Semi-automated software for the three-dimensional delineation of complex vascular networks

Segmentation of Vasculature From Fluorescently Labeled Endothelial Cells in Multi-Photon Microscopy Images

Vasculature is known to be of key biological significance, especially in the study of tumors. As such, considerable effort has been focused on the automated segmentation of vasculature in medical and pre-clinical images. The majority of vascular segmentation methods focus on bloodpool labeling methods; however, particularly, in the study of tumors, it is of particular interest to be able to visualize both the perfused and the non-perfused vasculature. Imaging vasculature by highlighting the endothelium provides a way to separate the morphology of vasculature from the potentially confounding factor of perfusion. Here, we present a method for the segmentation of tumor vasculature in 3D fluorescence microscopic images using signals from the endothelial and surrounding cells. We show that our method can provide complete and semantically meaningful segmentations of complex vasculature using a supervoxel-Markov random field approach. We show that in terms of extracting meaningful segmentations of the vasculature, our method outperforms both state-of-the-art method, specific to these data, as well as more classical vasculature segmentation methods.

Morphological analysis of human umbilical vein endothelial cells co-cultured with ovarian cancer cells in 3D: An oncogenic angiogenesis assay

Antiangiogenic therapy for cancer is a strategy targeted at tumour vasculature, often in combination with conventional cytotoxicity treatments. Animal testing is still the most common method used for evaluating the efficacy of new drugs but tissue-engineered in vitro models are becoming more acceptable for replacing and reducing the use of animals in anti-cancer drug screening. In this study, a 3D co-culture model of human endothelial cells and ovarian cancer cells was developed. This model has the potential to mimic the interactions between endothelial cells and ovarian cancer cells. The feasibility of applying this model in drug testing was explored here. The complex morphology of the co-culture system, which features development of both endothelial tubule-like structures and tumour structures, was analysed quantitatively by an image analysis method. The co-culture morphology integrity was maintained for 10 days and the potential of the model for anti-cancer drug testing was evaluated using Paclitaxel and Cisplatin, two common anti-tumour drugs with different mechanisms of action. Both traditional cell viability assays and quantitative morphological analyses were applied in the drug testing. Cisplatin proved a good example showing the advantages of morphological analysis of the co-culture model when compared with mono-culture of endothelial cells, which did not reveal an inhibitory effect of Cisplatin on the tubule-like endothelial structures. Thus, the tubule areas of the co-culture reflected the anti-angiogenesis potential of Cisplatin. In summary, in vitro cancer models can be developed using a tissue engineering approach to more closely mimic the characteristics of tumours in vivo. Combined with the image analysis technique, this developed 3D co-culture angiogenesis model will provide more reproducible and reliably quantified results and reveal further information of the drug's effects on both tumour cell growth and tumour angiogenesis.

Optimization of the dorsal skinfold window chamber model and multi-parametric characterization of tumor-associated vasculature

The dorsal skinfold window chamber (DSWC) model is a unique tool that enables analysis of various aspects of tumor biology and therapeutic response. Although the protocol for the murine DSWC model is standardized, certain tumors fail to grow or require a particular environment to promote growth. Given such limitations, we optimized the DSWC model for a slow-growing tumor that regresses spontaneously in the standard protocol. We further characterized the vascular network in the tumor model compared with that of non-tumor-bearing mice and observed significant differences in multiple parameters related to vascular structure and function.

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).

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.

Tumor vascular changes mediated by inhibition of oncogenic signaling

Many inhibitors of the epidermal growth factor receptor (EGFR)-RAS-phosphatidylinositol 3-kinase (PI3K)-AKT signaling pathway are in clinical use or under development for cancer therapy. Here, we show that treatment of mice bearing human tumor xenografts with inhibitors that block EGFR, RAS, PI3K, or AKT resulted in prolonged and durable enhancement of tumor vascular flow, perfusion, and decreased tumor hypoxia. The vessels in the treated tumors had decreased tortuosity and increased internodal length accounting for the functional alterations. Inhibition of tumor growth cannot account for these results, as the drugs were given at doses that did not alter tumor growth. The tumor cell itself was an essential target, as HT1080 tumors that lack EGFR did not respond to an EGFR inhibitor but did respond with vascular alterations to RAS or PI3K inhibition. We extended these observations to spontaneously arising tumors in MMTV-neu mice. These tumors also responded to PI3K inhibition with decreased tumor hypoxia, increased vascular flow, and morphologic alterations of their vessels, including increased vascular maturity and acquisition of pericyte markers. These changes are similar to the vascular normalization that has been described after the antiangiogenic treatment of xenografts. One difficulty in the use of vascular normalization as a therapeutic strategy has been its limited duration. In contrast, blocking tumor cell RAS-PI3K-AKT signaling led to persistent vascular changes that might be incorporated into clinical strategies based on improvement of vascular flow or decreased hypoxia. These results indicate that vascular alterations must be considered as a consequence of signaling inhibition in cancer therapy.

Automated identification of neurons in 3D confocal datasets from zebrafish brainstem

Many kinds of neuroscience data are being acquired regarding the dynamic behaviour and phenotypic diversity of nerve cells. But as the size, complexity and numbers of 3D neuroanatomical datasets grow ever larger, the need for automated detection and analysis of individual neurons takes on greater importance. We describe here a method that detects and identifies neurons within confocal image stacks acquired from the zebrafish brainstem. The first step is to create a template that incorporates the location of all known neurons within a population - in this case the population of reticulospinal cells. Once created, the template is used in conjunction with a sequence of algorithms to determine the 3D location and identity of all fluorescent neurons in each confocal dataset. After an image registration step, neurons are segmented within the confocal image stack and subsequently localized to specific locations within the brainstem template - in many instances identifying neurons as specific, individual reticulospinal cells. This image-processing sequence is fully automated except for the initial selection of three registration points on a maximum projection image. In analysing confocal image stacks that ranged considerably in image quality, we found that this method correctly identified on average approximately 80% of the neurons (if we assume that manual detection by experts constitutes 'ground truth'). Because this identification can be generated approximately 100 times faster than manual identification, it offers a considerable time savings for the investigation of zebrafish reticulospinal neurons. In addition to its cell identification function, this protocol might also be integrated with stereological techniques to enhance quantification of neurons in larger databases. Our focus has been on zebrafish brainstem systems, but the methods described should be applicable to diverse neural architectures including retina, hippocampus and cerebral cortex.