Monitoring brain development of chick embryos in vivo using 3.0 T MRI: subdivision volume change and preliminary structural quantification using DTI

Background

Magnetic resonance imaging (MRI) has many advantages in the research of in vivo embryonic brain development, specifically its noninvasive aspects and ability to avoid skeletal interference. However, few studies have focused on brain development in chick, which is a traditional animal model in developmental biology. We aimed to serially monitor chick embryo brain development in vivo using 3.0 T MRI.

Methods

Ten fertile Hy-line white eggs were incubated and seven chick embryo brains were monitored in vivo and analyzed serially from 5 to 20 days during incubation using 3.0 T MRI. A fast positioning sequence was pre-scanned to obtain sagittal and coronal brain planes corresponding to the established atlas. T2-weighted imaging (T2WI) was performed for volume estimation of the whole brain and subdivision (telencephalon, cerebellum, brainstem, and lateral ventricle [LV]); diffusion tensor imaging (DTI) was used to reflect the evolution of neural bundle structures.

Results

The chick embryos’ whole brain and subdivision grew non-linearly over time; the DTI fractional anisotropy (FA) value within the telencephalon increased non-linearly as well. All seven scanned eggs hatched successfully.

Conclusions

MRI avoids embryonic sacrifice in a way that allows serial monitoring of longitudinal developmental processes of a single embryo. Feasibility for analyzing subdivision of the brain during development, and adding structural information related to neural bundles, makes MRI a powerful tool for exploring brain development.

High-resolution MRI analysis of breast cancer xenograft on the chick chorioallantoic membrane

The chick chorioallantoic membrane (CAM) model has been successfully used to study angiogenesis, cancer progression and its pharmacological treatment, tumor pharmacokinetics, and properties of novel nanomaterials. MRI is an attractive technique for non-invasive and longitudinal monitoring of physiological processes and tumor growth. This study proposes an age-adapted cooling regime for immobilization of the chick embryo, enabling high-resolution MRI of the embryo and the CAM tumor xenograft. 64 chick embryos were enrolled in this study. The novel immobilization and imaging protocol was optimized in 29 embryos. From d7 to d18 immobilization of the embryo up to 90 min was achieved by cooling at 4 °C pre-imaging, with cooling times adapted to age. Its application to tumor growth monitoring was evaluated in 15 embryos after xenotransplantation of human MDA-MB-231 breast cancer cells on CAM. Tumor volumes were monitored from d4 to d9 after grafting (d11 to d16 after incubation) applying a T2 -weighted multislice RARE sequence. At d9 after grafting, the tumors were collected and compared with the MRI-derived data by histology and weight measurements. Additional imaging methods comprising DWI, T2 mapping, and the bio-distribution of contrast agents were tested at d9 after grafting in 20 further embryos. With the adaptive cooling regime, motion artifacts could be completely avoided for up to 90 min scan time, enabling high-resolution in ovo imaging. Excellent anatomical details could be obtained in the embryo and tumors. Tumor volumes could be quantified over time. The results prove the feasibility of high-resolution MRI for longitudinal tumor and organ growth monitoring. The suggested method is promising for future applications such as testing tailored and/or targeted treatment strategies, longitudinal monitoring of tumor development, analysis of therapeutic efficacies of drugs, or assessment of tumor pharmacokinetics. The method provides an alternative to animal experimentation.

Automated Segmentation and Object Classification of CT Images: Application to In Vivo Molecular Imaging of Avian Embryos

Background. Although chick embryogenesis has been studied extensively, there has been growing interest in the investigation of skeletogenesis. In addition to improved poultry health and minimized economic loss, a greater understanding of skeletal abnormalities can also have implications for human medicine. True in vivo studies require noninvasive imaging techniques such as high-resolution microCT. However, the manual analysis of acquired images is both time consuming and subjective. Methods. We have developed a system for automated image segmentation that entails object-based image analysis followed by the classification of the extracted image objects. For image segmentation, a rule set was developed using Definiens image analysis software. The classification engine was implemented using the WEKA machine learning tool. Results. Our system reduces analysis time and observer bias while maintaining high accuracy. Applying the system to the quantification of long bone growth has allowed us to present the first true in ovo data for bone length growth recorded in the same chick embryos. Conclusions. The procedures developed represent an innovative approach for the automated segmentation, classification, quantification, and visualization of microCT images. MicroCT offers the possibility of performing longitudinal studies and thereby provides unique insights into the morpho- and embryogenesis of live chick embryos.