Methods to label, image, and analyze the complex structural architectures of microvascular networks

Revealing the complexity of meniscus microvasculature through 3D visualization and analysis

Three-dimensional information is essential for a proper understanding of the healing potential of the menisci and their overall role in the knee joint. However, to date, the study of meniscal vascularity has relied primarily on two-dimensional imaging techniques. Here we present a method to elucidate the intricate 3D meniscal vascular network, revealing its spatial arrangement, connectivity and density. A polymerizing contrast agent was injected into the femoral artery of human cadaver legs, and the meniscal microvasculature was examined using micro-computed tomography at different levels of detail and resolution. The 3D vascular network was quantitatively assessed in a zone-base analysis using parameters such as diameter, length, tortuosity, and branching patterns. The results of this study revealed distinct vascular patterns within the meniscus, with the highest vascular volume found in the outer perimeniscal zone. Variations in vascular parameters were found between the different circumferential and radial meniscal zones. Moreover, through state-of-the-art 3D visualization using micro-CT, this study highlighted the importance of spatial resolution in accurately characterizing the vascular network. These findings, both from this study and from future research using this technique, improve our understanding of microvascular distribution, which may lead to improved therapeutic strategies.

Arterio-venous Anastomoses of the Sucquet-Hoyer Type: Complexity and Distribution in the Human Dermis

Our study aims at providing detailed information on numbers, form, and spatial distribution of arterio-venous anastomoses of the Sucquet-Hoyer type in the dermis of the nail bed, nail fold corner, thumb pad, arm, nose, glabella, lip, and ear. It further aims at providing a system, which relies on objective morphologic criteria for classifying Sucquet-Hoyer canals (SHCs). Using high-resolution episcopic microscopy (HREM), digital volume data of eight samples of each skin region were produced. Virtual three-dimensional (3D) models of the dermally located SHCs were created, and their 3D tortuosity (τ) values were determined. Dermal SHCs were identified in all 24 finger samples and in 1 lip sample. Beneath a field of 2 × 2 mm2, an average of four were located in the nail bed, three in the dermis of the thumb pad, and one in the dermis of the nail fold corner. Only a single dermal SHC was found in one lip sample. No SHCs were observed in the dermis of the other samples. The τ values of the SHCs ranged from 1.11 to 10. Building on these values, a classification system was designed, which distinguishes four SHC classes. The dermal distribution of the SHCs of different classes was similar in all specimens.

Dimension-based quantification of aging-associated cerebral microvasculature determined by optical coherence tomography and two-photon microscopy

Cerebral microvascular health is a key biomarker for the study of natural aging and associated neurological diseases. Our aim is to quantify aging-associated change of microvasculature at diverse dimensions in mice brain. We used optical coherence tomography (OCT) and two-photon microscopy (TPM) to obtain nonaged and aged C57BL/6J mice cerebral microvascular images in vivo. Our results indicated that artery & vein, arteriole & venule, and capillary from nonaged and aged mice showed significant differences in density, diameter, complexity, perimeter, and tortuosity. OCT angiography and TPM provided the comprehensive quantification for arteriole and venule via compensating the limitation of each modality alone. We further demonstrated that arteriole and venule at specific dimensions exhibited negative correlations in most quantification analyses between nonaged and aged mice, which indicated that TPM and OCT were able to offer complementary vascular information to study the change of cerebral blood vessels in aging.

Angiogenesis-on-a-chip coupled with single-cell RNA sequencing reveals spatially differential activations of autophagy along angiogenic sprouts

Several functions of autophagy associated with proliferation, differentiation, and migration of endothelial cells have been reported. Due to lack of models recapitulating angiogenic sprouting, functional heterogeneity of autophagy in endothelial cells along angiogenic sprouts remains elusive. Here, we apply an angiogenesis-on-a-chip to reconstruct 3D sprouts with clear endpoints. We perform single-cell RNA sequencing of sprouting endothelial cells from our chip to reveal high activation of autophagy in two endothelial cell populations- proliferating endothelial cells in sprout basements and stalk-like endothelial cells near sprout endpoints- and further the reciprocal expression pattern of autophagy-related genes between stalk- and tip-like endothelial cells near sprout endpoints, implying an association of autophagy with tip-stalk cell specification. Our results suggest a model describing spatially differential roles of autophagy: quality control of proliferating endothelial cells in sprout basements for sprout elongation and tip-stalk cell specification near sprout endpoints, which may change strategies for developing autophagy-based anti-angiogenic therapeutics.

Vessel Metrics: A software tool for automated analysis of vascular structure in confocal imaging

Images contain a wealth of information that is often under analyzed in biological studies. Developmental models of vascular disease are a powerful way to quantify developmentally regulated vessel phenotypes to identify the roots of the disease process. We present vessel Metrics, a software tool specifically designed to analyze developmental vascular microscopy images that will expedite the analysis of vascular images and provide consistency between research groups. We developed a segmentation algorithm that robustly quantifies different image types, developmental stages, organisms, and disease models at a similar accuracy level to a human observer. We validate the algorithm on confocal, lightsheet, and two photon microscopy data in a zebrafish model expressing fluorescent protein in the endothelial nuclei. The tool accurately segments data taken by multiple scientists on varying microscopes. We validate vascular parameters such as vessel density, network length, and diameter, across developmental stages, genetic mutations, and drug treatments, and show a favorable comparison to other freely available software tools. Additionally, we validate the tool in a mouse model. Vessel Metrics reduces the time to analyze experimental results, improves repeatability within and between institutions, and expands the percentage of a given vascular network analyzable in experiments.

A Comprehensive Look at In Vitro Angiogenesis Image Analysis Software

One of the complex challenges faced presently by tissue engineering (TE) is the development of vascularized constructs that accurately mimic the extracellular matrix (ECM) of native tissue in which they are inserted to promote vessel growth and, consequently, wound healing and tissue regeneration. TE technique is characterized by several stages, starting from the choice of cell culture and the more appropriate scaffold material that can adequately support and supply them with the necessary biological cues for microvessel development. The next step is to analyze the attained microvasculature, which is reliant on the available labeling and microscopy techniques to visualize the network, as well as metrics employed to characterize it. These are usually attained with the use of software, which has been cited in several works, although no clear standard procedure has been observed to promote the reproduction of the cell response analysis. The present review analyzes not only the various steps previously described in terms of the current standards for evaluation, but also surveys some of the available metrics and software used to quantify networks, along with the detection of analysis limitations and future improvements that could lead to considerable progress for angiogenesis evaluation and application in TE research.

Dermal features derived from optoacoustic tomograms via machine learning correlate microangiopathy phenotypes with diabetes stage

Skin microangiopathy has been associated with diabetes. Here we show that skin-microangiopathy phenotypes in humans can be correlated with diabetes stage via morphophysiological cutaneous features extracted from raster-scan optoacoustic mesoscopy (RSOM) images of skin on the leg. We obtained 199 RSOM images from 115 participants (40 healthy and 75 with diabetes), and used machine learning to segment skin layers and microvasculature to identify clinically explainable features pertaining to different depths and scales of detail that provided the highest predictive power. Features in the dermal layer at the scale of detail of 0.1-1 mm (such as the number of junction-to-junction branches) were highly sensitive to diabetes stage. A 'microangiopathy score' compiling the 32 most-relevant features predicted the presence of diabetes with an area under the receiver operating characteristic curve of 0.84. The analysis of morphophysiological cutaneous features via RSOM may allow for the discovery of diabetes biomarkers in the skin and for the monitoring of diabetes status.

Long-term assessment of cutaneous inflammation and treatment using optical resolution photoacoustic microscopy

Cutaneous inflammation is an acute skin disease characterized by edema and vascular hyperplasia. Longitudinal monitoring of vasculature is crucial for studying the development of inflammation and evaluating the therapeutic efficacy of drugs. Optical-resolution photoacoustic microscopy (OR-PAM) is a hybrid imaging tool for non-invasive and label-free visualization of microcirculations with a capillary-scale spatial resolution. In this study, we assess the feasibility of OR-PAM for long-term monitoring of vascular changes in 12-O-Tetradecanoylphorbol-13-Acetate (TPA)-induced mouse models, as well as the corresponding treatment process. Quantitative vascular evaluation is conducted based on derived key parameters, including vessel length, branchpoint number, vessel area fraction, vessel diameter, fractal dimension, vessel tortuosity and ear thickness, which reveal that vascular morphological changes are highly dependent on the concentration of TPA and existence of therapeutic drugs. Furthermore, the results show the potential of OR-PAM in the clinical management of inflammation and as an effective tool to evaluate vascular responses to pharmacological interventions in vivo.

Evaluation of the Morphological and Biological Functions of Vascularized Microphysiological Systems with Supervised Machine Learning

Vascularized microphysiological systems and organoids are contemporary preclinical experimental platforms representing human tissue or organ function in health and disease. While vascularization is emerging as a necessary physiological organ-level feature required in most such systems, there is no standard tool or morphological metric to measure the performance or biological function of vascularized networks within these models. Further, the commonly reported morphological metrics may not correlate to the network's biological function-oxygen transport. Here, a large library of vascular network images was analyzed by the measure of each sample's morphology and oxygen transport potential. The oxygen transport quantification is computationally expensive and user-dependent, so machine learning techniques were examined to generate regression models relating morphology to function. Principal component and factor analyses were applied to reduce dimensionality of the multivariate dataset, followed by multiple linear regression and tree-based regression analyses. These examinations reveal that while several morphological data relate poorly to the biological function, some machine learning models possess a relatively improved, but still moderate predictive potential. Overall, random forest regression model correlates to the biological function of vascular networks with relatively higher accuracy than other regression models.

Quantification of vascular morphology in optical coherence tomography angiography in primary open angle glaucoma

Purpose

To quantitatively measure and compare the vascular morphology in healthy eyes and eyes with primary open-angle glaucoma (POAG) using optical coherence tomography angiography (OCTA) scans.

Methods

This is a retrospective and cross-sectional study which include healthy individuals and individuals with POAG that underwent OCTA imaging at an academic center's glaucoma clinic. We analyzed OCTA scans of the macula and optic nerve head (ONH) of one eye from each subject to quantitatively measure vessel density (VD), vessel length density (VLD), and branchpoint density (BPD). We compared these 3 parameters between the healthy and POAG groups and used logistic regression classification models to determine their diagnostic value in differentiating healthy and glaucomatous eyes.

Results

We included 49 healthy subjects and 49 subjects with POAG. After age-adjusted analysis, the parameters of VD, VLD, and BPD were significantly reduced in eyes with POAG (P ​< ​0.001) in all scan layers and most significantly around the ONH. The parameter with the best performances were radial peripapillary capillary (RPC) VD [AUC (areas under the curve): 0.939 (0.891, 0.987)] which had statistically higher performances (P ​< ​0.05) than parameters in the superficial or deep layers. All 3 parameters in the RPC layer had statistically similar performances.

Conclusions

We found that VD, VLD, and BPD were reduced in glaucomatous eyes. The morphologic parameters of VLD and BPD had similar performances to the traditional parameter of VD in RPC layers. Our results suggest that vascular morphology parameters may provide additional value in the diagnosis and evaluation of glaucoma.

Q-VAT: Quantitative Vascular Analysis Tool

As our imaging capability increase, so does our need for appropriate image quantification tools. Quantitative Vascular Analysis Tool (Q-VAT) is an open-source software, written for Fiji (ImageJ), that perform automated analysis and quantification on large two-dimensional images of whole tissue sections. Importantly, it allows separation of the vessel measurement based on diameter, allowing the macro- and microvasculature to be quantified separately. To enable analysis of entire tissue sections on regular laboratory computers, the vascular network of large samples is analyzed in a tile-wise manner, significantly reducing labor and bypassing several limitations related to manual quantification. Double or triple-stained slides can be analyzed, with a quantification of the percentage of vessels where the staining's overlap. To demonstrate the versatility, we applied Q-VAT to obtain morphological read-outs of the vasculature network in microscopy images of whole-mount immuno-stained sections of various mouse tissues.

Digital labeling for 3D histology: segmenting blood vessels without a vascular contrast agent using deep learning

Recent advances in optical tissue clearing and three-dimensional (3D) fluorescence microscopy have enabled high resolution in situ imaging of intact tissues. Using simply prepared samples, we demonstrate here "digital labeling," a method to segment blood vessels in 3D volumes solely based on the autofluorescence signal and a nuclei stain (DAPI). We trained a deep-learning neural network based on the U-net architecture using a regression loss instead of a commonly used segmentation loss to achieve better detection of small vessels. We achieved high vessel detection accuracy and obtained accurate vascular morphometrics such as vessel length density and orientation. In the future, such digital labeling approach could easily be transferred to other biological structures.

Evaluation of the morphological and biological functions of vascularized microphysiological systems with supervised machine learning

Vascularized microphysiological systems and organoids are contemporary preclinical experimental platforms representing human tissue or organ function in health and disease. While vascularization is emerging as a necessary physiological organ-level feature required in most such systems, there is no standard tool or morphological metric to measure the performance or biological function of vascularized networks within these models. Further, the commonly reported morphological metrics may not correlate to the network's biological function - oxygen transport. Here, a large library of vascular network images was analyzed by the measure of each sample's morphology and oxygen transport potential. The oxygen transport quantification is computationally expensive and user-dependent, so machine learning techniques were examined to generate regression models relating morphology to function. Principal component and factor analyses were applied to reduce dimensionality of the multivariate dataset, followed by multiple linear regression and tree-based regression analyses. These examinations reveal that while several morphological data relate poorly to the biological function, some machine learning models possess a relatively improved, but still moderate predictive potential. Overall, random forest regression model correlates to the biological function of vascular networks with relatively higher accuracy than other regression models.

Histological Methods to Assess Skeletal Muscle Degeneration and Regeneration in Duchenne Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is a progressive disease caused by the loss of function of the protein dystrophin. This protein contributes to the stabilisation of striated cells during contraction, as it anchors the cytoskeleton with components of the extracellular matrix through the dystrophin-associated protein complex (DAPC). Moreover, absence of the functional protein affects the expression and function of proteins within the DAPC, leading to molecular events responsible for myofibre damage, muscle weakening, disability and, eventually, premature death. Presently, there is no cure for DMD, but different treatments help manage some of the symptoms. Advances in genetic and exon-skipping therapies are the most promising intervention, the safety and efficiency of which are tested in animal models. In addition to in vivo functional tests, ex vivo molecular evaluation aids assess to what extent the therapy has contributed to the regenerative process. In this regard, the later advances in microscopy and image acquisition systems and the current expansion of antibodies for immunohistological evaluation together with the development of different spectrum fluorescent dyes have made histology a crucial tool. Nevertheless, the complexity of the molecular events that take place in dystrophic muscles, together with the rise of a multitude of markers for each of the phases of the process, makes the histological assessment a challenging task. Therefore, here, we summarise and explain the rationale behind different histological techniques used in the literature to assess degeneration and regeneration in the field of dystrophinopathies, focusing especially on those related to DMD.

Comprehensive molecular and morphological resolution of blubber stratification in a deep-diving, fasting-adapted seal

Blubber is a modified subcutaneous adipose tissue in marine mammals that provides energy storage, thermoregulation, hydrodynamic locomotion, and buoyancy. Blubber displays vertical stratification by lipid content, fatty acid composition, and vascularization, leading to the assumption that deeper blubber layers are metabolically active, while superficial layers are mainly structural and thermoregulatory. However, few studies have examined functional stratification of marine mammal blubber directly, especially in pinnipeds. We characterized morphological and transcriptional differences across blubber layers in the northern elephant seal, a deep-diving and fasting-adapted phocid. We collected blubber from seals early in their fasting period and divided blubber cores into three similarly sized portions. We hypothesized that the innermost blubber portion would have higher 1) heterogeneity in adipocyte size, 2) microvascular density, and 3) expression of genes associated with metabolism and hormone signaling than outer blubber. We found that adipocyte area and variance increased from outermost (skin-adjacent) to innermost (muscle-adjacent) blubber layers, suggesting that inner blubber has a higher capacity for lipid storage and turnover than outer blubber. Inner blubber had a higher proportion of CD144+ endothelial cells, suggesting higher microvascular density. In contrast, outer blubber had a higher proportion of CD4+ immune cells than inner blubber, suggesting higher capacity for response to tissue injury. Transcriptome analysis identified 61 genes that were differentially expressed between inner and outer blubber layers, many of which have not been studied previously in marine mammals. Based on known functions of these genes in other mammals, we suggest that inner blubber has potentially higher 1) adipogenic capacity, 2) cellular diversity, and 3) metabolic and neuroendocrine signaling activity, while outer blubber may have higher 1) extracellular matrix synthesis activity and 2) responsiveness to pathogens and cell stressors. We further characterized expression of nine genes of interest identified by transcriptomics and two adipokines with higher precision across blubber layers using targeted assays. Our study provides functional insights into stratification of blubber in marine mammals and a molecular key, including CD144, CD4, HMGCS2, GABRG2, HCAR2, and COL1A2, for distinguishing blubber layers for physiological and functional studies in seals.

Hessian filter-assisted full diameter at half maximum (FDHM) segmentation and quantification method for optical-resolution photoacoustic microscopy

Optical-resolution photoacoustic microscopy has been validated as an ideal tool for angiographic studies. Quantitative vascular analysis reveals critical information where vessel segmentation plays the key step. The comm-only used Hessian filter method suffers from varying accuracy due to the multi-kernel strategy. In this work, we developed a Hessian filter-assisted, adaptive thresholding vessel segmentation algorithm. Its performance is validated by a digital phantom and in vivo images which demonstrates a superior and consistent accuracy of 0.987 regardless of kernel selection. Subtle vessel change detection is further tested in two longitudinal studies on blood pressure agents. In the antihypotensive case, the proposed method detected a twice larger vasoconstriction over the Hessian filter method. In the antihypertensive case, the proposed method detected a vasodilation of 21.2%, while the Hessian filter method failed in change detection. The proposed algorithm may further push the limit of quantitative imaging on angiographic applications.

Mechanical regulation of signal transduction in angiogenesis

Biophysical and biochemical cues work in concert to regulate angiogenesis. These cues guide angiogenesis during development and wound healing. Abnormal cues contribute to pathological angiogenesis during tumor progression. In this review, we summarize the known signaling pathways involved in mechanotransduction important to angiogenesis. We discuss how variation in the mechanical microenvironment, in terms of stiffness, ligand availability, and topography, can modulate the angiogenesis process. We also present an integrated view on how mechanical perturbations, such as stretching and fluid shearing, alter angiogenesis-related signal transduction acutely, leading to downstream gene expression. Tissue engineering-based approaches to study angiogenesis are reviewed too. Future directions to aid the efforts in unveiling the comprehensive picture of angiogenesis are proposed.

Quantitative Characterization of Age-Related Changes in Peripheral Vessels of a Human Palm Using Raster-Scan Optoacoustic Angiography

The analysis of age-related changes in skin vessels based on optoacoustic angiographic images during the in vivo skin monitoring of healthy volunteers at different ages is reported. As a result of a quantitative analysis of the three-dimensional OA images, the age-associated differences in the following image parameters were revealed: image intensity, ratio of blood content at different characteristics depths, total vessel length, and number of branches. The reported approach can be effectively employed for automatic assessment and monitoring of age-related vascular changes in the skin and underlying tissues.

Quantification of vascular networks in photoacoustic mesoscopy

Mesoscopic photoacoustic imaging (PAI) enables non-invasive visualisation of tumour vasculature. The visual or semi-quantitative 2D measurements typically applied to mesoscopic PAI data fail to capture the 3D vessel network complexity and lack robust ground truths for assessment of accuracy. Here, we developed a pipeline for quantifying 3D vascular networks captured using mesoscopic PAI and tested the preservation of blood volume and network structure with topological data analysis. Ground truth data of in silico synthetic vasculatures and a string phantom indicated that learning-based segmentation best preserves vessel diameter and blood volume at depth, while rule-based segmentation with vesselness image filtering accurately preserved network structure in superficial vessels. Segmentation of vessels in breast cancer patient-derived xenografts (PDXs) compared favourably to ex vivo immunohistochemistry. Furthermore, our findings underscore the importance of validating segmentation methods when applying mesoscopic PAI as a tool to evaluate vascular networks in vivo.

Analytical Approaches for the Segmentation of the Zebrafish Brain Vasculature

With advancements in imaging techniques, data visualization allows new insights into fundamental biological processes of development and disease. However, although biomedical science is heavily reliant on imaging data, interpretation of datasets is still often based on subjective visual assessment rather than rigorous quantitation. This overview presents steps to validate image processing and segmentation using the zebrafish brain vasculature data acquired with light sheet fluorescence microscopy as a use case. Blood vessels are of particular interest to both medical and biomedical science. Specific image enhancement filters have been developed that enhance blood vessels in imaging data prior to segmentation. Using the Sato enhancement filter as an example, we discuss how filter application can be evaluated and optimized. Approaches from the medical field such as simulated, experimental, and augmented datasets can be used to gain the most out of the data at hand. Using such datasets, we provide an overview of how biologists and data analysts can assess the accuracy, sensitivity, and robustness of their segmentation approaches that allow extraction of objects from images. Importantly, even after optimization and testing of a segmentation workflow (e.g., from a particular reporter line to another or between immunostaining processes), its generalizability is often limited, and this can be tested using double-transgenic reporter lines. Lastly, due to the increasing importance of deep learning networks, a comparative approach can be adopted to study their applicability to biological datasets. In summary, we present a broad methodological overview ranging from image enhancement to segmentation with a mixed approach of experimental, simulated, and augmented datasets to assess and validate vascular segmentation using the zebrafish brain vasculature as an example. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. HIGHLIGHTS: Simulated, experimental, and augmented datasets provide an alternative to overcome the lack of segmentation gold standards and phantom models for zebrafish cerebrovascular segmentation. Direct generalization of a segmentation approach to the data for which it was not optimized (e.g., different transgenics or antibody stainings) should be treated with caution. Comparison of different deep learning segmentation methods can be used to assess their applicability to data. Here, we show that the zebrafish cerebral vasculature can be segmented with U-Net-based architectures, which outperform SegNet architectures.

Open-source analysis and visualization of segmented vasculature datasets with VesselVio

Vascular networks are fundamental components of biological systems. Quantitative analysis and observation of the features of these networks can improve our understanding of their roles in health and disease. Recent advancements in imaging technologies have enabled the generation of large-scale vasculature datasets, but barriers to analyzing these datasets remain. Modern analysis options are mainly limited to paid applications or open-source terminal-based software that requires programming knowledge with high learning curves. Here, we describe VesselVio, an open-source application developed to analyze and visualize pre-binarized vasculature datasets and pre-constructed vascular graphs. Vasculature datasets and graphs can be loaded with annotations and processed with custom parameters. Here, the program is tested on ground-truth datasets and is compared with current pipelines. The utility of VesselVio is demonstrated by the analysis of multiple formats of 2D and 3D datasets acquired with several imaging modalities, including annotated mouse whole-brain vasculature volumes.

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.

Non-invasive longitudinal imaging of VEGF-induced microvascular alterations in skin wounds

Background: Microcirculation is essential for skin homeostasis and repair. A variety of growth factors have been identified as important regulators of wound healing. However, direct observation and longitudinal monitoring of skin remodeling in an unperturbed in vivo environment remains challenging.

Methods: We report on non-invasive longitudinal imaging of the wound healing process in transgenic mice overexpressing vascular endothelial growth factor A (VEGF-A) in keratinocytes by means of large-scale optoacoustic microscopy (LSOM). This rapid, label-free, high throughput intravital microscopy method averts the use of dorsal skin-fold chambers, allowing for fully non-invasive repeated imaging of intact wounds with capillary resolution over field-of-view spanning several centimeters.

Results: We observed VEGF-driven enhancement of dermal vascularization in ears, dorsal skin and healing wounds and quantified the hemoglobin content, fill fraction, vessel diameter and tortuosity. The in vivo findings were further corroborated by detailed side-by-side classical histological whole-mount vascular stainings and pan-endothelial CD31 immunofluorescence.

Conclusion: The new approach is suitable for supplementing or replacing the cumbersome histological procedures in a broad range of skin regeneration and tissue engineering applications.

Evaluation of 2D super-resolution ultrasound imaging of the rat renal vasculature using ex vivo micro-computed tomography

Super-resolution ultrasound imaging (SRUS) enables in vivo microvascular imaging of deeper-lying tissues and organs, such as the kidneys or liver. The technique allows new insights into microvascular anatomy and physiology and the development of disease-related microvascular abnormalities. However, the microvascular anatomy is intricate and challenging to depict with the currently available imaging techniques, and validation of the microvascular structures of deeper-lying organs obtained with SRUS remains difficult. Our study aimed to directly compare the vascular anatomy in two in vivo 2D SRUS images of a Sprague-Dawley rat kidney with ex vivo μCT of the same kidney. Co-registering the SRUS images to the μCT volume revealed visually very similar vascular features of vessels ranging from ~ 100 to 1300 μm in diameter and illustrated a high level of vessel branching complexity captured in the 2D SRUS images. Additionally, it was shown that it is difficult to use μCT data of a whole rat kidney specimen to validate the super-resolution capability of our ultrasound scans, i.e., validating the actual microvasculature of the rat kidney. Lastly, by comparing the two imaging modalities, fundamental challenges for 2D SRUS were demonstrated, including the complexity of projecting a 3D vessel network into 2D. These challenges should be considered when interpreting clinical or preclinical SRUS data in future studies.

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.

Ultrasound microvasculature imaging with entropy-based radiality super-resolution (ERSR)

Objective:Microvasculature is highly relevant to the occurrence and development of pathologies such as cancer and diabetes. Ultrasound localization microscopy (ULM) has bypassed the diffraction limit and demonstrated its great potential to provide new imaging modality and establish new diagnostic criteria in clinical application. However, sparse microbubble distribution can be a significant bottleneck for improving temporal resolution, even for further clinical translation. Other important challenges for ULM to tackle in clinic also include high microbubble concentration and low frame rate.Approach:As part of the efforts to facilitate clinical translation, this paper focused on the low frame rate and the high microbubble distribution issue and proposed a new super-resolution imaging strategy called entropy-based radiality super-resolution (ERSR). The feasibility of ERSR is validated with simulations, phantom experiment and contrast-enhanced ultrasound scan of rabbit sciatic nerve with clinical accessible ultrasound system.Main results:ERSR can achieve 10 times improvement in spatial resolution compared to conventional ultrasound imaging, higher temporal resolution (∼10 times higher) and contrast-to-noise ratio under high-density microbubbles, compared with ULM under low-density microbubbles.Significance:We conclude ERSR could be a valuable imaging tool with high spatio-temporal resolution for clinical diagnosis and assessment of diseases potentially.

Exploring the choroidal vascular labyrinth and its molecular and structural roles in health and disease

The choroid is a key player in maintaining ocular homeostasis and plays a role in a variety of chorioretinal diseases, many of which are poorly understood. Recent advances in the field of single-cell RNA sequencing have yielded valuable insights into the properties of choroidal endothelial cells (CECs). Here, we review the role of the choroid in various physiological and pathophysiological mechanisms, focusing on the role of CECs. We also discuss new insights regarding the phenotypic properties of CECs, CEC subpopulations, and the value of measuring transcriptomics in primary CEC cultures derived from post-mortem eyes. In addition, we discuss key phenotypic, structural, and functional differences that distinguish CECs from other endothelial cells such as retinal vascular endothelial cells. Understanding the specific clinical and molecular properties of the choroid will shed new light on the pathogenesis of the broad clinical range of chorioretinal diseases such as age-related macular degeneration, central serous chorioretinopathy and other diseases within the pachychoroid spectrum, uveitis, and diabetic choroidopathy. Although our knowledge is still relatively limited with respect to the clinical features and molecular pathways that underlie these chorioretinal diseases, we summarise new approaches and discuss future directions for gaining new insights into these sight-threatening diseases and highlight new therapeutic strategies such as pluripotent stem cell‒based technologies and gene therapy.

Long-Term Imaging of Wound Angiogenesis with Large Scale Optoacoustic Microscopy

Wound healing is a well-coordinated process, necessitating efficient formation of new blood vessels. Vascularization defects are therefore a major risk factor for chronic, non-healing wounds. The dynamics of mammalian tissue revascularization, vessel maturation, and remodeling remain poorly understood due to lack of suitable in vivo imaging tools. A label-free large-scale optoacoustic microscopy (LSOM) approach is developed for rapid, non-invasive, volumetric imaging of tissue regeneration over large areas spanning up to 50 mm with a depth penetration of 1.5 mm. Vascular networks in dorsal mouse skin and full-thickness excisional wounds are imaged with capillary resolution during the course of healing, revealing previously undocumented views of the angiogenesis process in an unperturbed wound environment. Development of an automatic analysis framework enables the identification of key features of wound angiogenesis, including vessel length, diameter, tortuosity, and angular alignment. The approach offers a versatile tool for preclinical research in tissue engineering and regenerative medicine, empowering label-free, longitudinal, high-throughput, and quantitative studies of the microcirculation in processes associated with normal and impaired vascular remodeling, and analysis of vascular responses to pharmacological interventions in vivo.

Investigation of the Orbital Arterial Distribution Using Image Superimposition to Determine Safe Zones for Retrobulbar Injection and to Prevent Filler Complications

BACKGROUND

Retrobulbar filler injection has recently been considered an ideal method for orbital volume enhancement due to its nontoxic, easily reversible, and noninvasive characteristics. This study determined the arterial distribution in the orbit with the aim of defining a safety zone for retrobulbar filler injections used to enhance the orbital volume.

METHODS

Twenty-seven orbits of 24 formalin-embalmed cadavers were dissected. The orbital arteries were identified after removal of the eyeball, extraocular muscles, and connective tissues. The course of each orbital artery was then recorded in each specimen, and all of the courses were then superimposed to determine the arterial distribution in the orbit.

RESULTS

The superimposition of lined images based on the orbital vasculature of each specimen revealed that the arterial density was highest in the superonasal region and lowest in the inferotemporal region. In particular, orbital arteries were scarce at 8 o'clock and 4 o'clock in the right and left orbits, respectively, and an artery-free zone was demonstrated in the outer part of those directions.

CONCLUSIONS

When performing a transcutaneous retrobulbar injection of filler for orbital volume enhancement, the relative safety zone could be considered to be located at 8 o'clock and 4 o'clock in the right and left orbits, respectively. The detailed topographic information about the arterial distribution in the orbit, provided by the present study, may help oculofacial surgeons to avoid injury to major vessels and decrease the risk of retrobulbar hemorrhage and vision-threatening complications.

Non-Invasive Evaluation of Acute Effects of Tubulin Binding Agents: A Review of Imaging Vascular Disruption in Tumors

Tumor vasculature proliferates rapidly, generally lacks pericyte coverage, and is uniquely fragile making it an attractive therapeutic target. A subset of small-molecule tubulin binding agents cause disaggregation of the endothelial cytoskeleton leading to enhanced vascular permeability generating increased interstitial pressure. The resulting vascular collapse and ischemia cause downstream hypoxia, ultimately leading to cell death and necrosis. Thus, local damage generates massive amplification and tumor destruction. The tumor vasculature is readily accessed and potentially a common target irrespective of disease site in the body. Development of a therapeutic approach and particularly next generation agents benefits from effective non-invasive assays. Imaging technologies offer varying degrees of sophistication and ease of implementation. This review considers technological strengths and weaknesses with examples from our own laboratory. Methods reveal vascular extent and patency, as well as insights into tissue viability, proliferation and necrosis. Spatiotemporal resolution ranges from cellular microscopy to single slice tomography and full three-dimensional views of whole tumors and measurements can be sufficiently rapid to reveal acute changes or long-term outcomes. Since imaging is non-invasive, each tumor may serve as its own control making investigations particularly efficient and rigorous. The concept of tumor vascular disruption was proposed over 30 years ago and it remains an active area of research.

Tissue clearing and imaging methods for cardiovascular development

Tissue imaging in 3D using visible light is limited and various clearing techniques were developed to increase imaging depth, but none provides universal solution for all tissues at all developmental stages. In this review, we focus on different tissue clearing methods for 3D imaging of heart and vasculature, based on chemical composition (solvent-based, simple immersion, hyperhydration, and hydrogel embedding techniques). We discuss in detail compatibility of various tissue clearing techniques with visualization methods: fluorescence preservation, immunohistochemistry, nuclear staining, and fluorescent dyes vascular perfusion. We also discuss myocardium visualization using autofluorescence, tissue shrinking, and expansion. Then we overview imaging methods used to study cardiovascular system and live imaging. We discuss heart and vessels segmentation methods and image analysis. The review covers the whole process of cardiovascular system 3D imaging, starting from tissue clearing and its compatibility with various visualization methods to the types of imaging methods and resulting image analysis.

Vessel tech: a high-accuracy pipeline for comprehensive mouse retinal vasculature characterization

Mouse retinal vasculature is a well-recognized and commonly used animal model for angiogenesis and microvascular remodeling. Morphological features of retinal vasculature reflect the vessel's biological functions, and are critical in understanding the physiological and pathological process of vascular development and disease. Here we developed a comprehensive software, Vessel Tech, using retinal vasculature images of postnatal mice. This pipeline can automatically process retinal vascular images, reconstruct vessel network with high accuracy and assess global and local vascular characteristics based on the recent machine-learning techniques. The development of Vessel Tech provides a powerful tool for vascular biologists.

Image-guided simulation in comparison with laser speckle contrast imaging for full-field observation of blood flow in a microvasculature model

The in vitro reconstruction of the microvascular network model provides a reproducible platform for hemodynamic study with great biological relevance. In the present study, microvascular models with different parametric features were designed under the guidance of Murray's law and derived from representative natural vascular network topography in vivo. Computational fluid dynamics (CFD) was used to numerically simulate blood velocity distributions inside of the designed microvasculature models. Full-field blood flow in the vascular network was visualized in vivo using a laser speckle contrast imaging (LSCI) system, from which the measured relative velocity was compared with CFD computed flow distribution. The results have shown that, in comparison with the simplified flow patterns obtained from idealized geometries, the irregular vascular topography is expected to lead to nonuniform and poor regional blood velocity distribution. The velocity distribution acquired by in vivo LSCI experiment is in good agreement with that of numerical simulation, indicating the technical feasibility of using biomimetic microchannels as a reasonable approximation of the microcirculatory flow conditions. This study provides a new paradigm that can be well suited to the study of microvascular blood flow properties and can further expand to mimic other in-vivo scenarios for accurately recapitulating the physical and hemodynamic environment of the microcirculation.

Extracellular matrix remodeling associated with bleomycin-induced lung injury supports pericyte-to-myofibroblast transition

Of the many origins of pulmonary myofibroblasts, microvascular pericytes are a known source. Prior literature has established the ability of pericytes to transition into myofibroblasts, but provide limited insight into molecular cues that drive this process during lung injury repair and fibrosis. Fibronectin and RGD-binding integrins have long been considered pro-fibrotic factors in myofibroblast biology, and here we test the hypothesis that these known myofibroblast cues coordinate pericyte-to-myofibroblast transitions. Specifically, we hypothesized that αvβ3 integrin engagement on fibronectin induces pericyte transition into myofibroblastic phenotypes in the murine bleomycin lung injury model. Myosin Heavy Chain 11 (Myh11)-CreERT2 lineage tracing in transgenic mice allows identification of cells of pericyte origin and provides a robust tool for isolating pericytes from tissues for further evaluation. We used this murine model to track and characterize pericyte behaviors during tissue repair. The majority of Myh11 lineage-positive cells are positive for the pericyte surface markers, PDGFRβ (55%) and CD146 (69%), and display typical pericyte morphology with spatial apposition to microvascular networks. After intratracheal bleomycin treatment of mice, Myh11 lineage-positive cells showed significantly increased contractile and secretory markers, as well as αv integrin expression. According to RNASeq measurements, many disease and tissue-remodeling genesets were upregulated in Myh11 lineage-positive cells in response to bleomycin-induced lung injury. In vitro, blocking αvβ3 binding through cycloRGDfK prevented expression of the myofibroblastic marker αSMA relative to controls. In response to RGD-containing provisional matrix proteins present in lung injury, pericytes may alter their integrin profile.

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Pericyte lineage model enables study of transdifferentiating pericytes.

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High dimensional flow cytometry used to characterize pulmonary stromal cells

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Pulmonary pericytes express matrix-remodeling genes and proteins in lung injury.

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Myofibroblasts derived from pericytes have active αvβ3 integrin.

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In vitro assay reveals necessity of RGD for pericyte transdifferentiation.

Dapagliflozin Promotes Neovascularization by Improving Paracrine Function of Skeletal Muscle Cells in Diabetic Hindlimb Ischemia Mice Through PHD2/HIF-1α Axis

Diabetes mellitus is associated with a high risk of hindlimb ischemia (HLI) progression and an inevitably poor prognosis, including worse limb salvage and mortality. Skeletal muscle cells can secrete angiogenic factors, which could promote neovascularization and blood perfusion recovery. Thus, paracrine function of skeletal muscle cells, which is aberrant in diabetic conditions, is crucial for therapeutic angiogenesis in diabetic HLI. Dapagliflozin is a well-known anti-hyperglycemia and anti-obesity drug; however, its role in therapeutic angiogenesis is unknown. Herein, we found that dapagliflozin could act as an angiogenesis stimulator in diabetic HLI. We showed that dapagliflozin enhances the viability, proliferation, and migration potentials of skeletal muscle cells and promotes the secretion of multiple angiogenic factors from skeletal muscle cells, most plausibly through PHD2/HIF-1α axis. Furthermore, we demonstrated that conditioned medium from dapagliflozin-treated skeletal muscle cells enhances the proliferation and migration potentials of vascular endothelial and smooth muscle cells, which are two fundamental cells of functional mature vessels. Finally, an in vivo study demonstrated that intramuscular administration of dapagliflozin effectively enhances the formation of mature blood vessels and, subsequently, blood perfusion recovery in diabetic HLI mice. Hence, our results suggest a novel function of dapagliflozin as a potential therapeutic angiogenesis agent for diabetic HLI.

A Comparative Study of Engineered Dermal Templates for Skin Wound Repair in a Mouse Model

Engineered dermal templates have revolutionised the repair and reconstruction of skin defects. Their interaction with the wound microenvironment and linked molecular mediators of wound repair is still not clear. This study investigated the wound bed and acellular "off the shelf" dermal template interaction in a mouse model. Full-thickness wounds in nude mice were grafted with allogenic skin, and either collagen-based or fully synthetic dermal templates. Changes in the wound bed showed significantly higher vascularisation and fibroblast infiltration in synthetic grafts when compared to collagen-based grafts (P ≤ 0.05). Greater tissue growth was associated with higher prostaglandin-endoperoxide synthase 2 (Ptgs2) RNA and cyclooxygenase-2 (COX-2) protein levels in fully synthetic grafts. Collagen-based grafts had higher levels of collagen III and matrix metallopeptidase 2. To compare the capacity to form a double layer skin substitute, both templates were seeded with human fibroblasts and keratinocytes (so-called human skin equivalent or HSE). Mice were grafted with HSEs to test permanent wound closure with no further treatment required. We found the synthetic dermal template to have a significantly greater capacity to support human epidermal cells. In conclusion, the synthetic template showed advantages over the collagen-based template in a short-term mouse model of wound repair.

REAVER: A program for improved analysis of high-resolution vascular network images

Alterations in vascular networks, including angiogenesis and capillary regression, play key roles in disease, wound healing, and development. The spatial structures of blood vessels can be captured through imaging, but effective characterization of network architecture requires both metrics for quantification and software to carry out the analysis in a high‐throughput and unbiased fashion. We present Rapid Editable Analysis of Vessel Elements Routine (REAVER), an open‐source tool that researchers can use to analyze high‐resolution 2D fluorescent images of blood vessel networks, and assess its performance compared to alternative image analysis programs. Using a dataset of manually analyzed images from a variety of murine tissues as a ground‐truth, REAVER exhibited high accuracy and precision for all vessel architecture metrics quantified, including vessel length density, vessel area fraction, mean vessel diameter, and branchpoint count, along with the highest pixel‐by‐pixel accuracy for the segmentation of the blood vessel network. In instances where REAVER's automated segmentation is inaccurate, we show that combining manual curation with automated analysis improves the accuracy of vessel architecture metrics. REAVER can be used to quantify differences in blood vessel architectures, making it useful in experiments designed to evaluate the effects of different external perturbations (eg, drugs or disease states).

Special topics issue: "Complexity in the microcirculation"

This Special Topics Issue of the journal "Microcirculation" presents seven manuscripts spanning multiple perspectives of investigation. The first two manuscripts present technical/analytical approaches to determining and quantifying vascular network structure, and the third presents a methodology for determining intravascular hemodynamics within the in situ microvascular network. The fourth manuscript utilizes complexity analyses to determine changes in microvascular perfusion as a predictor of disease severity, while the fifth study links the changes to perfusion complexity to tissue metabolic demand and potential limitations on mitochondrial metabolism within skeletal muscle. The sixth manuscript further addresses this critical topic, providing a state-of-the-art discussion of skeletal muscle oxygen kinetics and the factors that impact this vital process. The final manuscript outlines the impact of the deletion of Robo4 on the vascular endothelium on microvascular function in white adipose tissue and the potentially beneficial effects for anti-obesity treatment. We hope that this presentation of issues of "Complexity in the Microcirculation" will be beneficial to the reader.

Methods to label, image, and analyze the complex structural architectures of microvascular networks

Microvascular networks play key roles in oxygen transport and nutrient delivery to meet the varied and dynamic metabolic needs of different tissues throughout the body, and their spatial architectures of interconnected blood vessel segments are highly complex. Moreover, functional adaptations of the microcirculation enabled by structural adaptations in microvascular network architecture are required for development, wound healing, and often invoked in disease conditions, including the top eight causes of death in the Unites States. Effective characterization of microvascular network architectures is not only limited by the available techniques to visualize microvessels but also reliant on the available quantitative metrics that accurately delineate between spatial patterns in altered networks. In this review, we survey models used for studying the microvasculature, methods to label and image microvessels, and the metrics and software packages used to quantify microvascular networks. These programs have provided researchers with invaluable tools, yet we estimate that they have collectively attained low adoption rates, possibly due to limitations with basic validation, segmentation performance, and nonstandard sets of quantification metrics. To address these existing constraints, we discuss opportunities to improve effectiveness, rigor, and reproducibility of microvascular network quantification to better serve the current and future needs of microvascular research.