Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Sep 1;14(17):4273.
doi: 10.3390/cancers14174273.

A Novel Artificial Intelligence-Based Approach for Quantitative Assessment of Angiogenesis in the Ex Ovo CAM Model

Lorenz Faihs  1   2 , Bardia Firouz  2 , Paul Slezak  2 , Cyrill Slezak  2   3 , Michael Weißensteiner  4 , Thomas Ebner  4 , Nassim Ghaffari Tabrizi-Wizsy  5 , Kurt Schicho  1 , Peter Dungel  2
Affiliations

A Novel Artificial Intelligence-Based Approach for Quantitative Assessment of Angiogenesis in the Ex Ovo CAM Model

Lorenz Faihs et al. Cancers (Basel). .

Abstract

Angiogenesis is a highly regulated process. It promotes tissue regeneration and contributes to tumor growth. Existing therapeutic concepts interfere with different steps of angiogenesis. The quantification of the vasculature is of crucial importance for research on angiogenetic effects. The chorioallantoic membrane (CAM) assay is widely used in the study of angiogenesis. Ex ovo cultured chick embryos develop an easily accessible, highly vascularised membrane on the surface. Tumor xenografts can be incubated on this membrane enabling studies on cancer angiogenesis and other major hallmarks. However, there is no commonly accepted gold standard for the quantification of the vasculature of the CAM. We compared four widely used measurement techniques to identify the most appropriate one for the quantification of the vascular network of the CAM. The comparison of the different quantification methods suggested that the CAM assay application on the IKOSA platform is the most suitable image analysis application for the vasculature of the CAM. The new CAM application on the IKOSA platform turned out to be a reliable and feasible tool for practical use in angiogenesis research. This novel image analysis software enables a deeper exploration of various aspects of angiogenesis and might support future research on new anti-angiogenic strategies for cancer treatment.

Keywords: angiogenesis; artificial intelligence; chorioallantoic membrane assay; comparison of image analysis methods for angiogenesis.

PubMed Disclaimer

Conflict of interest statement

M.W. and T.E. declare to be employed as computer vision and machine learning engineers by KML vision.

Figures

Figure 1
Figure 1
Experimental design. (a) Start of incubation. (b) Cracking of the eggs and transfer of the embryos into weight boats on day 3 of development. (c) Imaging of the vascular network at day 10 of development. (d) Image input for the analysis.
Figure 2
Figure 2
Segmentation masks with different image analysis applications. (a) ImageScope. (b) AngioTool. (c) IKOSA CAM Assay application.
Figure 3
Figure 3
Bland–Altman plots with a comparison of the branching points of the vascular networks quantified with the different image analysis methods. (a) Manual analysis, IKOSA CAM Assay application. (b) Manual analysis, AngioTool. (c) IKOSA CAM Assay application, AngioTool.
Figure 4
Figure 4
Bland–Altman Plots with a comparison of the total vasculature length measured with the IKOSA CAM Assay application and AngioTool.
Figure 5
Figure 5
Bland–Altman plots with a comparison of the total area of the vasculature measured with different image analysis methods. (a) IKOSA CAM Assay application, AngioTool. (b) IKOSA CAM Assay application, ImageScope. (c) AngioTool, ImageScope.
Figure 6
Figure 6
Bland–Altman plot with the comparison of the mean thickness of the vasculature measured manually and with the IKOSA CAM Assay application.
Figure 7
Figure 7
Comparison of the image analysis with (a) AngioTool and (b) the IKOSA CAM Assay application.
Figure 8
Figure 8
Image analysis with ImageScope. (a) Artefacts related to specific background structures (here: deeper blood vessels). (b) Light artefacts due to light reflections. (c) Exclusion of areas with the ‘negative pen tool’.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Ribatti D. The Chick Embryo Chorioallantoic Membrane (CAM). A Multifaceted Experimental Model. Mech. Dev. 2016;141:70–77. doi: 10.1016/j.mod.2016.05.003. - DOI - PubMed
    1. Nowak-Sliwinska P., Alitalo K., Allen E., Anisimov A., Aplin A.C., Auerbach R., Augustin H.G., Bates D.O., van Beijnum J.R., Bender R.H.F., et al. Consensus Guidelines for the Use and Interpretation of Angiogenesis Assays. Angiogenesis. 2018;21:532. doi: 10.1007/s10456-018-9613-x. - DOI - PMC - PubMed
    1. Schneider-Stock R., Ribatti D. The CAM Assay as an Alternative In Vivo Model for Drug Testing. Handb. Exp. Pharmacol. 2021;265:303–323. doi: 10.1007/164_2020_375. - DOI - PubMed
    1. Moreno-Jiménez I., Hulsart-Billstrom G., Lanham S.A., Janeczek A.A., Kontouli N., Kanczler J.M., Evans N.D., Oreffo R.O.C. The Chorioallantoic Membrane (CAM) Assay for the Study of Human Bone Regeneration: A Refinement Animal Model for Tissue Engineering. Sci. Rep. 2016;6:32168. doi: 10.1038/srep32168. - DOI - PMC - PubMed
    1. Ribatti D., Nico B., Vacca A., Presta M. The Gelatin Sponge-Chorioallantoic Membrane Assay. Nat. Protoc. 2006;1:85–91. doi: 10.1038/nprot.2006.13. - DOI - PubMed

LinkOut - more resources