Imaging fetal anatomy.

Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development

The prediction, diagnosis and management of complications in monochorionic twin pregnancies

Monochorionic twin pregnancies are high-risk and closely monitored antenatally. A systematic review revealed no existing predictive factors for twin-twin transfusion syndrome (TTTS), growth restriction, or intrauterine fetal death (IUFD). The Optimal Management of Monochorionic Twins (OMMIT) study found that first trimester inter-twin nuchal translucency discordance, crown-rump length discordance, β-hCG, PAPP-A, AFP, PlGF and sFlt-1 do not predict adverse outcome. A difference was seen in novel second trimester biomarkers: in the recipient twin amniotic fluid metabolites pre- and post-fetoscopic laser ablation; and a relationship with recipient twin cardiac function was demonstrated. Discovery work on miRNA in second trimester maternal serum of TTTS pregnancies found no difference compared to uncomplicated monochorionic twin pregnancies. A systematic review provided a more personalised risk prediction for the surviving co-twin in single IUFD, including that that the rate of abnormal brain imaging is 20% and the IUFDs occurring at 14-28 weeks are at higher risk. A preliminary study of parent-fetal antenatal and postnatal attachment and depression in TTTS pregnancies found maternal attachment increased postnatally and depressive symptoms decreased, whereas paternal scores did not change. This thesis has reported exciting findings which have clinical implications, and advance knowledge of complicated monochorionic twin pregnancies

Endothelial plasticity in cardiovascular development : role of growth factors VEGF and PDGF

The central cell type within vascular development is the endothelial cell (EC). It forms during (lymph)vasculogenesis, proliferates during angiogenesis and instructs medial cells during arteriogenesis. The venous population also gives rise to a subset of the lymphatic endothelium and the endocardium is instructive in formation of the primitive heart. We show that endothelial plasticity is very high in the developing embryo/fetus and that its outcome is dependent on the VEGF, Notch and PDGF-signaling pathways. Alterations in VEGF and Notch-signaling abrogate endocardial and endothelial differentiation, cardiac development and coronary maturation. Alterations in these pathways are most likely also involved in abnormal lymphatic development as seen in fetuses with increased nuchal translucency. In this thesis, lymphatic endothelial plasticity is particularly underscored, as lymphatic ECs gain arterial characteristics in certain pathological situations. Additionally, we show that impaired VEGF, Notch and PDGF-B/PDGFR-_-signaling in ECs and/or vSMCs severely impairs coronary arteriogenesis. In conclusion, many growth factors either influencing the EC (such as VEGF) or produced by the EC (such as PDGF) play a role in regulating and fine-tuning these processes. Increasing our knowledge on how these factors influence (ab)normal vascular development will improve our understanding of many pathological conditions and might increase therapeutic approaches.The work presented in this thesis was supported by a grant of the Netherlands Heart Foundation (2001B057)UBL - phd migration 201

Down Syndrome detection with Swin Transformer architecture

Objective: Down Syndrome, also known as Trisomy 21, is a severe genetic disease caused by an extra chromosome 21. For the detection of Trisomy 21, despite those statistical methods have been widely used for screening, karyotyping remains the gold standard and the first level of testing for diagnosis. Due to karyotyping being a time-consuming and labour-intensive procedure, Computer Vision methodologies have been explored to automate the karyotyping process for decades. However, few studies have focused on Down Syndrome detection with the Transformer technique. This study develops a Down-Syndrome-Detector (DSD) architecture based on the Transformer structure, which includes a segmentation module, an alignment module, a classification module, and a Down Syndrome indicator. Methods: The segmentation and classification modules are designed by homogeneous transfer learning at the model level. Transfer learning techniques enable a network to share weights learned from the source domain (e.g., millions of data in ImageNet) and optimize the weights with limited labeled data in the target domain (e.g., less than 6,000 images in BioImLab). The Align-Module is designed to process the segmentation output to fit the classification dataset, and the Down Syndrome Indicator identifies a Down Syndrome case from the classification output. Results: Experiments are first performed on two public datasets BioImLab (119 cases) and Advanced Digital Imaging Research (ADIR, 180 cases). Our performance metrics indicate the good ability of segmentation and classification modules of DSD. Then, the DS detection performance of DSD is evaluated on a private dataset consisting of 1084 cells (including 20 DS cells from 2 singleton cases): 90.0% and 86.1% for cell-level TPR and TNR; 100% and 96.08% for case-level TPR and TNR, respectively. Conclusion: This study develops a pipeline based on the modern Transformer architecture for the detection of Down Syndrome from original metaphase micrographs. Both segmentation and classification models developed in this study are assessed using public datasets with commonly used metrics, and both achieved good results. The DSDproposed in this study reported satisfactory singleton case-specific DS detection results. Significance: As verified by a medical specialist, the developed method may improve Down Syndrome detection efficiency by saving human labor and improving clinical practice