The preparation of chicken ex ovo embryos and chorioallantoic membrane vessels as in vivo model for contrast-enhanced ultrasound imaging and microbubble-mediated drug delivery studies

Bram Meijlink*, Ilya Skachkov, Antonius F.W. van der Steen, Nico de Jong, Klazina Kooiman

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)
173 Downloads (Pure)

Abstract

The chicken embryo and the blood-vessel rich chorioallantoic membrane (CAM) is a valuable in vivo model to investigate biomedical processes, new ultrasound pulsing schemes, or novel transducers for contrast-enhanced ultrasound imaging and microbubble-mediated drug delivery. The reasons for this are the accessibility of the embryo and vessel network of the CAM as well as the low costs of the model. An important step to get access to the embryo and CAM vessels is to take the egg content out of the eggshell. In this protocol, three methods for taking the content out of the eggshell between day 5 and 8 of incubation are described thus allowing the embryos to develop inside the eggshell up to these days. The described methods only require simple tools and equipment and yield a higher survival success rate of 90% for 5-day, 75% for 6-day, 50% for 7-day, and 60% for 8-day old incubated eggs in comparison to ex ovo cultured embryos (~50%). The protocol also describes how to inject cavitation nuclei, such as microbubbles, into the CAM vascular system, how to separate the membrane containing the embryo and CAM from the rest of the egg content for optically transparent studies, and how to use the chicken embryo and CAM in a variety of short-term ultrasound experiments. The in vivo chicken embryo and CAM model is extremely relevant to investigate novel imaging protocols, ultrasound contrast agents, and ultrasound pulsing schemes for contrast-enhanced ultrasound imaging, and to unravel the mechanisms of ultrasound-mediated drug delivery.

Original languageEnglish
Article numbere62076
Pages (from-to)1-27
JournalJournal of Visualized Experiments
Volume2021
Issue number168
DOIs
Publication statusPublished - 2021

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