Deep learning toolbox for automated enhancement, segmentation, and graphing of cortical optical coherence tomography microangiograms

Dual acquisition scheme-based optical coherence tomography 3D angiography

Significance

Optical coherence tomography angiography (OCTA) is a noninvasive technique dedicated to high-resolution microvasculature imaging. However, the projection artifacts of large pial vessels make it difficult to visualize the underlying microvessels, challenging its 3D vascular imaging ability.

Aim

We propose a dual acquisition scheme-based 3D OCTA method aimed at simultaneously mitigating projection artifacts and enhancing the detection of capillary networks.

Approach

In this study, we introduce an approach incorporating a dual data acquisition scheme with optimally oriented flux (OOF) filtering to address this problem. The repeated A-scan acquisition scheme and corresponding data processing algorithm were used to address the projection artifact issue underneath large pial vessels, whereas repeated B-scan acquisition-based data processing was used to image the capillary network.

Results

With such a processing scheme, the projection artifacts can be effectively suppressed, whereas the high detection sensitivity to small vessels of repeat B-scan OCTA can be preserved, thus enabling high-sensitivity 3D imaging of the cerebral vasculature after OOF filtering.

Conclusions

The results demonstrate the capability of the proposed method for 3D OCTA imaging, which may play an important role in cerebral microvascular dysfunction-related disease studies.

Label free, capillary-scale blood flow mapping in vivo reveals that low-intensity focused ultrasound evokes persistent dilation in cortical microvasculature

Non-invasive, low intensity focused ultrasound is an emerging neuromodulation technique that offers the potential for precision, personalized therapy. An increasing body of research has identified mechanosensitive ion channels that can be modulated by FUS and support acute electrical activity in neurons. However, neuromodulatory effects that persist from hours to days have also been reported. The brain's ability to provide blood flow to electrically active regions involves a multitude of non-neuronal cell types and signaling pathways in the cerebral vasculature; an open question is whether persistent effects can be attributed, at least partly, to vascular mechanisms. Using an in vivo optical approach, we found that microvasculature, and not larger vessels, exhibit significant persistent dilation following sonication without the use of microbubbles. This finding reveals a heretofore unseen aspect of the effects of FUS in vivo and indicates that concurrent changes in neurovascular function may partially underly persistent neuromodulatory effects.

Optical coherence tomography (OCT) and OCT angiography: Technological development and applications in brain science

Brain diseases are a leading cause of disability and death worldwide. Early detection can lead to earlier intervention and better outcomes for patients. In recent years, optical coherence tomography (OCT) and OCT angiography (OCTA) imaging have been widely used in stroke, traumatic brain injury (TBI), and brain cancer due to their advantages of in vivo, unlabeled, and high-resolution 3D microvessel imaging at the capillary resolution level. This review summarizes recent advances and challenges in living brain imaging using OCT/OCTA, including technique modality, types of diseases, and theoretical approach. Although there may still be many limitations, with the development of lasers and the advances in artificial intelligence are expected to enable accurate detection of deep cerebral hemodynamics and guide intraoperative tumor resection in vivo in the future.

Bessel beam optical coherence microscopy enables multiscale assessment of cerebrovascular network morphology and function

Understanding the morphology and function of large-scale cerebrovascular networks is crucial for studying brain health and disease. However, reconciling the demands for imaging on a broad scale with the precision of high-resolution volumetric microscopy has been a persistent challenge. In this study, we introduce Bessel beam optical coherence microscopy with an extended focus to capture the full cortical vascular hierarchy in mice over 1000 × 1000 × 360 μm3 field-of-view at capillary level resolution. The post-processing pipeline leverages a supervised deep learning approach for precise 3D segmentation of high-resolution angiograms, hence permitting reliable examination of microvascular structures at multiple spatial scales. Coupled with high-sensitivity Doppler optical coherence tomography, our method enables the computation of both axial and transverse blood velocity components as well as vessel-specific blood flow direction, facilitating a detailed assessment of morpho-functional characteristics across all vessel dimensions. Through graph-based analysis, we deliver insights into vascular connectivity, all the way from individual capillaries to broader network interactions, a task traditionally challenging for in vivo studies. The new imaging and analysis framework extends the frontiers of research into cerebrovascular function and neurovascular pathologies.

Neurophotonics: a comprehensive review, current challenges and future trends

The human brain, with its vast network of billions of neurons and trillions of synapses (connections) between diverse cell types, remains one of the greatest mysteries in science and medicine. Despite extensive research, an understanding of the underlying mechanisms that drive normal behaviors and response to disease states is still limited. Advancement in the Neuroscience field and development of therapeutics for related pathologies requires innovative technologies that can provide a dynamic and systematic understanding of the interactions between neurons and neural circuits. In this work, we provide an up-to-date overview of the evolution of neurophotonic approaches in the last 10 years through a multi-source, literature analysis. From an initial corpus of 243 papers retrieved from Scopus, PubMed and WoS databases, we have followed the PRISMA approach to select 56 papers in the area. Following a full-text evaluation of these 56 scientific articles, six main areas of applied research were identified and discussed: (1) Advanced optogenetics, (2) Multimodal neural interfaces, (3) Innovative therapeutics, (4) Imaging devices and probes, (5) Remote operations, and (6) Microfluidic platforms. For each area, the main technologies selected are discussed according to the photonic principles applied, the neuroscience application evaluated and the more indicative results of efficiency and scientific potential. This detailed analysis is followed by an outlook of the main challenges tackled over the last 10 years in the Neurophotonics field, as well as the main technological advances regarding specificity, light delivery, multimodality, imaging, materials and system designs. We conclude with a discussion of considerable challenges for future innovation and translation in Neurophotonics, from light delivery within the brain to physical constraints and data management strategies.

OCTA-500: A retinal dataset for optical coherence tomography angiography study

Optical coherence tomography angiography (OCTA) is a novel imaging modality that has been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels and microvascular systems. However, publicly available OCTA datasets remain scarce. In this paper, we introduce the largest and most comprehensive OCTA dataset dubbed OCTA-500, which contains OCTA imaging under two fields of view (FOVs) from 500 subjects. The dataset provides rich images and annotations including two modalities (OCT/OCTA volumes), six types of projections, four types of text labels (age/gender/eye/disease) and seven types of segmentation labels (large vessel/capillary/artery/vein/2D FAZ/3D FAZ/retinal layers). Then, we propose a multi-object segmentation task called CAVF, which integrates capillary segmentation, artery segmentation, vein segmentation, and FAZ segmentation under a unified framework. In addition, we optimize the 3D-to-2D image projection network (IPN) to IPN-V2 to serve as one of the segmentation baselines. Experimental results demonstrate that IPN-V2 achieves an about 10% mIoU improvement over IPN on CAVF task. Finally, we further study the impact of several dataset characteristics: the training set size, the model input (OCT/OCTA, 3D volume/2D projection), the baseline networks, and the diseases. The dataset and code are publicly available at: https://ieee-dataport.org/open-access/octa-500.

Towards standardising retinal OCT angiography image analysis with open-source toolbox OCTAVA

Quantitative assessment of retinal microvasculature in optical coherence tomography angiography (OCTA) images is important for studying, diagnosing, monitoring, and guiding the treatment of ocular and systemic diseases. However, the OCTA user community lacks universal and transparent image analysis tools that can be applied to images from a range of OCTA instruments and provide reliable and consistent microvascular metrics from diverse datasets. We present a retinal extension to the OCTA Vascular Analyser (OCTAVA) that addresses the challenges of providing robust, easy-to-use, and transparent analysis of retinal OCTA images. OCTAVA is a user-friendly, open-source toolbox that can analyse retinal OCTA images from various instruments. The toolbox delivers seven microvascular metrics for the whole image or subregions and six metrics characterising the foveal avascular zone. We validate OCTAVA using images collected by four commercial OCTA instruments demonstrating robust performance across datasets from different instruments acquired at different sites from different study cohorts. We show that OCTAVA delivers values for retinal microvascular metrics comparable to the literature and reduces their variation between studies compared to their commercial equivalents. By making OCTAVA publicly available, we aim to expand standardised research and thereby improve the reproducibility of quantitative analysis of retinal microvascular imaging. Such improvements will help to better identify more reliable and sensitive biomarkers of ocular and systemic diseases.

Size correction and deep image optimization in optical coherence tomography angiography with structural image-assisted common parts extraction method

Tail artifact elimination is essential in optical coherence tomography angiography (OCTA) for the artifacts will prevent the reconstruction of the 3D vessel image. The tail artifacts of superficial vessels obscure the deep vascular signals and cause the signals at different depths to mix with each other. Most tail artifact elimination methods can shorten the tails but have difficulty in determining the lower boundary of the vessels. In this letter, we introduce a technique to extract vascular signals with more accurate vascular boundaries. With the help of structural image, our method can reconstruct the 3D image of the vascular network more precisely and perform better in deep areas. The images of vessels of palm are used to compare our new technique with previous common parts extraction method experimentally. The results show that our method removes the tail artifacts more thoroughly and has a significant advantage in imaging deep vessels.

Tail Artifact Removal via Transmittance Effect Subtraction in Optical Coherence Tail Artifact Images

Optical Coherence Tomography Angiography (OCTA) has revolutionized non-invasive, high-resolution imaging of blood vessels. However, the challenge of tail artifacts in OCTA images persists. In response, we present the Tail Artifact Removal via Transmittance Effect Subtraction (TAR-TES) algorithm that effectively mitigates these artifacts. Through a simple physics-based model, the TAR-TES accounts for variations in transmittance within the shallow layers with the vasculature, resulting in the removal of tail artifacts in deeper layers after the vessel. Comparative evaluations with alternative correction methods demonstrate that TAR-TES excels in eliminating these artifacts while preserving the essential integrity of vasculature images. Crucially, the success of the TAR-TES is closely linked to the precise adjustment of a weight constant, underlining the significance of individual dataset parameter optimization. In conclusion, TAR-TES emerges as a powerful tool for enhancing OCTA image quality and reliability in both clinical and research settings, promising to reshape the way we visualize and analyze intricate vascular networks within biological tissues. Further validation across diverse datasets is essential to unlock the full potential of this physics-based solution.

Cortical microvascular blood flow velocity mapping by combining dynamic light scattering optical coherence tomography and two-photon microscopy

Significance

The accurate large-scale mapping of cerebral microvascular blood flow velocity is crucial for a better understanding of cerebral blood flow (CBF) regulation. Although optical imaging techniques enable both high-resolution microvascular angiography and fast absolute CBF velocity measurements in the mouse cortex, they usually require different imaging techniques with independent system configurations to maximize their performances. Consequently, it is still a challenge to accurately combine functional and morphological measurements to co-register CBF speed distribution from hundreds of microvessels with high-resolution microvascular angiograms.

Aim

We propose a data acquisition and processing framework to co-register a large set of microvascular blood flow velocity measurements from dynamic light scattering optical coherence tomography (DLS-OCT) with the corresponding microvascular angiogram obtained using two-photon microscopy (2PM).

Approach

We used DLS-OCT to first rapidly acquire a large set of microvascular velocities through a sealed cranial window in mice and then to acquire high-resolution microvascular angiograms using 2PM. The acquired data were processed in three steps: (i) 2PM angiogram coregistration with the DLS-OCT angiogram, (ii) 2PM angiogram segmentation and graphing, and (iii) mapping of the CBF velocities to the graph representation of the 2PM angiogram.

Results

We implemented the developed framework on the three datasets acquired from the mice cortices to facilitate the coregistration of the large sets of DLS-OCT flow velocity measurements with 2PM angiograms. We retrieved the distributions of red blood cell velocities in arterioles, venules, and capillaries as a function of the branching order from precapillary arterioles and postcapillary venules from more than 1000 microvascular segments.

Conclusions

The proposed framework may serve as a useful tool for quantitative analysis of large microvascular datasets obtained by OCT and 2PM in studies involving normal brain functioning, progression of various diseases, and numerical modeling of the oxygen advection and diffusion in the realistic microvascular networks.

Near-lifespan longitudinal tracking of brain microvascular morphology, topology, and flow in male mice

In age-related neurodegenerative diseases, pathology often develops slowly across the lifespan. As one example, in diseases such as Alzheimer's, vascular decline is believed to onset decades ahead of symptomology. However, challenges inherent in current microscopic methods make longitudinal tracking of such vascular decline difficult. Here, we describe a suite of methods for measuring brain vascular dynamics and anatomy in mice for over seven months in the same field of view. This approach is enabled by advances in optical coherence tomography (OCT) and image processing algorithms including deep learning. These integrated methods enabled us to simultaneously monitor distinct vascular properties spanning morphology, topology, and function of the microvasculature across all scales: large pial vessels, penetrating cortical vessels, and capillaries. We have demonstrated this technical capability in wild-type and 3xTg male mice. The capability will allow comprehensive and longitudinal study of a broad range of progressive vascular diseases, and normal aging, in key model systems.

Quantitative optical coherence microscopy of neuron morphology in human entorhinal cortex

Introduction

The size and shape of neurons are important features indicating aging and the pathology of neurodegenerative diseases. Despite the significant advances of optical microscopy, quantitative analysis of the neuronal features in the human brain remains largely incomplete. Traditional histology on thin slices bears tremendous distortions in three-dimensional reconstruction, the magnitude of which are often greater than the structure of interest. Recently development of tissue clearing techniques enable the whole brain to be analyzed in small animals; however, the application in the human remains challenging.

Methods

In this study, we present a label-free quantitative optical coherence microscopy (OCM) technique to obtain the morphological parameters of neurons in human entorhinal cortex (EC). OCM uses the intrinsic back-scattering property of tissue to identify individual neurons in 3D. The area, length, width, and orientation of individual neurons are quantified and compared between layer II and III in EC.

Results

The high-resolution mapping of neuron size, shape, and orientation shows significant differences between layer II and III neurons in EC. The results are validated by standard Nissl staining of the same samples.

Discussion

The quantitative OCM technique in our study offers a new solution to analyze variety of neurons and their organizations in the human brain, which opens new insights in advancing our understanding of neurodegenerative diseases.

Adaptive dynamic analysis-based optical coherence tomography angiography for blood vessel projection artifact suppression

Optical coherence tomography angiography (OCTA) for blood vessel 3-D structure imaging suffers from blood vessel projection artifacts/tail artifacts when using a long decorrelation time (e.g., repeat B-scan acquisition in regular OCTA) or loss of micro vessel signal when using a short decorrelation time. In this work, we developed an adaptive first-order field autocorrelation function (g₁) analysis-based technique to suppress the projection artifacts under macro vessels while enhancing the dynamic signal of micro vessels. The proposed method is based on the differences of the decorrelation rate and the phase variations of g₁ between the vessel voxels and the artifacts regions. A short or long decorrelation time was applied to obtain the dynamic index of the projection artifacts region or the blood vessel region, respectively. Compared to the slab subtraction-based post-image processing-based techniques, the proposed approach addresses this problem on a physical basis and shows the ability to suppress the projection artifacts while enhancing the detection of the micro vessels.

Tail artifacts removal of three-dimensional optical coherence tomography angiography with common parts extraction method

In optical coherence tomography angiography (OCTA), each blood vessel has a tail artifact. These tails of superficial vessels will shadow underlying the deep vascular images and make it difficult to reconstruct the three-dimensional (3D) image of the vessels. As 3D structure can provide much more information than two-dimensional (2D) images, it is important to develop a method to remove the artifacts. In this letter, we introduce an image processing technique based on common parts extraction to remove the artifacts. With the help of subtraction operation and erode operation, our method can reconstruct the 3D image of vascular network by extracting the common parts of adjacent B-Scan OCTA images. Vessels of palm are used as samples to experimentally demonstrate our technique. In the 3D image, we can see the interesting phenomenon that the ends of the blood vessels which close to the surface of the skin point toward the surface.

Towards standardizing retinal optical coherence tomography angiography: a review

The visualization and assessment of retinal microvasculature are important in the study, diagnosis, monitoring, and guidance of treatment of ocular and systemic diseases. With the introduction of optical coherence tomography angiography (OCTA), it has become possible to visualize the retinal microvasculature volumetrically and without a contrast agent. Many lab-based and commercial clinical instruments, imaging protocols and data analysis methods and metrics, have been applied, often inconsistently, resulting in a confusing picture that represents a major barrier to progress in applying OCTA to reduce the burden of disease. Open data and software sharing, and cross-comparison and pooling of data from different studies are rare. These inabilities have impeded building the large databases of annotated OCTA images of healthy and diseased retinas that are necessary to study and define characteristics of specific conditions. This paper addresses the steps needed to standardize OCTA imaging of the human retina to address these limitations. Through review of the OCTA literature, we identify issues and inconsistencies and propose minimum standards for imaging protocols, data analysis methods, metrics, reporting of findings, and clinical practice and, where this is not possible, we identify areas that require further investigation. We hope that this paper will encourage the unification of imaging protocols in OCTA, promote transparency in the process of data collection, analysis, and reporting, and facilitate increasing the impact of OCTA on retinal healthcare delivery and life science investigations.

Deep Learning and Simulation for the Estimation of Red Blood Cell Flux With Optical Coherence Tomography

We present a deep learning and simulation-based method to measure cortical capillary red blood cell (RBC) flux using Optical Coherence Tomography (OCT). This method is more accurate than the traditional peak-counting method and avoids any user parametrization, such as a threshold choice. We used data that was simultaneously acquired using OCT and two-photon microscopy to uncover the distribution of parameters governing the height, width, and inter-peak time of peaks in OCT intensity associated with the passage of RBCs. This allowed us to simulate thousands of time-series examples for different flux values and signal-to-noise ratios, which we then used to train a 1D convolutional neural network (CNN). The trained CNN enabled robust measurement of RBC flux across the entire network of hundreds of capillaries.

Neurophotonic tools for microscopic measurements and manipulation: status report

Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.

Near-Lifespan Tracking of Cerebral Microvascular Degeneration in Aging to Alzheimer’s Continuum

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder affecting millions of people worldwide and is currently incurable. As the population ages, AD and related dementia are becoming the biggest epidemic in medical history: the number of people aged 65 and older with AD is projected to increase between two- and three-fold by 2050. Imaging and biomarker studies suggest that the pathophysiological processes of AD begin more than a decade before the diagnosis of dementia, opening the possibility of early, preemptive prediction. For accurate prediction, it is important although challenging to fully understand how multiple etiologies and age-related prodromal processes contribute to the onset of Alzheimer’s continuum, across a long period comparable to the lifespan. Addressing this challenge was one of the overarching transformative concepts at the 2015 AD Research Summit, “to develop new programs on systems biology and integrative physiology to gain a deeper understanding of the complex biology of the disease.”

Among other factors, cerebral microvascular degeneration (CMD) may play a key role in the onset and development of Alzheimer’s continuum, potentially prior to, along with, or independently of the beta-amyloid (Aβ) accumulation. Despite its importance for early detection and as a therapeutic target for early intervention, it is unknown whether CMD is a causal factor for AD pathogenesis or an early consequence of multifactorial conditions that lead to AD at a later stage. Here, this Viewpoint suggests that we should fill two critical knowledge gaps: (1) Temporal relationships between various CMDs and other key factors before/during/after the onset of Alzheimer’s continuum have not been established; (2) Little integrative study down to the capillary vessel level has been conducted on how individual defects in various microvascular structural and flow properties distinctly correlate with and/or contribute to neuronal degeneration. As the first step toward filling these gaps, I propose utilizing recent advances in microscopic imaging and image analysis techniques to longitudinally track a comprehensive set of CMDs over the lifespan in model animals, along with Aβ, tau, neuronal degeneration, and cognitive impairment when possible.

OCTAVA: An open-source toolbox for quantitative analysis of optical coherence tomography angiography images

Optical coherence tomography angiography (OCTA) performs non-invasive visualization and characterization of microvasculature in research and clinical applications mainly in ophthalmology and dermatology. A wide variety of instruments, imaging protocols, processing methods and metrics have been used to describe the microvasculature, such that comparing different study outcomes is currently not feasible. With the goal of contributing to standardization of OCTA data analysis, we report a user-friendly, open-source toolbox, OCTAVA (OCTA Vascular Analyzer), to automate the pre-processing, segmentation, and quantitative analysis of en face OCTA maximum intensity projection images in a standardized workflow. We present each analysis step, including optimization of filtering and choice of segmentation algorithm, and definition of metrics. We perform quantitative analysis of OCTA images from different commercial and non-commercial instruments and samples and show OCTAVA can accurately and reproducibly determine metrics for characterization of microvasculature. Wide adoption could enable studies and aggregation of data on a scale sufficient to develop reliable microvascular biomarkers for early detection, and to guide treatment, of microvascular disease.

Deep Learning in Biomedical Optics

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.