with known optical properties and showed a similar attenuation pattern with increasing depth while diverging beyond 1.5 mm and proximal to layer interfaces. MCOCT may help in the design of OCT systems for a wide range of applications.

Macular and peripapillary Choroidal Vascularity Index in children with different refractive status

OBJECTIVES

To characterize choroidal vascular changes in children with different refractive status.

METHODS

A study including 5864 children aged 6-9 years was performed to investigate the choroidal vascular index (CVI) in myopic, emmetropic and hyperopic eyes. Each participant had a comprehensive ocular examination with cycloplegic autorefraction performed, axial length (AL) measured and Swept Source-Optical Coherence Tomography (SS-OCT) scans acquired. Choroidal thickness (ChT) was measured by built-in software, and CVI was calculated using a previously validated self-developed algorithm.

RESULTS

The mean ChT and CVI were 275.88 ± 53.34 μm and 34.91 ± 3.83 in the macula region, and 191.96 ± 46.28 μm and 32.35 ± 4.21 in the peripapillary region. CVI was significantly lowest for myopes, followed by emmetropes and hyperopes (P < 0.001). CVI varied between different sectors separated by the Early Treatment of Diabetic Retinopathy Study (ETDRS) grid (P < 0.001). Macular CVI decreased horizontally from nasal to temporal quadrant with lowest in center fovea, and vertically from superior to inferior quadrants. Peripapillary CVI was highest in the nasal and lowest in the inferior sector. Multiple regression showed that spherical equivalent (SE), AL, intraocular pressure (IOP), ChT, age, and gender were significantly related to CVI (P < 0.05).

CONCLUSIONS

In children, the distribution of CVI in the posterior pole is not uniform. A decreased CVI was observed from hyperopia to myopia and was associated with decreased SE, elongated AL, and choroidal thinning. Further study of changes in CVI during myopia onset and progression is required to better understand the role of the choroidal vasculature in myopia development.

Imaging the Ear Anatomy and Function Using Optical Coherence Tomography Vibrometry

Optical coherence tomography (OCT) is a novel technology for performing real-time high-speed and high-resolution cross-sectional imaging on the micro-scale in situ. It is analogous to ultrasound imaging, except that it uses light instead of sound. OCT has recently been introduced in auditory research to visualize the various structures of the ear with a minimally invasive operation. In addition, OCT can be used as a vibrometry system that is capable to detect sound-induced sub-nanometer vibrations of the middle and inner ear. OCT-vibrometry measures depth-resolved vibrations into the specimen, which overcomes several limitations of classical vibrometry techniques (e.g., single surface point measurements using laser interferometry). In this article, we illustrate how to visualize the anatomy and function of the middle and inner ear (the cochlea) in a gerbil model using recently developed spectral-domain OCT. Our results demonstrate that the largest clinical impact of OCT for otology is to visualize various pathologies and quantify sound conduction and processing in the individual peripheral human ear.

Quantitative analysis of deep learning-based denoising model efficacy on optical coherence tomography images with different noise levels

BACKGROUND

To quantitatively evaluate the effectiveness of the Noise2Noise (N2N) model, a deep learning (DL)-based noise reduction algorithm, on enhanced depth imaging-optical coherence tomography (EDI-OCT) images with different noise levels.

METHODS

The study included 30 subfoveal EDI-OCT images averaged with 100 frames from 30 healthy participants. Artificial Gaussian noise at 25.00, 50.00, and 75.00 standard deviations were added to the averaged (original) images, and the images were grouped as 25N, 50N, and 75N. Afterward, noise-added images were denoised with the N2N model and grouped as 25dN, 50dN, and 75dN, according to previous noise levels. The choroidal vascularity index (CVI) and deep choroidal contrast-to-noise ratio (CNR) were calculated for all images, and noise-added and denoised images were compared with the original images. The structural similarity of the noise-added and denoised images to the original images was assessed by the Multi-Scale Structural Similarity Index (MS-SSI).

RESULTS

The CVI and CNR parameters of the original images (68.08 ± 2.47 %, and 9.71 ± 2.80) did not differ from the only 25dN images (67.97 ± 2.34 % and 8.50 ± 2.43) (p:1.000, and p:0.062, respectively). Noise reduction improved the MS-SSI at each noise level (p < 0.001). However, the highest MS-SSI was achieved in 25dN images.

CONCLUSIONS

The DL-based N2N denoising model can be used effectively for images with low noise levels, but at increasing noise levels, this model may be insufficient to provide both the original structural features of the choroid and structural similarity to the original image.

Optical Coherence Tomographic Optic Nerve Head Morphology in Myopia III: The Exposed Neural Canal Region in Healthy Eyes-Implications for High Myopia

PURPOSE

To determine the prevalence and magnitude of optical coherence tomography (OCT) exposed neural canal (ENC), externally oblique choroidal border tissue (EOCBT), and exposed scleral flange (ESF) regions in 362 non-highly myopic (spherical equivalent -6.00 to 5.75 diopters) eyes of 362 healthy subjects.

DESIGN

Cross-sectional study.

METHODS

After OCT optic nerve head (ONH) imaging, Bruch membrane opening (BMO), the anterior scleral canal opening (ASCO), and the scleral flange opening (SFO) were manually segmented. BMO, ASCO, and SFO points were projected to the BMO reference plane. The direction and magnitude of BMO/ASCO offset as well as the magnitude of ENC, EOCBT, and ESF was calculated within 30° sectors relative to the foveal-BMO axis. Hi-ESF eyes demonstrated an ESF ≥100 µm in at least 1 sector. Sectoral peri-neural canal choroidal thickness (pNC-CT) was measured and correlations between the magnitude of sectoral ESF and proportional pNC-CT were assessed.

RESULTS

Seventy-three Hi-ESF (20.2%) and 289 non-Hi-ESF eyes (79.8%) were identified. BMO/ASCO offset as well as ENC, EOCBT, and ESF prevalence and magnitude were greatest inferior temporally where the pNC-CT was thinnest. Among Hi-ESF eyes, the magnitude of each ENC region correlated with the BMO/ASCO offset magnitude, and the sectors with the longest ESF correlated with the sectors with proportionally thinnest pNC-CT.

CONCLUSIONS

ONH BMO/ASCO offset, either as a cause or result of ONH neural canal remodeling, corresponds with the sectoral location of maximum ESF and minimum pNC-CT in non-highly myopic eyes. Longitudinal studies to characterize the development and clinical implications of ENC Hi-ESF regions in non-highly myopic and highly myopic eyes are indicated.

Self-supervised Self2Self denoising strategy for OCT speckle reduction with a single noisy image

Optical coherence tomography (OCT) inevitably suffers from the influence of speckles originating from multiple scattered photons owing to its low-coherence interferometry property. Although various deep learning schemes have been proposed for OCT despeckling, they typically suffer from the requirement for ground-truth images, which are difficult to collect in clinical practice. To alleviate the influences of speckles without requiring ground-truth images, this paper presents a self-supervised deep learning scheme, namely, Self2Self strategy (S2Snet), for OCT despeckling using a single noisy image. Specifically, in this study, the main deep learning architecture is the Self2Self network, with its partial convolution being updated with a gated convolution layer. Specifically, both the input images and their Bernoulli sampling instances are adopted as network input first, and then, a devised loss function is integrated into the network to remove the background noise. Finally, the denoised output is estimated using the average of multiple predicted outputs. Experiments with various OCT datasets are conducted to verify the effectiveness of the proposed S2Snet scheme. Results compared with those of the existing methods demonstrate that S2Snet not only outperforms those existing self-supervised deep learning methods but also achieves better performances than those non-deep learning ones in different cases. Specifically, S2Snet achieves an improvement of 3.41% and 2.37% for PSNR and SSIM, respectively, as compared to the original Self2Self network, while such improvements become 19.9% and 22.7% as compared with the well-known non-deep learning NWSR method.

Role of intravascular ultrasound and optical coherence tomography in intracoronary imaging for coronary artery disease: a systematic review

Coronary angiography has long been the standard for coronary imaging, but it has limitations in assessing vessel wall anatomy and guiding percutaneous coronary intervention (PCI). Intracoronary imaging techniques like intravascular ultrasound (IVUS) and optical coherence tomography (OCT) can overcome these limitations. IVUS uses ultrasound and OCT uses near-infrared light to visualize coronary pathology in unique ways due to differences in temporal and spatial resolution. These techniques have evolved to offer clinical utility in plaque characterization and vessel assessment during PCI. Meta-analyses and adjusted observational studies suggest that both IVUS and OCT-guided PCI correlate with reduced cardiovascular risks compared to angiographic guidance alone. While IVUS demonstrates consistent clinical outcome benefits, OCT evidence is less robust. IVUS has progressed from early motion detection to high-resolution systems, with smaller compatible catheters. OCT utilizes near infrared light to achieve unparalleled resolutions, but requires temporary blood clearance for optimal imaging. Enhanced visualization and guidance make IVUS and OCT well-suited for higher risk PCI in patients with diabetes and chronic kidney disease by allowing detailed visualization of complex lesions and ensuring optimal stent deployment and positioning in PCI for patients with type 2 diabetes and chronic kidney disease, improving outcomes. IVUS and recent advancements in zero- and low-contrast OCT techniques can reduce nephrotoxic contrast exposure, thus helping to minimize PCI complications in these high-risk patient groups. IVUS and OCT provide valuable insights into coronary pathophysiology and guide interventions precisely compared to angiography alone. Both have comparable clinical outcomes, emphasizing the need for tailored imaging choices based on clinical scenarios. Continued refinement and integration of intravascular imaging will likely play a pivotal role in optimizing coronary interventions and outcomes. This systematic review aims to delve into the nuances of IVUS and OCT, highlighting their strengths and limitations as PCI adjuncts.

Impaired brachial flow-mediated dilation may predict choroidal and retinal nerve fibre layer thickness changes in people with obesity

CLINICAL RELEVANCE

Choroidal thickness and peripapillary retinal nerve fibre layer (RNFL) changes are known to occur in obesity. Endothelial dysfunction and systemic atherosclerosis may play a role in the pathophysiology of these differences.

BACKGROUND

Flow-mediated dilation (FMD) is reduced in patients with endothelial dysfunction, and the ankle-brachial index is a surrogate marker for atherosclerosis. This study was conducted to examine the relationship between systemic vascular parameters (FMD, and ankle-brachial index), subfoveal choroidal thickness, and peripapillary RNFL thickness in obese individuals.

METHODS

This observational, cross-sectional study involved 108 total participants who were divided into two groups. One group consisted of 54 obese subjects who each had a body mass index of 30 kg/m2 or more. The other control group contained 54 participants who each had a body mass index of 25 kg/m2 or less but higher than 20 kg/m2 . For each participant, only one eye was examined in this study. Subfoveal choroidal thickness, RNFL thickness, ankle-brachial index, and ultrasound measurement of the brachial artery FMD were performed. FMD was categorised according to receiver operating characteristic analysis, and endothelial dysfunction was defined as an FMD ≤ 7.29%.

RESULTS

Subfoveal choroidal and RNFL thicknesses in the temporal quadrant were significantly lower in the obese group (p < 0.05). Lower mean values of subfoveal choroidal and RNFL thicknesses in the temporal and inferior quadrants were observed in subjects with an FMD ≤ 7.29% (p < 0.05). In people with obesity, FMD was positively correlated with subfoveal choroidal thickness (r = 0.322, p = 0.001), inferior RNFL thickness (r = 0.259, p = 0.007), and temporal RNFL thickness (r = 0.297, p = 0.002). However, the ankle-brachial index was not correlated with obesity.

CONCLUSIONS

Impaired FMD was associated with reduced subfoveal choroidal and RNFL thicknesses in the temporal and inferior quadrants of people with obesity.

Enhancing foveal avascular zone analysis for Alzheimer's diagnosis with AI segmentation and machine learning using multiple radiomic features

We propose a hybrid technique that employs artificial intelligence (AI)-based segmentation and machine learning classification using multiple features extracted from the foveal avascular zone (FAZ)-a retinal biomarker for Alzheimer's disease-to improve the disease diagnostic performance. Imaging data of optical coherence tomography angiography from 37 patients with Alzheimer's disease and 48 healthy controls were investigated. The presence or absence of brain amyloids was confirmed using amyloid positron emission tomography. In the superficial capillary plexus of the angiography scans, the FAZ was automatically segmented using an AI method to extract multiple biomarkers (area, solidity, compactness, roundness, and eccentricity), which were paired with clinical data (age and sex) as common correction variables. We used a light-gradient boosting machine (a light-gradient boosting machine is a machine learning algorithm based on trees utilizing gradient boosting) to diagnose Alzheimer's disease by integrating the corresponding multiple radiomic biomarkers. Fivefold cross-validation was applied for analysis, and the diagnostic performance for Alzheimer's disease was determined by the area under the curve. The proposed hybrid technique achieved an area under the curve of [Formula: see text]%, outperforming the existing single-feature (area) criteria by over 13%. Furthermore, in the holdout test set, the proposed technique exhibited a 14% improvement compared to single features, achieving an area under the curve of 72.0± 4.8%. Based on these facts, we have demonstrated the effectiveness of our technology in achieving significant performance improvements in FAZ-based Alzheimer's diagnosis research through the use of multiple radiomic biomarkers (area, solidity, compactness, roundness, and eccentricity).

Assessment of macular choroidal and retinal thickness: a cohort study in Tibetan healthy children

This research investigates the distribution, progressive changes, and contributing factors of macular choroidal and retinal thickness in Tibetan children utilizing swept-source optical coherence tomography (SS-OCT). The Lhasa childhood study recruited 1632 students from seven primary schools in Lhasa. These participants underwent OCT and ophthalmological evaluations, encompassing retinal and choroidal thickness measurements, refractive error, axial length (AL), and systemic examinations. The median age of the scholars was 8.57 ± 0.50 years with a median spherical equivalent (SE) of 0.19 ± 1.28D. Multivariate regression analysis revealed that thinner macular choroid thickness was correlated with lower value of SE, worse best-corrected visual acuity, higher mean arterial blood pressure (MABP) and boys, while retinal thickness was associated with better image quality and lower value of SE. The choroid and retina were significantly thinner in myopic children. SE was positively related to the thickness of all choroidal and full retinal subregions. In comparison to baseline data from 20 months prior, most regions of the full retina had significantly thinned. Choroidal thickness of Tibetan children is thinner than that of same-age children from other regions. Thinning of retina, the outer-sector GCC and GCIPL may be specified as a follow-up and prognostic indicator for myopia.

Motion Contrast, Phase Gradient, and Simultaneous OCT Images Assist in the Interpretation of Dark-Field Images in Eyes with Retinal Pathology

The cellular-level visualization of retinal microstructures such as blood vessel wall components, not available with other imaging modalities, is provided with unprecedented details by dark-field imaging configurations; however, the interpretation of such images alone is sometimes difficult since multiple structural disturbances may be present in the same time. Particularly in eyes with retinal pathology, microstructures may appear in high-resolution retinal images with a wide range of sizes, sharpnesses, and brightnesses. In this paper we show that motion contrast and phase gradient imaging modalities, as well as the simultaneous acquisition of depth-resolved optical coherence tomography (OCT) images, provide additional insight to help understand the retinal neural and vascular structures seen in dark-field images and may enable improved diagnostic and treatment plans.

Two-photon excitation fluorescence in ophthalmology: safety and improved imaging for functional diagnostics

Two-photon excitation fluorescence (TPEF) is emerging as a powerful imaging technique with superior penetration power in scattering media, allowing for functional imaging of biological tissues at a subcellular level. TPEF is commonly used in cancer diagnostics, as it enables the direct observation of metabolism within living cells. The technique is now widely used in various medical fields, including ophthalmology. The eye is a complex and delicate organ with multiple layers of different cell types and tissues. Although this structure is ideal for visual perception, it generates aberrations in TPEF eye imaging. However, adaptive optics can now compensate for these aberrations, allowing for improved imaging of the eyes of animal models for human diseases. The eye is naturally built to filter out harmful wavelengths, but these wavelengths can be mimicked and thereby utilized in diagnostics via two-photon (2Ph) excitation. Recent advances in laser-source manufacturing have made it possible to minimize the exposure of in vivo measurements within safety, while achieving sufficient signals to detect for functional images, making TPEF a viable option for human application. This review explores recent advances in wavefront-distortion correction in animal models and the safety of use of TPEF on human subjects, both of which make TPEF a potentially powerful tool for ophthalmological diagnostics.

Artificial intelligence and hemodynamic studies in optical coherence tomography angiography for diabetic retinopathy evaluation: A review

Diabetic retinopathy (DR) is a rapidly emerging retinal abnormality worldwide, which can cause significant vision loss by disrupting the vascular structure in the retina. Recently, optical coherence tomography angiography (OCTA) has emerged as an effective imaging tool for diagnosing and monitoring DR. OCTA produces high-quality 3-dimensional images and provides deeper visualization of retinal vessel capillaries and plexuses. The clinical relevance of OCTA in detecting, classifying, and planning therapeutic procedures for DR patients has been highlighted in various studies. Quantitative indicators obtained from OCTA, such as blood vessel segmentation of the retina, foveal avascular zone (FAZ) extraction, retinal blood vessel density, blood velocity, flow rate, capillary vessel pressure, and retinal oxygen extraction, have been identified as crucial hemodynamic features for screening DR using computer-aided systems in artificial intelligence (AI). AI has the potential to assist physicians and ophthalmologists in developing new treatment options. In this review, we explore how OCTA has impacted the future of DR screening and early diagnosis. It also focuses on how analysis methods have evolved over time in clinical trials. The future of OCTA imaging and its continued use in AI-assisted analysis is promising and will undoubtedly enhance the clinical management of DR.

CylinGCN: Cylindrical structures segmentation in 3D biomedical optical imaging by a contour-based graph convolutional network

Cylindrical organs, e.g., blood vessels, airways, and intestines, are ubiquitous structures in biomedical optical imaging analysis. Image segmentation of these structures serves as a vital step in tissue physiology analysis. Traditional model-driven segmentation methods seek to fit the structure by constructing a corresponding topological geometry based on domain knowledge. Classification-based deep learning methods neglect the geometric features of the cylindrical structure and therefore cannot ensure the continuity of the segmentation surface. In this paper, by treating the cylindrical structures as a 3D graph, we introduce a novel contour-based graph neural network for 3D cylindrical structure segmentation in biomedical optical imaging. Our proposed method, which we named CylinGCN, adopts a novel learnable framework that extracts semantic features and complex topological relationships in the 3D volumetric data to achieve continuous and effective 3D segmentation. Our CylinGCN consists of a multiscale 3D semantic feature extractor for extracting inter-frame multiscale semantic features, and a residual graph convolutional network (GCN) contour generator that combines the semantic features and cylindrical topological priors to generate segmentation contours. We tested the CylinGCN framework on two types of optical tomographic imaging data, small animal whole body photoacoustic tomography (PAT) and endoscopic airway optical coherence tomography (OCT), and the results show that CylinGCN achieves state-of-the-art performance. Code will be released at https://github.com/lzc-smu/CylinGCN.git.

Interpretable Diabetic Retinopathy Diagnosis Based on Biomarker Activation Map

OBJECTIVE

Deep learning classifiers provide the most accurate means of automatically diagnosing diabetic retinopathy (DR) based on optical coherence tomography (OCT) and its angiography (OCTA). The power of these models is attributable in part to the inclusion of hidden layers that provide the complexity required to achieve a desired task. However, hidden layers also render algorithm outputs difficult to interpret. Here we introduce a novel biomarker activation map (BAM) framework based on generative adversarial learning that allows clinicians to verify and understand classifiers' decision-making.

METHODS

A data set including 456 macular scans were graded as non-referable or referable DR based on current clinical standards. A DR classifier that was used to evaluate our BAM was first trained based on this data set. The BAM generation framework was designed by combing two U-shaped generators to provide meaningful interpretability to this classifier. The main generator was trained to take referable scans as input and produce an output that would be classified by the classifier as non-referable. The BAM is then constructed as the difference image between the output and input of the main generator. To ensure that the BAM only highlights classifier-utilized biomarkers an assistant generator was trained to do the opposite, producing scans that would be classified as referable by the classifier from non-referable scans.

RESULTS

The generated BAMs highlighted known pathologic features including nonperfusion area and retinal fluid.

CONCLUSION/SIGNIFICANCE

A fully interpretable classifier based on these highlights could help clinicians better utilize and verify automated DR diagnosis.

Portable contactless caliper

This work presents a portable optical meter for noncontact thickness measurement. The device shines a focused laser light on a thin and transparent sample, resulting in an interference between light reflecting from the top and from the bottom surface, and the interfering pattern is recorded by a linear sensor array before data analysis with an Arduino microcontroller. The device produced accurate thickness values from glass cover slips and transparent plastic sheets within a fraction of a second per measurement. Additionally, the sample's refractive index is not required a priori. Therefore, it has a high potential to be of use in real-time quality control in transparent thick-film coating and manufacturing.

Imaging of Anterior Segment Tumours: A Comparison of Ultrasound Biomicroscopy Versus Anterior Segment Optical Coherence Tomography

Anterior segment tumours of the eye are relatively rare but can pose significant morbidity and mortality. We conducted a literature review to compare the performance of ultrasound biomicroscopy to anterior segment optical coherence tomography in the imaging of these tumours. A total of seven studies were included accounting for a cumulative 1,114 eyes. Ultrasound biomicroscopy has traditionally formed, and remains, the mainstay of tumour imaging due to its ability to penetrate pigmented lesions and delineate the posterior border of tumours, and the current evidence supports this.

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.

Imaging peritoneal blood vessels through optical coherence tomography angiography for laparoscopic surgery

Laparoscopic surgery presents challenges in identifying blood vessels due to lack of tactile feedback. The image-guided laparoscopic surgical tool (IGLaST) integrated with optical coherence tomography (OCT) has potential for in vivo blood vessel imaging; however, distinguishing vessels from surrounding tissue remains a challenge. In this study, we propose utilizing an inter-A-line intensity differentiation-based OCT angiography (OCTA) to improve visualization of blood vessels. By evaluating a tissue phantom with varying flow speeds, we optimized the system's blood flow imaging capabilities in terms of minimum detectable flow and contrast-to-noise ratio. In vivo experiments on rat and porcine models, successfully visualized previously unidentified blood vessels and concealed blood flows beneath the 1 mm depth peritoneum. Qualitative comparison of various OCTA algorithms indicated that the intensity differentiation-based algorithm performed best for our application. We believe that implementing IGLaST with OCTA can enhance surgical outcomes and reduce procedure time in laparoscopic surgeries.

Revolutionizing Cancer Care: Advances in Carbon-Based Materials for Diagnosis and Treatment

Cancer involves intricate pathological mechanisms marked by complexities such as cytotoxicity, drug resistance, stem cell proliferation, and inadequate specificity in current chemotherapy approaches. Cancer therapy has embraced diverse nanomaterials renowned for their unique magnetic, electrical, and optical properties to address these challenges. Despite the expanding corpus of knowledge in this area, there has been less advancement in approving nano drugs for use in clinical settings. Nanotechnology, and more especially the development of intelligent nanomaterials, has had a profound impact on cancer research and treatment in recent years. Due to their large surface area, nanoparticles can adeptly encapsulate diverse compounds. Furthermore, the modification of nanoparticles is achievable through a broad spectrum of bio-based substrates, including DNA, aptamers, RNA, and antibodies. This functionalization substantially enhances their theranostic capabilities. Nanomaterials originating from biological sources outperform their conventionally created counterparts, offering advantages such as reduced toxicity, lower manufacturing costs, and enhanced efficiency. This review uses carbon nanomaterials, including graphene-based materials, carbon nanotubes (CNTs) based nanomaterials, and carbon quantum dots (CQDs), to give a complete overview of various methods used in cancer theranostics. We also discussed their advantages and limitations in cancer diagnosis and treatment settings. Carbon nanomaterials might significantly improve cancer theranostics and pave the way for fresh tumor diagnosis and treatment approaches. More study is needed to determine whether using nano-carriers for targeted medicine delivery may increase material utilization. More insight is required to explore the correlation between heightened cytotoxicity and retention resulting from increased permeability.

An optical coherence study on optic disc parameters and peripapillary retinal nerve fiber layer thickness in patients with optic disc edema

PURPOSE

This study aimed at evaluation of patients diagnosed with optic disc edema (ODE) in terms of demographics, etiology, clinical presentation, and optical coherence tomography parameters.

METHODS

An observational cross-sectional study was conducted from August 2021 to July 2022. Patients diagnosed with ODE underwent comprehensive ophthalmic evaluation. Peripapillary retinal nerve fiber layer (RNFL) thickness and optic nerve head parameters were assessed using optical coherence tomography. Radiologic investigations were done as deemed necessary.

RESULTS

One hundred and forty-eight eyes with ODE (134 eyes from 67 patients with bilateral ODE and 14 eyes from 14 patients with unilateral ODE) and 148 eyes of age- and gender-matched control group were included in the study. The mean age of the study population was 31.51 ± 13.33 years, with 44 (54.3%) males and 37 (45.6%) females. Bilateral ODE was seen in 82.7% of patients. Idiopathic intracranial hypertension was the most common cause of bilateral ODE, and nonarteritic anterior ischemic optic neuropathy was the most common cause of unilateral presentation. Decreased vision and headache were the main symptoms reported by a majority of patients. Peripapillary RNFL thickness was significantly increased in the ODE group compared to controls.

CONCLUSION

The current study provides the clinical profile and optic disc and RNFL measurements of ODE patients in an Eastern Indian population. Detailed history and careful evaluation are necessary, as the treatment strategy is highly dependent on the underlying etiologies.

Imaging objects hidden inside the strongly scattering media based on bidirectional ghost imaging

We demonstrate a novel, to the best of our knowledge, method for imaging objects hidden inside the strongly scattering media based on bidirectional ghost imaging (GI). In this method, GI is performed separately on both sides of the object, resulting in two GI results. Through an autocorrelation operation to the two GI results, the convolution between the autocorrelation of the object and the point spread function (PSF) of the strongly scattering media can be recovered. Therefore, the object can be recovered by obtaining the PSF of the strongly scattering media through noninvasive measurement or numerical calculation. Simulation and experimental results show that bidirectional ghost imaging (BGI) can reconstruct high-quality images, particularly when the thickness of the strongly scattering media greatly exceeds the scattering mean free path.

Cross-attention learning enables real-time nonuniform rotational distortion correction in OCT

Nonuniform rotational distortion (NURD) correction is vital for endoscopic optical coherence tomography (OCT) imaging and its functional extensions, such as angiography and elastography. Current NURD correction methods require time-consuming feature tracking/registration or cross-correlation calculations and thus sacrifice temporal resolution. Here we propose a cross-attention learning method for the NURD correction in 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 spatial 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. We further verify the NURD correction performance of our method on 3D stent reconstruction using a home-built endoscopic OCT system. Our method achieves a ∼3 × speedup to real time (26 ± 3 fps), and superior correction performance.

The LMIT: Light-mediated minimally-invasive theranostics in oncology

Minimally-invasive diagnosis and therapy have gradually become the trend and research hotspot of current medical applications. The integration of intraoperative diagnosis and treatment is a development important direction for real-time detection, minimally-invasive diagnosis and therapy to reduce mortality and improve the quality of life of patients, so called minimally-invasive theranostics (MIT). Light is an important theranostic tool for the treatment of cancerous tissues. Light-mediated minimally-invasive theranostics (LMIT) is a novel evolutionary technology that integrates diagnosis and therapeutics for the less invasive treatment of diseased tissues. Intelligent theranostics would promote precision surgery based on the optical characterization of cancerous tissues. Furthermore, MIT also requires the assistance of smart medical devices or robots. And, optical multimodality lay a solid foundation for intelligent MIT. In this review, we summarize the important state-of-the-arts of optical MIT or LMIT in oncology. Multimodal optical image-guided intelligent treatment is another focus. Intraoperative imaging and real-time analysis-guided optical treatment are also systemically discussed. Finally, the potential challenges and future perspectives of intelligent optical MIT are discussed.

Optical tomography in a single camera frame using fringe-encoded deep-learning full-field OCT

Optical coherence tomography is a valuable tool for in vivo examination thanks to its superior combination of axial resolution, field-of-view and working distance. OCT images are reconstructed from several phases that are obtained by modulation/multiplexing of light wavelength or optical path. This paper shows that only one phase (and one camera frame) is sufficient for en face tomography. The idea is to encode a high-frequency fringe patterns into the selected layer of the sample using low-coherence interferometry. These patterns can then be efficiently extracted with a high-pass filter enhanced via deep learning networks to create the tomographic full-field OCT view. This brings 10-fold improvement in imaging speed, considerably reducing the phase errors and incoherent light artifacts related to in vivo movements. Moreover, this work opens a path for low-cost tomography with slow consumer cameras. Optically, the device resembles the conventional time-domain full-field OCT without incurring additional costs or a field-of-view/resolution reduction. The approach is validated by imaging in vivo cornea in human subjects. Open-source and easy-to-follow codes for data generation/training/inference with U-Net/Pix2Pix networks are provided to be used in a variety of image-to-image translation tasks.