(a) Morphology of the ventricles observed through transparent brain tissue. This processing allowed us to make precise observations of the gross external and internal morphology, including the formation of the ventricular system (Shiraishi et al., 2015a).
(b) Surface color mapping external view of the whole brain. The dynamic changes in thickness on the brain surface were visualized with a color scale (Shiraishi et al., 2015a).
(c) The core region (COR) of the thickening brain wall. The filter module “extracting the core regions,” shrinking from the surface of the brain for constructing COR, enabled visualization of the core regions of the thickening brain wall that resulted from brain differentiation and 3D growth. The brain was relatively uniform in thickness between CS13 and CS16. However, non-uniformity in the thickness of the brain wall was distinct after CS17. The anatomical positions of the COR were mostly consistent with nuclei such as the basal ganglia, thalamus, and pyramidal tract. The COR may be valuable as an anatomical indicator of the development and differentiation of the nuclei and tracts in the brain (Shiraishi et al., 2015a).
(d) Brain Model at CS23. The 3D digital data of MRI (2.35 T) was transformed to .STL data and then subjected to 3D printer (Shiraishi et al., 2013b).
The recent advent of several technologies has enabled us to acquire a much larger field of images with higher resolution. These include MRI and CT, which are acquisition systems; higher specification computers, which can compute a large amount of information accurately in a short time; and higher volume of storage. Using these technologies, datasets from larger samples, which correspond to later part of the first trimester and the second trimester, can be acquired and analyzed. The number of morphological studies on the later part of the first trimester and second trimester are less as compared to those on the first 8 weeks from fertilization (at the end of CS 23)(O’Rahilly and Müller, 1987). Many researchers have been attracted to the dynamic morphogenesis in rather earlier developmental stages. Establishment of CS may contribute in encouraging studies for those periods. In addition, technical limitations may also be the reason to avoid studies on fetuses after CS 23. It is difficult to apply histological analysis for the entire body of the fetus with a size larger than that at CS 23. Studies conducted on post embryonic period are mainly confined to localized histological analysis. From this point of view, 3D datasets of samples in larger samples are worth analyzing as they can reveal the 3D development of the entire body as well as organs.
Our analysis primarily focused on the morphological aspects of digital datasets. Both MRI and PCT contain additional information that reflects the structural component (elements) and structural order (orientation) in addition to the morphology. Previous fetal brain imaging studies using diffusion tensor images have been performed in the second trimester (Huang et al., 2009). The diffusion tensor image method has also been applied to cardiac muscles in mice (Angeli et al., 2014). Such methods maybe are applicable to 3D digital datasets from MRI (7 T), even though the samples have been stored for a long time in formalin. Moreover, PCT with Zeff imaging methods can be used to recognize and differentiate heavy metals such as Fe, Al, Ni, and Cu (Yoneyama et al., 2013). The 3D dynamics of such elements during human embryonic development are not currently known. Hematogenesis of the embryos may be also detectable using Fe as a trace marker. Such information may provide new insight to human development.
When analysis is performed using 3D digitized datasets, the pitfalls and limitations should be known. When a target organ is selected, its internal information and information on its surrounding organs are prone to be lost. Accurate determination of target anatomical landmarks as well as those used for references in digital datasets is very important to increase the accuracy of the analysis and hence that of the conclusion obtained. Careful comparison of histological sections of samples of similar ages and specialized anatomical knowledge are also required.
The 3D information obtained in classical embryology since the late 19th century has been used as the basis of prenatal diagnosis using ultrasound. The use of ultrasound for prenatal diagnostics has rapidly increased in the past 25 years (Blaas 2014). Moreover, 3D sonography performed with high-frequency transvaginal transducers has expanded as 3D sonoembryology. Normal developmental data during the embryonic stages, however, is still insufficient for guiding such clinical evaluations. The 3D analysis in our study may serve to provide accurate morphologic data as well as the dynamics of embryonic structures related to developmental stages required for insights into the dynamic and complex processes occurring during organogenesis.
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