Measuring the velocity of fluorescently labelled red blood cells with a keyhole tracking algorithm

Modelling the Tumour Microenvironment, but What Exactly Do We Mean by "Model"?

The Oxford English Dictionary includes 17 definitions for the word "model" as a noun and another 11 as a verb. Therefore, context is necessary to understand the meaning of the word model. For instance, "model railways" refer to replicas of railways and trains at a smaller scale and a "model student" refers to an exemplary individual. In some cases, a specific context, like cancer research, may not be sufficient to provide one specific meaning for model. Even if the context is narrowed, specifically, to research related to the tumour microenvironment, "model" can be understood in a wide variety of ways, from an animal model to a mathematical expression. This paper presents a review of different "models" of the tumour microenvironment, as grouped by different definitions of the word into four categories: model organisms, in vitro models, mathematical models and computational models. Then, the frequencies of different meanings of the word "model" related to the tumour microenvironment are measured from numbers of entries in the MEDLINE database of the United States National Library of Medicine at the National Institutes of Health. The frequencies of the main components of the microenvironment and the organ-related cancers modelled are also assessed quantitatively with specific keywords. Whilst animal models, particularly xenografts and mouse models, are the most commonly used "models", the number of these entries has been slowly decreasing. Mathematical models, as well as prognostic and risk models, follow in frequency, and these have been growing in use.

Segmentation-based tracking of macrophages in 2D＋time microscopy movies inside a living animal

The automated segmentation and tracking of macrophages during their migration are challenging tasks due to their dynamically changing shapes and motions. This paper proposes a new algorithm to achieve automatic cell tracking in time-lapse microscopy macrophage data. First, we design a segmentation method employing space-time filtering, local Otsu's thresholding, and the SUBSURF (subjective surface segmentation) method. Next, the partial trajectories for cells overlapping in the temporal direction are extracted in the segmented images. Finally, the extracted trajectories are linked by considering their direction of movement. The segmented images and the obtained trajectories from the proposed method are compared with those of the semi-automatic segmentation and manual tracking. The proposed tracking achieved 97.4% of accuracy for macrophage data under challenging situations, feeble fluorescent intensity, irregular shapes, and motion of macrophages. We expect that the automatically extracted trajectories of macrophages can provide pieces of evidence of how macrophages migrate depending on their polarization modes in the situation, such as during wound healing.

Tracking leukocytes in intravital time lapse images using 3D cell association learning network

Leukocytes are key cellular elements of the innate immune system in all vertebrates, which play a crucial role in defending organisms against invading pathogens. Tracking these highly migratory and amorphous cells in in vivo models such as zebrafish embryos is a challenging task in cellular immunology. As temporal and special analysis of these imaging datasets by a human operator is quite laborious, developing an automated cell tracking method is highly in demand. Despite the remarkable advances in cell detection, this field still lacks powerful algorithms to accurately associate the detected cell across time frames. The cell association challenge is mostly related to the amorphous nature of cells, and their complicated motion profile through their migratory paths. To tackle the cell association challenge, we proposed a novel deep-learning-based object linkage method. For this aim, we trained the 3D cell association learning network (3D-CALN) with enough manually labelled paired 3D images of single fluorescent zebrafish's neutrophils from two consecutive frames. Our experiment results prove that deep learning is significantly applicable in cell linkage and particularly for tracking highly mobile and amorphous leukocytes. A comparison of our tracking accuracy with other available tracking algorithms shows that our approach performs well in relation to addressing cell tracking problems.

Cell Tracking Profiler - a user-driven analysis framework for evaluating 4D live-cell imaging data

Accurate measurements of cell morphology and behaviour are fundamentally important for understanding how disease, molecules and drugs affect cell function in vivo Here, by using muscle stem cell (muSC) responses to injury in zebrafish as our biological paradigm, we established a 'ground truth' for muSC behaviour. This revealed that segmentation and tracking algorithms from commonly used programs are error-prone, leading us to develop a fast semi-automated image analysis pipeline that allows user-defined parameters for segmentation and correction of cell tracking. Cell Tracking Profiler (CTP) is a package that runs two existing programs, HK Means and Phagosight within the Icy image analysis suite, to enable user-managed cell tracking from 3D time-lapse datasets to provide measures of cell shape and movement. We demonstrate how CTP can be used to reveal changes to cell behaviour of muSCs in response to manipulation of the cell cytoskeleton by small-molecule inhibitors. CTP and the associated tools we have developed for analysis of outputs thus provide a powerful framework for analysing complex cell behaviour in vivo from 4D datasets that are not amenable to straightforward analysis.

Comparative Study of Contact Repulsion in Control and Mutant Macrophages Using a Novel Interaction Detection

In this paper, a novel method for interaction detection is presented to compare the contact dynamics of macrophages in the Drosophila embryo. The study is carried out by a framework called macrosight, which analyses the movement and interaction of migrating macrophages. The framework incorporates a segmentation and tracking algorithm into analysing the motion characteristics of cells after contact. In this particular study, the interactions between cells is characterised in the case of control embryos and Shot mutants, a candidate protein that is hypothesised to regulate contact dynamics between migrating cells. Statistical significance between control and mutant cells was found when comparing the direction of motion after contact in specific conditions. Such discoveries provide insights for future developments in combining biological experiments with computational analysis.

Macrosight: A Novel Framework to Analyze the Shape and Movement of Interacting Macrophages Using Matlab®

This paper presents a novel software framework, called macrosight, which incorporates routines to detect, track, and analyze the shape and movement of objects, with special emphasis on macrophages. The key feature presented in macrosight consists of an algorithm to assess the changes of direction derived from cell–cell contact, where an interaction is assumed to occur. The main biological motivation is the determination of certain cell interactions influencing cell migration. Thus, the main objective of this work is to provide insights into the notion that interactions between cell structures cause a change in orientation. Macrosight analyzes the change of direction of cells before and after they come in contact with another cell. Interactions are determined when the cells overlap and form clumps of two or more cells. The framework integrates a segmentation technique capable of detecting overlapping cells and a tracking framework into a tool for the analysis of the trajectories of cells before and after they overlap. Preliminary results show promise into the analysis and the hypothesis proposed, and lays the groundwork for further developments. The extensive experimentation and data analysis show, with statistical significance, that under certain conditions, the movement changes before and after an interaction are different from movement in controlled cases.

An automated quantitative image analysis pipeline of in vivo oxidative stress and macrophage kinetics

Macrophage behavior is of great interest in response to tissue injury and promotion of regeneration. With increasing numbers of zebrafish reporter-based assays, new capabilities now exist to characterize macrophage migration, and their responses to biochemical cues, such as reactive oxygen species. Real time detection of macrophage behavior in response to oxidative stress using quantitative measures is currently beyond the scope of commercially available software solutions, presenting a gap in understanding macrophage behavior. To address this gap, we developed an image analysis pipeline solution to provide real time quantitative measures of cellular kinetics and reactive oxygen species content in vivo after tissue injury. This approach, termed Zirmi, differs from current software solutions that may only provide qualitative, single image analysis, or cell tracking solutions. Zirmi is equipped with user-defined algorithm parameters to customize quantitative data measures with visualization checks for an analysis pipeline of time-based changes. Moreover, this pipeline leverages open-source PhagoSight, as an automated keyhole cell tracking solution, to avoid parallel developments and build upon readily available tools. This approach demonstrated standardized space- and time-based quantitative measures of (1) fluorescent probe based oxidative stress and (2) macrophage recruitment kinetic based changes after tissue injury. Zirmi image analysis pipeline performed at execution speeds up to 10-times faster than manual image-based approaches. Automated segmentation methods were comparable to manual methods with a DICE Similarity coefficient > 0.70. Zirmi provides an open-source, quantitative, and non-generic image analysis pipeline. This strategy complements current wide-spread zebrafish strategies, for automated standardizations of analysis and data measures.

Centroid tracking and velocity measurement of white blood cell in video

Automated blood cells tracking system has a vital role as the tracking process reflects the blood cell characteristics and indicates several diseases. Blood cells tracking is challenging due to the non-rigid shapes of the blood cells, and the variability in their videos along with the existence of different moving objects in the blood. To tackle such challenges, we proposed a green star based centroid (GSBC) moving white blood cell (WBC) tracking algorithm to measure its velocity and draw its trajectory. The proposed cell tracking system consists of two stages, namely WBC detection and blob analysis, and fine tuning the tracking process by determine the centroid of the WBC, and mark the centroid for further fine tracking and to exclude the bacteria from the bounding box. Furthermore, the speed and the trajectory of the WBC motion are recorded and plotted. In the experiments, an optical flow technique is compared with the proposed tracking system showing the superiority of the proposed system as the optical flow method failed to track the WBC. The proposed system identified the WBC accurately, while the optical flow identified all other objects lead to its disability to track the WBC.

Understanding the neurovascular unit at multiple scales: Advantages and limitations of multi-photon and functional ultrasound imaging

Developing efficient brain imaging technologies by combining a high spatiotemporal resolution and a large penetration depth is a key step for better understanding the neurovascular interface that emerges as a main pathway to neurodegeneration in many pathologies such as dementia. This review focuses on the advances in two complementary techniques: multi-photon laser scanning microscopy (MPLSM) and functional ultrasound imaging (fUSi). MPLSM has become the gold standard for in vivo imaging of cellular dynamics and morphology, together with cerebral blood flow. fUSi is an innovative imaging modality based on Doppler ultrasound, capable of recording vascular brain activity over large scales (i.e., tens of cubic millimeters) at unprecedented spatial and temporal resolution for such volumes (up to 10μm pixel size at 10kHz). By merging these two technologies, researchers may have access to a more detailed view of the various processes taking place at the neurovascular interface. MPLSM and fUSi are also good candidates for addressing the major challenge of real-time delivery, monitoring, and in vivo evaluation of drugs in neuronal tissue.

Longitudinal imaging of the ageing mouse

Several non-invasive imaging techniques are used to investigate the effect of pathologies and treatments over time in mouse models. Each preclinical in vivo technique provides longitudinal and quantitative measurements of changes in tissues and organs, which are fundamental for the evaluation of alterations in phenotype due to pathologies, interventions and treatments. However, it is still unclear how these imaging modalities can be used to study ageing with mice models. Almost all age related pathologies in mice such as osteoporosis, arthritis, diabetes, cancer, thrombi, dementia, to name a few, can be imaged in vivo by at least one longitudinal imaging modality. These measurements are the basis for quantification of treatment effects in the development phase of a novel treatment prior to its clinical testing. Furthermore, the non-invasive nature of such investigations allows the assessment of different tissue and organ phenotypes in the same animal and over time, providing the opportunity to study the dysfunction of multiple tissues associated with the ageing process. This review paper aims to provide an overview of the applications of the most commonly used in vivo imaging modalities used in mouse studies: micro-computed-tomography, preclinical magnetic-resonance-imaging, preclinical positron-emission-tomography, preclinical single photon emission computed tomography, ultrasound, intravital microscopy, and whole body optical imaging.

A computational framework for particle and whole cell tracking applied to a real biological dataset

Cell tracking is becoming increasingly important in cell biology as it provides a valuable tool for analysing experimental data and hence furthering our understanding of dynamic cellular phenomena. The advent of high-throughput, high-resolution microscopy and imaging techniques means that a wealth of large data is routinely generated in many laboratories. Due to the sheer magnitude of the data involved manual tracking is often cumbersome and the development of computer algorithms for automated cell tracking is thus highly desirable. In this work, we describe two approaches for automated cell tracking. Firstly, we consider particle tracking. We propose a few segmentation techniques for the detection of cells migrating in a non-uniform background, centroids of the segmented cells are then calculated and linked from frame to frame via a nearest-neighbour approach. Secondly, we consider the problem of whole cell tracking in which one wishes to reconstruct in time whole cell morphologies. Our approach is based on fitting a mathematical model to the experimental imaging data with the goal being that the physics encoded in the model is reflected in the reconstructed data. The resulting mathematical problem involves the optimal control of a phase-field formulation of a geometric evolution law. Efficient approximation of this challenging optimal control problem is achieved via advanced numerical methods for the solution of semilinear parabolic partial differential equations (PDEs) coupled with parallelisation and adaptive resolution techniques. Along with a detailed description of our algorithms, a number of simulation results are reported on. We focus on illustrating the effectivity of our approaches by applying the algorithms to the tracking of migrating cells in a dataset which reflects many of the challenges typically encountered in microscopy data.

Quantitative Estimation of Tissue Blood Flow Rate

The rate of blood flow through a tissue (F) is a critical parameter for assessing the functional efficiency of a blood vessel network following angiogenesis. This chapter aims to provide the principles behind the estimation of F, how F relates to other commonly used measures of tissue perfusion, and a practical approach for estimating F in laboratory animals, using small readily diffusible and metabolically inert radio-tracers. The methods described require relatively nonspecialized equipment. However, the analytical descriptions apply equally to complementary techniques involving more sophisticated noninvasive imaging.Two techniques are described for the quantitative estimation of F based on measuring the rate of tissue uptake following intravenous administration of radioactive iodo-antipyrine (or other suitable tracer). The Tissue Equilibration Technique is the classical approach and the Indicator Fractionation Technique, which is simpler to perform, is a practical alternative in many cases. The experimental procedures and analytical methods for both techniques are given, as well as guidelines for choosing the most appropriate method.

Measurement of Retinal Blood Flow Using Fluorescently Labeled Red Blood Cells

Blood flow is a useful indicator of the metabolic state of the retina. However, accurate measurement of retinal blood flow is difficult to achieve in practice. Most existing optical techniques used for measuring blood flow require complex assumptions and calculations. We describe here a simple and direct method for calculating absolute blood flow in vessels of all sizes in the rat retina. The method relies on ultrafast confocal line scans to track the passage of fluorescently labeled red blood cells (fRBCs). The accuracy of the blood flow measurements was verified by (1) comparing blood flow calculated independently using either flux or velocity combined with diameter measurements, (2) measuring total retinal blood flow in arterioles and venules, (3) measuring blood flow at vessel branch points, and (4) measuring changes in blood flow in response to hyperoxic and hypercapnic challenge. Confocal line scans oriented parallel and diagonal to vessels were used to compute fRBC velocity and to examine velocity profiles across the width of vessels. We demonstrate that these methods provide accurate measures of absolute blood flow and velocity in retinal vessels of all sizes.

In vivo flow mapping in complex vessel networks by single image correlation

We describe a novel method (FLICS, FLow Image Correlation Spectroscopy) to extract flow speeds in complex vessel networks from a single raster-scanned optical xy-image, acquired in vivo by confocal or two-photon excitation microscopy. Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details. The flow velocity is obtained by computing the Cross Correlation Function (CCF) of the intensity fluctuations detected in pairs of columns of the image. The analytical expression of the CCF has been derived by applying scanning fluorescence correlation concepts to drifting optically resolved objects and the theoretical framework has been validated in systems of increasing complexity. The power of the technique is revealed by its application to the intricate murine hepatic microcirculatory system where blood flow speed has been mapped simultaneously in several capillaries from a single xy-image and followed in time at high spatial and temporal resolution.

Influence of soluble or matrix-bound isoforms of vascular endothelial growth factor-A on tumor response to vascular-targeted strategies

Antiangiogenic therapy based on blocking the actions of vascular endothelial growth factor-A (VEGF) can lead to "normalization" of blood vessels in both animal and human tumors. Differential expression of VEGF isoforms affects tumor vascular maturity, which could influence the normalization process and response to subsequent treatment. Fibrosarcoma cells expressing only VEGF120 or VEGF188 isoforms were implanted either subcutaneously (s.c.) or in dorsal skin-fold "window" chambers in SCID mice. VEGF120 was associated with vascular fragility and hemorrhage. Tumor-bearing mice were treated with repeat doses of SU5416, an indolinone receptor tyrosine kinase inhibitor with activity against VEGFR-2 and proven preclinical ability to induce tumor vascular normalization. SU5416 reduced vascularization in s.c. implants of both VEGF120 and VEGF188 tumors. However, in the window chamber, SU5416 treatment increased red cell velocity in VEGF120 (representing vascular normalization) but not VEGF188 tumors. SU5416 treatment had no effect on growth or necrosis levels in either tumor type but tended to counteract the increase in interstitial fluid pressure seen with growth of VEGF120 tumors. SU5416 pretreatment resulted in the normally fragile blood vessels in VEGF120-expressing tumors becoming resistant to the vascular damaging effects of the tubulin-binding vascular disrupting agent (VDA), combretastatin A4 3-O-phosphate (CA4P). Thus, vascular normalization induced by antiangiogenic treatment can reduce the efficacy of subsequent VDA treatment. Expression of VEGF120 made tumors particularly susceptible to vascular normalization by SU5416, which in turn made them resistant to CA4P. Therefore, VEGF isoform expression may be useful for predicting response to both antiangiogenic and vascular-disrupting therapy.

PhagoSight: an open-source MATLAB® package for the analysis of fluorescent neutrophil and macrophage migration in a zebrafish model

Neutrophil migration in zebrafish larvae is increasingly used as a model to study the response of these leukocytes to different determinants of the cellular inflammatory response. However, it remains challenging to extract comprehensive information describing the behaviour of neutrophils from the multi-dimensional data sets acquired with widefield or confocal microscopes. Here, we describe PhagoSight, an open-source software package for the segmentation, tracking and visualisation of migrating phagocytes in three dimensions. The algorithms in PhagoSight extract a large number of measurements that summarise the behaviour of neutrophils, but that could potentially be applied to any moving fluorescent cells. To derive a useful panel of variables quantifying aspects of neutrophil migratory behaviour, and to demonstrate the utility of PhagoSight, we evaluated changes in the volume of migrating neutrophils. Cell volume increased as neutrophils migrated towards the wound region of injured zebrafish. PhagoSight is openly available as MATLAB® m-files under the GNU General Public License. Synthetic data sets and a comprehensive user manual are available from http://www.phagosight.org.

Accurate blood flow measurements: are artificial tracers necessary?

Imaging-based blood flow measurement techniques, such as particle image velocimetry, have become an important tool in cardiovascular research. They provide quantitative information about blood flow, which benefits applications ranging from developmental biology to tumor perfusion studies. Studies using these methods can be classified based on whether they use artificial tracers or red blood cells to visualize the fluid motion. We here present the first direct comparison in vivo of both methods. For high magnification cases, the experiments using red blood cells strongly underestimate the flow (up to 50% in the present case), as compared to the tracer results. For medium magnification cases, the results from both methods are indistinguishable as they give the same underestimation of the real velocities (approximately 33%, based on in vitro reference measurements). These results suggest that flow characteristics reported in literature cannot be compared without a careful evaluation of the imaging characteristics. A method to predict the expected flow averaging behavior for a particular facility is presented.

Online chromatic and scale-space microvessel-tracing analysis for transmitted light optical images

Limited contrast in transmitted light optical images from intravital microscopy is problematic for analysing tumour vascular morphology. Moreover, in some cases, changes in vasculature are visible to a human observer but are not easy to quantify. In this paper two online algorithms are presented: scale-space vessel tracing and chromatic decomposition for analysis of the vasculature of SW1222 human colorectal carcinoma xenografts growing in dorsal skin-fold "window" chambers in mice. Transmitted light optical images of tumours were obtained from mice treated with the tumour vascular disrupting agent, combretastatin-A-4-phosphate (CA4P), or saline. The tracing algorithm was validated against hand-traced vessels with accurate results. The measurements extracted with the algorithms confirmed the known effects of CA4P on tumour vascular topology. Furthermore, changes in the chromaticity suggest a deoxygenation of the blood with a recovery to initial levels in CA4P-treated tumours relative to the controls. The algorithms can be freely applied to other studies through the CAIMAN website (CAncer IMage ANalysis: http://www.caiman.org.uk).

The neutrophil's eye-view: inference and visualisation of the chemoattractant field driving cell chemotaxis in vivo

As we begin to understand the signals that drive chemotaxis in vivo, it is becoming clear that there is a complex interplay of chemotactic factors, which changes over time as the inflammatory response evolves. New animal models such as transgenic lines of zebrafish, which are near transparent and where the neutrophils express a green fluorescent protein, have the potential to greatly increase our understanding of the chemotactic process under conditions of wounding and infection from video microscopy data. Measurement of the chemoattractants over space (and their evolution over time) is a key objective for understanding the signals driving neutrophil chemotaxis. However, it is not possible to measure and visualise the most important contributors to in vivo chemotaxis, and in fact the understanding of the main contributors at any particular time is incomplete. The key insight that we make in this investigation is that the neutrophils themselves are sensing the underlying field that is driving their action and we can use the observations of neutrophil movement to infer the hidden net chemoattractant field by use of a novel computational framework. We apply the methodology to multiple in vivo neutrophil recruitment data sets to demonstrate this new technique and find that the method provides consistent estimates of the chemoattractant field across the majority of experiments. The framework that we derive represents an important new methodology for cell biologists investigating the signalling processes driving cell chemotaxis, which we label the neutrophils eye-view of the chemoattractant field.

Extracting fluorescent reporter time courses of cell lineages from high-throughput microscopy at low temporal resolution

The extraction of fluorescence time course data is a major bottleneck in high-throughput live-cell microscopy. Here we present an extendible framework based on the open-source image analysis software ImageJ, which aims in particular at analyzing the expression of fluorescent reporters through cell divisions. The ability to track individual cell lineages is essential for the analysis of gene regulatory factors involved in the control of cell fate and identity decisions. In our approach, cell nuclei are identified using Hoechst, and a characteristic drop in Hoechst fluorescence helps to detect dividing cells. We first compare the efficiency and accuracy of different segmentation methods and then present a statistical scoring algorithm for cell tracking, which draws on the combination of various features, such as nuclear intensity, area or shape, and importantly, dynamic changes thereof. Principal component analysis is used to determine the most significant features, and a global parameter search is performed to determine the weighting of individual features. Our algorithm has been optimized to cope with large cell movements, and we were able to semi-automatically extract cell trajectories across three cell generations. Based on the MTrackJ plugin for ImageJ, we have developed tools to efficiently validate tracks and manually correct them by connecting broken trajectories and reassigning falsely connected cell positions. A gold standard consisting of two time-series with 15,000 validated positions will be released as a valuable resource for benchmarking. We demonstrate how our method can be applied to analyze fluorescence distributions generated from mouse stem cells transfected with reporter constructs containing transcriptional control elements of the Msx1 gene, a regulator of pluripotency, in mother and daughter cells. Furthermore, we show by tracking zebrafish PAC2 cells expressing FUCCI cell cycle markers, our framework can be easily adapted to different cell types and fluorescent markers.

Microflow of fluorescently labelled red blood cells in tumours expressing single isoforms of VEGF and their response to vascular targeting agents

In this work we studied the functional differences between the microcirculation of murine tumours that express only single isoforms of vascular endothelial growth factor-A (VEGF), namely VEGF120 and VEGF188, and the effect of VEGF receptor tyrosine kinase (VEGF-R TK) inhibition on their functional response to the vascular disrupting agent, combretastatin A-4 phosphate (CA-4-P), using measurement of red blood cell (RBC) velocity by a 'keyhole' tracking algorithm. RBC velocities in VEGF188 tumours were unaffected by chronic treatment with a VEGF-R tyrosine kinase inhibitor, SU5416, whereas RBC velocities in VEGF120 tumours were significantly increased compared to control VEGF120 tumours. This effect was accompanied by a reduced tumour vascularisation. Pre-treatment of VEGF120 tumours with SU5416 made them much more resistant to CA-4-P treatment, with a RBC velocity response that was very similar to that of the more mature vasculature of the VEGF188 tumours. This study shows that vascular normalisation following anti-angiogenic treatment with a VEGF-R tyrosine kinase inhibitor reduced the response of a previously sensitive tumour line to CA-4-P.

Application of intravital microscopy in studies of tumor microcirculation

To grow and progress, solid tumors develop a vascular network through co-option and angiogenesis that is characterized by multiple structural and functional abnormalities, which negatively influence therapeutic outcome through direct and indirect mechanisms. As such, the morphology and function of tumor blood vessels, plus their response to different treatments, are a vital and active area of biological research. Intravital microscopy (IVM) has played a key role in studies of tumor angiogenesis, and ongoing developments in molecular probes, imaging techniques, and postimage analysis methods have ensured its continued and widespread use. In this review we discuss some of the primary advantages and disadvantages of IVM approaches and describe recent technological advances in optical microscopy (e.g., confocal microscopy, multiphoton microscopy, hyperspectral imaging, and optical coherence tomography) with examples of their application to studies of tumor angiogenesis.

A critical analysis of current in vitro and in vivo angiogenesis assays

The study of angiogenesis has grown exponentially over the past 40 years with the recognition that angiogenesis is essential for numerous pathologies and, more recently, with the advent of successful drugs to inhibit angiogenesis in tumours. The main problem with angiogenesis research remains the choice of appropriate assays to evaluate the efficacy of potential new drugs and to identify potential targets within the angiogenic process. This selection is made more complex by the recognition that heterogeneity occurs, not only within the endothelial cells themselves, but also within the specific microenvironment to be studied. Thus, it is essential to choose the assay conditions and cell types that most closely resemble the angiogenic disease being studied. This is especially important when aiming to translate data from in vitro to in vivo and from preclinical to the clinic. Here we critically review and highlight recent advances in the principle assays in common use including those for endothelial cell proliferation, migration, differentiation and co-culture with fibroblasts and mural cells in vitro, vessel outgrowth from organ cultures and in vivo assays such as chick chorioallantoic membrane (CAM), zebrafish, sponge implantation, corneal, dorsal air sac, chamber and tumour angiogenesis models. Finally, we briefly discuss the direction likely to be taken in future studies, which include the use of increasingly sophisticated imaging analysis systems for data acquisition.

An affine transformation invariance approach to cell tracking

Accurate and robust methods for automatically tracking rolling leukocytes facilitate inflammation research as leukocyte motion is a primary indicator of inflammatory response in the microvasculature. This paper reports on an affine transformation invariance approach we proposed to track rolling leukocyte in intravital microscopy image sequences. The method is based on the affine transformation invariance property, which enables the accommodation of linear affine transformations (translation, rotation, and/or scaling) of the target, and a particle filter that overcomes the effect of image clutter. In our data set of 50 sequences, we compared the new approach with an active contour tracking method and a Monte Carlo tracker. With the manual tracking result provided by an operator as the reference, the root mean square errors for the active contour tracking method, the Monte Carlo tracker and the affine transformation invariance approach were 0.95 microm, 0.79 microm and 0.74 microm, respectively, and the percentage of frames tracked were 72%, 75% and 89%, respectively. The affine transformation invariance approach demonstrated more robust (being able to successfully locate target leukocyte in more frames) and more accurate (lower root mean square error) tracking performance. We also separately studied the ability of the affine transformation invariance approach to track a dark target leukocyte and a bright target leukocyte by using the number of frames tracked as an evaluation measure. Dark target leukocyte possesses similar image intensity to the background, making it difficult to be located. In 20 sequences where the target leukocyte was dark, the affine transformation invariance approach tracked more frames in 18 sequences and fewer frames in 2 sequences when compared with the active contour tracking method. In comparison with the Monte Carlo tracker, the affine invariance method tracked more frames in 9 sequences, the same number of frames in 7 sequences and fewer frames in 4 sequences. In tracking a bright target leukocyte in 30 sequences, the affine transformation invariance approach demonstrated superior performance in 7 sequences and inferior performance in 1 sequence when compared with the active contour tracking method. It outperformed the Monte Carlo tracker in 15 sequences and underperformed in 1 sequence.