Segmentation propagation using a 3D embryo atlas for high-throughput MRI phenotyping: comparison and validation with manual segmentation

Deep learning enabled multi-organ segmentation of mouse embryos

The International Mouse Phenotyping Consortium (IMPC) has generated a large repository of three-dimensional (3D) imaging data from mouse embryos, providing a rich resource for investigating phenotype/genotype interactions. While the data is freely available, the computing resources and human effort required to segment these images for analysis of individual structures can create a significant hurdle for research. In this paper, we present an open source, deep learning-enabled tool, Mouse Embryo Multi-Organ Segmentation (MEMOS), that estimates a segmentation of 50 anatomical structures with a support for manually reviewing, editing, and analyzing the estimated segmentation in a single application. MEMOS is implemented as an extension on the 3D Slicer platform and is designed to be accessible to researchers without coding experience. We validate the performance of MEMOS-generated segmentations through comparison to state-of-the-art atlas-based segmentation and quantification of previously reported anatomical abnormalities in a Cbx4 knockout strain. This article has an associated First Person interview with the first author of the paper.

A bioimage informatics platform for high-throughput embryo phenotyping

High-throughput phenotyping is a cornerstone of numerous functional genomics projects. In recent years, imaging screens have become increasingly important in understanding gene-phenotype relationships in studies of cells, tissues and whole organisms. Three-dimensional (3D) imaging has risen to prominence in the field of developmental biology for its ability to capture whole embryo morphology and gene expression, as exemplified by the International Mouse Phenotyping Consortium (IMPC). Large volumes of image data are being acquired by multiple institutions around the world that encompass a range of modalities, proprietary software and metadata. To facilitate robust downstream analysis, images and metadata must be standardized to account for these differences. As an open scientific enterprise, making the data readily accessible is essential so that members of biomedical and clinical research communities can study the images for themselves without the need for highly specialized software or technical expertise. In this article, we present a platform of software tools that facilitate the upload, analysis and dissemination of 3D images for the IMPC. Over 750 reconstructions from 80 embryonic lethal and subviable lines have been captured to date, all of which are openly accessible at mousephenotype.org. Although designed for the IMPC, all software is available under an open-source licence for others to use and develop further. Ongoing developments aim to increase throughput and improve the analysis and dissemination of image data. Furthermore, we aim to ensure that images are searchable so that users can locate relevant images associated with genes, phenotypes or human diseases of interest.

Evolution of structural abnormalities in the rat brain following in utero exposure to maternal immune activation: A longitudinal in vivo MRI study

Genetic and environmental risk factors for psychiatric disorders are suggested to disrupt the trajectory of brain maturation during adolescence, leading to the development of psychopathology in adulthood. Rodent models are powerful tools to dissect the specific effects of such risk factors on brain maturational profiles, particularly when combined with Magnetic Resonance Imaging (MRI; clinically comparable technology). We therefore investigated the effect of maternal immune activation (MIA), an epidemiological risk factor for adult-onset psychiatric disorders, on rat brain maturation using atlas and tensor-based morphometry analysis of longitudinal in vivo MR images. Exposure to MIA resulted in decreases in the volume of several cortical regions, the hippocampus, amygdala, striatum, nucleus accumbens and unexpectedly, the lateral ventricles, relative to controls. In contrast, the volumes of the thalamus, ventral mesencephalon, brain stem and major white matter tracts were larger, relative to controls. These volumetric changes were maximal between post-natal day 50 and 100 with no differences between the groups thereafter. These data are consistent with and extend prior studies of brain structure in MIA-exposed rodents. Apart from the ventricular findings, these data have robust face validity to clinical imaging findings reported in studies of individuals at high clinical risk for a psychiatric disorder. Further work is now required to address the relationship of these MRI changes to behavioral dysfunction and to establish thier cellular correlates.

Micro-Computed Tomography for the Quantitative 3-Dimensional Assessment of the Compact Myocardium in the Mouse Embryo

BACKGROUND

Ventricular non-compaction is characterized by a thin layer of compact ventricular myocardium and it is an important abnormality in the mouse heart. It is reminiscent of left ventricular non-compaction, a fairly common human congenital cardiomyopathy. Non-compaction in transgenic mice has been classically evaluated by measuring the thickness of the compact myocardium through histological techniques involving image analysis of 2-dimensional (D) sections. Given the 3D nature of the heart, the aim of this study was to determine whether a technique for the non-destructive, 3D assessment of the mouse embryonic compact myocardium could be developed.

METHODS AND RESULTS

Micro-computed tomography (micro-CT), in combination with iodine staining, enabled the differentiation of the trabecular from the compact myocardium in wild-type mice. The 3D and digital nature of the micro-CT data allowed computation anatomical techniques to be readily applied, which were demonstrated via construction of group atlases and atlas-based descriptive statistics. Finally, micro-CT was used to identify the presence of non-compaction in mice with a deletion of the cell cycle inhibitor protein, p27(Kip1).

CONCLUSIONS

Iodine staining-enhanced micro-CT with computational anatomical analysis represents a valid addition to classical histology for the delineation of compact myocardial wall thickness in the mouse embryo. Given the quantitative 3D resolution of micro-CT, these approaches might provide helpful information for the analysis of non-compaction. (Circ J 2016; 80: 1795-1803).

Automatic classification framework for ventricular septal defects: a pilot study on high-throughput mouse embryo cardiac phenotyping

Intensive international efforts are underway toward phenotyping the entire mouse genome by modifying all its [Formula: see text] genes one-by-one for comparative studies. A workload of this scale has triggered numerous studies harnessing image informatics for the identification of morphological defects. However, existing work in this line primarily rests on abnormality detection via structural volumetrics between wild-type and gene-modified mice, which generally fails when the pathology involves no severe volume changes, such as ventricular septal defects (VSDs) in the heart. Furthermore, in embryo cardiac phenotyping, the lack of relevant work in embryonic heart segmentation, the limited availability of public atlases, and the general requirement of manual labor for the actual phenotype classification after abnormality detection, along with other limitations, have collectively restricted existing practices from meeting the high-throughput demands. This study proposes, to the best of our knowledge, the first fully automatic VSD classification framework in mouse embryo imaging. Our approach leverages a combination of atlas-based segmentation and snake evolution techniques to derive the segmentation of heart ventricles, where VSD classification is achieved by checking whether the left and right ventricles border or overlap with each other. A pilot study has validated our approach at a proof-of-concept level and achieved a classification accuracy of 100% through a series of empirical experiments on a database of 15 images.

In amnio MRI of mouse embryos

Mouse embryo imaging is conventionally carried out on ex vivo embryos excised from the amniotic sac, omitting vital structures and abnormalities external to the body. Here, we present an in amnio MR imaging methodology in which the mouse embryo is retained in the amniotic sac and demonstrate how important embryonic structures can be visualised in 3D with high spatial resolution (100 µm/px). To illustrate the utility of in amnio imaging, we subsequently apply the technique to examine abnormal mouse embryos with abdominal wall defects. Mouse embryos at E17.5 were imaged and compared, including three normal phenotype embryos, an abnormal embryo with a clear exomphalos defect, and one with a suspected gastroschisis phenotype. Embryos were excised from the mother ensuring the amnion remained intact and stereo microscopy was performed. Embryos were next embedded in agarose for 3D, high resolution MRI on a 9.4T scanner. Identification of the abnormal embryo phenotypes was not possible using stereo microscopy or conventional ex vivo MRI. Using in amnio MRI, we determined that the abnormal embryos had an exomphalos phenotype with varying severities. In amnio MRI is ideally suited to investigate the complex relationship between embryo and amnion, together with screening for other abnormalities located outside of the mouse embryo, providing a valuable complement to histology and existing imaging methods available to the phenotyping community.

Phenotyping the central nervous system of the embryonic mouse by magnetic resonance microscopy

Genetic mouse models of neurodevelopmental disorders are being massively generated, but technologies for their high-throughput phenotyping are missing. The potential of high-resolution magnetic resonance imaging (MRI) for structural phenotyping has been demonstrated before. However, application to the embryonic mouse central nervous system has been limited by the insufficient anatomical detail. Here we present a method that combines staining of live embryos with a contrast agent together with MR microscopy after fixation, to provide unprecedented anatomical detail at relevant embryonic stages. By using this method we have phenotyped the embryonic forebrain of Robo1/2(-/-) double mutant mice enabling us to identify most of the well-known anatomical defects in these mutants, as well as novel more subtle alterations. We thus demonstrate the potential of this methodology for a fast and reliable screening of subtle structural abnormalities in the developing mouse brain, as those associated to defects in disease-susceptibility genes of neurologic and psychiatric relevance.

A coming of age: advanced imaging technologies for characterising the developing mouse

The immense challenge of annotating the entire mouse genome has stimulated the development of cutting-edge imaging technologies in a drive for novel information. These techniques promise to improve understanding of the genes involved in embryo development, at least one third of which have been shown to be essential. Aligning advanced imaging technologies with biological needs will be fundamental to maximising the number of phenotypes discovered in the coming years. International efforts are underway to meet this challenge through an integrated and sophisticated approach to embryo phenotyping. We review rapid advances made in the imaging field over the past decade and provide a comprehensive examination of the relative merits of current and emerging techniques. The aim of this review is to provide a guide to state-of-the-art embryo imaging that will enable informed decisions as to which technology to use and fuel conversations between expert imaging laboratories, researchers, and core mouse production facilities.

Phenotype detection in morphological mutant mice using deformation features

Large-scale global efforts are underway to knockout each of the approximately 25,000 mouse genes and interpret their roles in shaping the mammalian embryo. Given the tremendous amount of data generated by imaging mutated prenatal mice, high-throughput image analysis systems are inevitable to characterize mammalian development and diseases. Current state-of-the-art computational systems offer only differential volumetric analysis of pre-defined anatomical structures between various gene-knockout mice strains. For subtle anatomical phenotypes, embryo phenotyping still relies on the laborious histological techniques that are clearly unsuitable in such big data environment. This paper presents a system that automatically detects known phenotypes and assists in discovering novel phenotypes in muCT images of mutant mice. Deformation features obtained from non-linear registration of mutant embryo to a normal consensus average image are extracted and analyzed to compute phenotypic and candidate phenotypic areas. The presented system is evaluated using C57BL/10 embryo images. All cases of ventricular septum defect and polydactyly, well-known to be present in this strain, are successfully detected. The system predicts potential phenotypic areas in the liver that are under active histological evaluation for possible phenotype of this mouse line.