Imaging of the blood vessel networks that make up the human vasculature is of great importance in understanding various human diseases such as peripheral vascular disease, ophthalmology and the study of the retina, and cancer. The analysis of blood vessels from traditional histopathology slides is difficult and cumbersome, since only small portions of blood vessels are visible in each slide. The use of flat-mounts (e.g. retina) or whole-mounts with tissue clearing techniques and imaging with confocal microscopy allows for interrogation of the entire tissue region, and visualization of the complete vasculature within the intact tissue sample. Quantitative analysis of blood vessel networks can be a difficult task, requiring sophisticated image processing techniques to evaluate and extract quantitative data.
Visikol offers a suite of services for the quantification and analysis of blood vessels and vascular networks within flat-mounts or whole-mounts using tissue clearing and confocal microscopy. With a specialization in blood vessel networks of the retina, our team of experts at Visikol can evaluate and quantify many aspects of the vascular networks in your tissues of interest.
Alternatively clients can provide imaging data from any imaging modality
|Analysis Method||Confocal Imaging|
|Markers||Immunolabeling for CD31|
Other vessel markers available on request
|Sample Submission||Whole Tissue fixed and stored in PBS with 0.05% azide|
Flat mount retina or ocular tissue
Pre-stained and mounted slides
Digitized slide images (confocal, OCTA, FITC-angiography, etc.)
|Imaging Parameters||10X, 20X, 40X magnification|
|Image Analysis||Vessel area/volume quantification|
Quantification of branch length and frequency (optional)
Quantification of tortuosity (optional)
Vessel orientation analysis (optional)
|Data Delivery||Whole Slide Images in RGB format, ROI masks|
Data tables containing quantitative data
Histograms of branch lengths, tortuosity, orientations
Other quantification strategies available on request
- Tissue sample is transferred to Visikol in PBS w/ 0.05% azide or in a form most appropriate for the customer (e.g. FFPE, OCT compound).
- Alternatively, mounted and stained slides or digitized images of IHC sections can be sent for analysis.
- The sample is processed, sectioned, and stained using immunohistochemistry techniques.
- The sample slides are imaged with high-throughput slide scanner at desired magnification.
- The images are then processed and analyzed according to customer specifications.
- Images and quantification report are then transferred to the customer.
Representative Data: Analysis of Blood Vessel Network in Rabbit Retina
Figure 1. Whole flat-mount rabbit retina, labeled with CD31. Blood vessel structures segmented by curvature analysis.
Figure 2. Retina blood vessels and segmentation mask
Figure 3. Analysis of blood vessel orientation in rabbit retina. Orientation color key in top left of colormap image.
Representative Data: Analysis of blood vessel networks in Alzheimer’s Disease model mice
With two recent high-profile failures of promising treatments to Alzheimer’s Disease (AD) in Phase III clinical trials (Bapineuzumab, Solanezumab) which targeted amyloid β plaques occurring in AD, there has been a revival of basic research toward new targets and pathologies relevant to the disease. Toward these efforts, there has been much interest in examining the roles of inflammation and the roles of blood vessel networks in contributing to AD. It is believed that changes in and damage to blood vessel networks in the brains of AD patients contribute to AD-related dementia.
Quantification of changes in the tortuosity of blood vessel networks in AD mouse models was conducted utilizing immunolabeling and 3D imaging of 1 mm mouse brain sections. Reconstruction of the blood vessel network in 3D allowed for analysis of branching patterns and branch length, which provided quantitative measures of alterations in the blood vessel networks in the triple transgene 3xTg AD mouse models compared to BALB/cJ mouse brains.
Tortuosity is a measure of how curved a blood vessel is, calculated for this work as the ratio of the branch length to the distance between the branch’s endpoints. Increasing tortuosity results in less efficient blood flow through the vessels, since more linear distance must be traveled to reach the endpoint of a vessel. The average blood vessel tortuosity in the brain of mice is approximately 1.2, meaning that the ratio of the branch length to the distance between the ends of the branches is approximately 5 to 4. Significant differences in the blood vessel network were detected between BALB/cJ and 3xTg mouse models.
Figure 4. Histogram depicting distribution of branch length of blood vessels in mouse model brains
Figure 5. Histogram depicting distribution of tortuosity, defined as the ratio of branch length to distance between the endpoints, of blood vessels in mouse model brains
A similar approach has been applied in the investigation of villous blood vessel networks in human placenta. It is thought that changes in the blood vessel network of placentae can contribute to complications during pregnancy such as pre-eclampsia and eclampsia, and utilizing immunolabeling and tissue clearing, quantitative analysis of blood vessel networks in portions of human placenta tissue were examined. This work has been published in JoVE (https://www.jove.com/video/57099/three-dimensional-rendering-analysis-immunolabeled-clarified-human).