Segmentation of tumor vessels based on parallel double snakes including region information

International audience— In this paper, we address the problem of the seg-mentation of vessels in images of mouse tumors, with an efficient algorithm that minimizes the user's intervention. For each vessel, two points delimiting its extremities have to be selected. Then, a line inside the vessel is automatically determined based on a Dijkstra-type algorithm. Finally, an original active contour model combining both parallel double snakes and region criteria aims at finding the borders of the vessel. Our segmentation algorithm provides numerical models of tumor vessels, suitable for the simulation of blood and contrast agent flow

Rapid Analysis of Vessel Elements (RAVE): A Tool for Studying Physiologic, Pathologic and Tumor Angiogenesis

Quantification of microvascular network structure is important in a myriad of emerging research fields including microvessel remodeling in response to ischemia and drug therapy, tumor angiogenesis, and retinopathy. To mitigate analyst-specific variation in measurements and to ensure that measurements represent actual changes in vessel network structure and morphology, a reliable and automatic tool for quantifying microvascular network architecture is needed. Moreover, an analysis tool capable of acquiring and processing large data sets will facilitate advanced computational analysis and simulation of microvascular growth and remodeling processes and enable more high throughput discovery. To this end, we have produced an automatic and rapid vessel detection and quantification system using a MATLAB graphical user interface (GUI) that vastly reduces time spent on analysis and greatly increases repeatability. Analysis yields numerical measures of vessel volume fraction, vessel length density, fractal dimension (a measure of tortuosity), and radii of murine vascular networks. Because our GUI is open sourced to all, it can be easily modified to measure parameters such as percent coverage of non-endothelial cells, number of loops in a vascular bed, amount of perfusion and two-dimensional branch angle. Importantly, the GUI is compatible with standard fluorescent staining and imaging protocols, but also has utility analyzing brightfield vascular images, obtained, for example, in dorsal skinfold chambers. A manually measured image can be typically completed in 20 minutes to 1 hour. In stark comparison, using our GUI, image analysis time is reduced to around 1 minute. This drastic reduction in analysis time coupled with increased repeatability makes this tool valuable for all vessel research especially those requiring rapid and reproducible results, such as anti-angiogenic drug screening

An Improved In Vivo Methodology to Visualise Tumour Induced Changes in Vasculature Using the Chick Chorionic Allantoic Membrane Assay

Background/Aim: Decreasing the vascularity of a tumour has proven to be an effective strategy to suppress tumour growth and metastasis. Anti-angiogenic therapies have revolutionized the treatment of advanced-stage cancers, however there is still demand for further improvement. This necessitates new experimental models that will allow researchers to reliably study aspects of angiogenesis. The aim of this study was to demonstrate an in vivo technique in which the highly vascular and accessible chorioallantoic membrane (CAM) of the chick embryo is used to study tumour-induced changes in the macro and microvessels. Materials and Methods: Two cancer cell lines (human melanoma (C8161) and human prostate cancer (PC3)) were selected as model cells. Human dermal fibroblasts were used as a control. One million cells were labelled with green fluorescent protein and implanted on the CAM of the chick embryo at embryonic development day (EDD) 7 and angiogenesis was evaluated at EDDs 10, 12 and 14. A fluorescently-tagged lectin (lens culinaris agglutinin (LCA)) was injected intravenously into the chick embryo to label endothelial cells. The LCA is known to label the luminal surface of endothelial cells, or dextrans, in the CAM vasculature. Macrovessels were imaged by a hand-held digital microscope and images were processed for quantification. Microvessels were evaluated by confocal microscopy. Tumour invasion was assessed by histological and optical sectioning. Results: Tumour cells (C8161 and PC3) produced quantifiable increases in the total area covered by blood vessels, compared to fibroblasts when assessed by digital microscopy. Tumour invasion could be demonstrated by both histological and optical sectioning. The most significant changes in tumour vasculature observed were in the microvascular structures adjacent to the tumour cells, which showed an increase in the endothelial cell coverage. Additionally, tumour intravasation and tumour thrombus formation could be detected in the areas adjacent to tumour cells. The fragility of tumour blood vessels could be demonstrated when tumour cells seeded on a synthetic scaffold were grown on CAM. Conclusion: We report on a modification to a well-studied CAM in vivo assay, which can be effectively used to study tumour induced changes in macro and microvasculature

HIF-1α effects on angiogenic potential in human small cell lung carcinoma

<p>Abstract</p> <p>Background</p> <p>Hypoxia-inducible factor-1 alpha (HIF-1α) maybe an important regulatory factor for angiogenesis of small cell lung cancer (SCLC). Our study aimed to investigate the effect of HIF-1α on angiogenic potential of SCLC including two points: One is the effect of HIF-1α on the angiogenesis of SCLC <it>in vivo</it>. The other is the regulation of angiogenic genes by HIF-1α <it>in vitro </it>and <it>in vivo</it>.</p> <p>Methods</p> <p><it>In vivo </it>we used an alternative method to study the effect of HIF-1a on angiogenic potential of SCLC by buliding NCI-H446 cell transplantation tumor on the chick embryo chorioallantoic membrane (CAM) surface. <it>In vitro </it>we used microarray to screen out the angiogenic genes regulated by HIF-1a and tested their expression level in CAM transplantation tumor by RT-PCR and Western-blot analysis.</p> <p>Results</p> <p><it>In vivo </it>angiogenic response surrounding the SCLC transplantation tumors in chick embryo chorioallantoic membrane (CAM) was promoted after exogenous HIF-1α transduction (p < 0.05). <it>In vitro </it>the changes of angiogenic genes expression induced by HIF-1α in NCI-H446 cells were analyzed by cDNA microarray experiments. HIF-1α upregulated the expression of angiogenic genes VEGF-A, TNFAIP6, PDGFC, FN1, MMP28, MMP14 to 6.76-, 6.69-, 2.26-, 2.31-, 4.39-, 2.97- fold respectively and glycolytic genes GLUT1, GLUT2 to2.98-, 3.74- fold respectively. In addition, the expression of these angiogenic factors were also upregulated by HIF-1α in the transplantion tumors in CAM as RT-PCR and Western-blot analysis indicated.</p> <p>Conclusions</p> <p>These results indicated that HIF-1α may enhance the angiogenic potential of SCLC by regulating some angiogenic genes such as VEGF-A, MMP28 etc. Therefore, HIF-1α may be a potential target for the gene targeted therapy of SCLC.</p

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is the growth of abnormal new vessels. In this paper, an automated method for the detection of new vessels from retinal images is presented. This method is based on a dual classification approach. Two vessel segmentation approaches are applied to create two separate binary vessel map which each hold vital information. Local morphology features are measured from each binary vessel map to produce two separate 4-D feature vectors. Independent classification is performed for each feature vector using a support vector machine (SVM) classifier. The system then combines these individual outcomes to produce a final decision. This is followed by the creation of additional features to generate 21-D feature vectors, which feed into a genetic algorithm based feature selection approach with the objective of finding feature subsets that improve the performance of the classification. Sensitivity and specificity results using a dataset of 60 images are 0.9138 and 0.9600, respectively, on a per patch basis and 1.000 and 0.975, respectively, on a per image basis

Effects of nitrite and oxygen on angiogenesis in vascular networks of the chicken embryo

Nitric oxide (NO) is an important mediator of angiogenesis and is primarily produced endogenously through the action of nitric oxide synthase (NOS). An alternate pathway for NO production is the conversion of nitrite to NO, which depends on the presence of hemoglobin (Hb) and hypoxic conditions. The angiogenic effects of topically applied sodium nitrite on two vascular beds in the ex ovo chicken embryonic model of angiogenesis were assessed. Gas barrier films were used to modulate local oxygen levels in the chorioallantoic membrane (CAM), a respiratory vascular network, and the area vasculosa (AV) on the yolk sac, a typical peripheral vascular network. The low-permeable film polyvinylidene chloride (PVDC) and highly permeable regenerated cellulose (RC) were applied to the surface of the vasculature to alter oxygen diffusion and transport and produce a local environment of low or high oxygen, respectively. Phosphorescence Quenching Microscopy (PQM) was used to verify the oxygen levels in the vascular membranes underneath the films. Following 48 hours of continuous application of sodium nitrite (330 μg/kg/day), saline, or sodium nitrite + cPTIO (a NO scavenger) (1mg/kg/day), the angiogenic response was quantified by measuring vascular density and network complexity. The PVDC film reduced CAM PO2 to 17.9±5.5 mmHg and AV PO2 to 29.5±3.6 while the RC film maintained a PO2 of 115 mmHg. At the edge of PVDC film, there was found to be a small area of transition between the nearby low and high PO2 regions. After nitrite application, significant increases in vascularity were observed in the AV under hypoxic conditions, but not normoxic conditions (p\u3c0.03). cPTIO inhibited nitrite-induced angiogenesis and returned vascularity to levels observed with saline application. No significant changes were observed in the CAM, but a trend of reduced angiogenesis after nitrite application was observed compared to saline and saline+cPTIO. These results indicate that two highly diffusible gases, NO and O2, play important roles in the growth of new blood vessels, but in a way that appears to depend on the gas exchange function of the vascular network

Automated detection of proliferative diabetic retinopathy from retinal images

Diabetic retinopathy (DR) is a retinal vascular disease associated with diabetes and it is one of the most common causes of blindness worldwide. Diabetic patients regularly attend retinal screening in which digital retinal images are captured. These images undergo thorough analysis by trained individuals, which can be a very time consuming and costly task due to the large diabetic population. Therefore, this is a field that would greatly benefit from the introduction of automated detection systems. This project aims to automatically detect proliferative diabetic retinopathy (PDR), which is the most advanced stage of the disease and poses a high risk of severe visual impairment. The hallmark of PDR is neovascularisation, the growth of abnormal new vessels. Their tortuous, convoluted and obscure appearance can make them difficult to detect. In this thesis, we present a methodology based on the novel approach of creating two different segmented vessel maps. Segmentation methods include a standard line operator approach and a novel modified line operator approach. The former targets the accurate segmentation of new vessels and the latter targets the reduction of false responses to non-vessel edges. Both generated binary vessel maps hold vital information which is processed separately using a dual classification framework. Features are measured from each binary vessel map to produce two separate feature sets. Independent classification is performed for each feature set using a support vector machine (SVM) classifier. The system then combines these individual classification outcomes to produce a final decision. The proposed methodology, using a dataset of 60 images, achieves a sensitivity of 100.00% and a specificity of 92.50% on a per image basis and a sensitivity of 87.93% and a specificity of 94.40% on a per patch basis. The thesis also presents an investigation into the search for the most suitable features for the classification of PDR. This entails the expansion of the feature vector, followed by feature selection using a genetic algorithm based approach. This provides an improvement in results, which now stand at a sensitivity and specificity 3 of 100.00% and 97.50% respectively on a per image basis and 91.38% and 96.00% respectively on a per patch basis. A final extension to the project sees the framework of dual classification further explored, by comparing the results of dual SVM classification with dual ensemble classification. The results of the dual ensemble approach are deemed inferior, achieving a sensitivity and specificity of 100.00% and 95.00% respectively on a per image basis and 81.03% and 95.20% respectively on a per patch basis

The development and alignment of engineered microvasculature in fibrin gel

University of Minnesota Ph.D. dissertation. Ph.D. November 2012. Major:Biomedical Engineering. Advisor: Robert T. Tranquillo. 1 computer file (PDF); iv, 301 pages, appendices A-C.The ability to engineer microvasculature would be of great utility for the tissue engineering of highly metabolic tissues such as myocardium. In addition, the alignment of such a network is critical to the success of using it to deliver oxygen to tissue cells because it provides natural inlet and outlet sides for perfusion. In this work, the ability of engineered microvessels to align with their fibrin gel matrix has been examined and a bioreactor has been designed to harness this ability and perfuse the engineered tissue. The results indicate that engineered microvasculature can be aligned via cell-induced gel compaction and that this compaction improves lumen density. Interstitial flow provided an additional increase in lumen density. A mathematical model of fluid flow through engineered microvessels and a variety of image analysis methods were also developed