Dynamic Imaging of Mouse Embryos and Cardiac Development in Static Culture

Imaging Approaches and the Quantitative Analysis of Heart Development

Heart morphogenesis is a complex and dynamic process that has captivated researchers for almost a century. This process involves three main stages, during which the heart undergoes growth and folding on itself to form its common chambered shape. However, imaging heart development presents significant challenges due to the rapid and dynamic changes in heart morphology. Researchers have used different model organisms and developed various imaging techniques to obtain high-resolution images of heart development. Advanced imaging techniques have allowed the integration of multiscale live imaging approaches with genetic labeling, enabling the quantitative analysis of cardiac morphogenesis. Here, we discuss the various imaging techniques used to obtain high-resolution images of whole-heart development. We also review the mathematical approaches used to quantify cardiac morphogenesis from 3D and 3D+time images and to model its dynamics at the tissue and cellular levels.

Longitudinal in Utero Analysis of Engrailed-1 Knockout Mouse Embryonic Phenotypes Using High-Frequency Ultrasound

Large-scale international efforts to generate and analyze loss-of-function mutations in each of the approximately 20,000 protein-encoding gene mutations are ongoing using the "knockout" mouse as a model organism. Because one-third of gene knockouts are expected to result in embryonic lethality, it is important to develop non-invasive in utero imaging methods to detect and monitor mutant phenotypes in mouse embryos. We describe the utility of 3-D high-frequency (40-MHz) ultrasound (HFU) for longitudinal in utero imaging of mouse embryos between embryonic days (E) 11.5 and E14.5, which represent critical stages of brain and organ development. Engrailed-1 knockout (En1-ko) mouse embryos and their normal control littermates were imaged with HFU in 3-D, enabling visualization of morphological phenotypes in the developing brains, limbs and heads of the En1-ko embryos. Recently developed deep learning approaches were used to automatically segment the embryonic brain ventricles and bodies from the 3-D HFU images, allowing quantitative volumetric analyses of the En1-ko brain phenotypes. Taken together, these results show great promise for the application of longitudinal 3-D HFU to analyze knockout mouse embryos in utero.