ABSTRACT
BACKGROUND: We used two 3D ultrasound volumes of fetal heads at 13 weeks to create live-size 3D-printed phantoms with a view to training or assessment of diagnostic abilities for normal and abnormal nuchal translucency measurements. The phantoms are suitable for use in a water bath, imitating a real-life exam. They were then used to study measurement accuracy and reproducibility in examiners of different skill levels. METHODS: Ultrasound scans of a 13 + 0-week fetus were processed using 3D Slicer software, producing a stereolithography file for 3D printing. The model, crafted in Autodesk Fusion360™, adhered to FMF guidelines for NT dimensions (NT 2.3 mm). Additionally, a model with pathologic NT was designed (NT 4.2 mm). Printing was performed via Formlabs Form 3® printer using High Temp Resin V2. The externally identical looking 3D models were embedded in water-filled condoms for ultrasound examination. Eight specialists of varying expertise levels conducted five NT measurements for each model, classifying them in physiological and abnormal models. RESULTS: Classification of the models in physiological or abnormal NT resulted in a detection rate of 100%. Average measurements for the normal NT model and the increased NT model were 2.27 mm (SD ± 0.38) and 4.165 mm (SD ± 0.51), respectively. The interrater reliability was calculated via the intraclass correlation coefficient (ICC) which yielded a result of 0.883, indicating robust agreement between the raters. Cost-effectiveness analysis demonstrated the economical nature of the 3D printing process. DISCUSSION: This study underscores the potential of 3D printed fetal models for enhancing ultrasound training through high inter-rater reliability, consistency across different expert levels, and cost-effectiveness. Limitations, including population variability and direct translation to clinical outcomes, warrant further exploration. The study contributes to ongoing discussions on integrating innovative technologies into medical education, offering a practical and economical method to acquire, refine and revise diagnostic skills in prenatal ultrasound. Future research should explore broader applications and long-term economic implications, paving the way for transformative advancements in medical training and practice.
ABSTRACT
Infective endocarditis requiring mitral valve replacement during pregnancy is a rare event. We present a case of infective endocarditis of the mitral valve during second trimester and report maternal and perinatal outcomes. Prompt identification and interdisciplinary treatment is crucial; maternal and fetal follow-up including serial fetal neurosonography is recommended.
ABSTRACT
Artificial intelligence (AI) has gained prominence in medical imaging, particularly in obstetrics and gynecology (OB/GYN), where ultrasound (US) is the preferred method. It is considered cost effective and easily accessible but is time consuming and hindered by the need for specialized training. To overcome these limitations, AI models have been proposed for automated plane acquisition, anatomical measurements, and pathology detection. This study aims to overview recent literature on AI applications in OB/GYN US imaging, highlighting their benefits and limitations. For the methodology, a systematic literature search was performed in the PubMed and Cochrane Library databases. Matching abstracts were screened based on the PICOS (Participants, Intervention or Exposure, Comparison, Outcome, Study type) scheme. Articles with full text copies were distributed to the sections of OB/GYN and their research topics. As a result, this review includes 189 articles published from 1994 to 2023. Among these, 148 focus on obstetrics and 41 on gynecology. AI-assisted US applications span fetal biometry, echocardiography, or neurosonography, as well as the identification of adnexal and breast masses, and assessment of the endometrium and pelvic floor. To conclude, the applications for AI-assisted US in OB/GYN are abundant, especially in the subspecialty of obstetrics. However, while most studies focus on common application fields such as fetal biometry, this review outlines emerging and still experimental fields to promote further research.
ABSTRACT
Background: Pregnancies in women with pre-existing medical conditions are on the rise. These pregnancies are characterized by an increased rate of maternal and perinatal complications, which can result in higher health care expenditures and altered pregnancy experiences. The purpose of this study is to integrally analyze maternity care for women with pre-existing conditions in the framework of a risk-adapted, interdisciplinary care by recording three substantial parts of maternity care: (1) maternal and perinatal outcome; (2) hospital costs and reimbursements covering the period from preconception counseling or initial antenatal visit to discharge after birth; and (3) women's experience of reproductive choice and becoming a mother in the presence of a pre-existing condition. Methods: In this observational, prospective, longitudinal, and monocentric cohort study, we aim to include a total of 1,500 women over a recruitment period of 15 months. Women registering for care at the Department of Obstetrics and Prenatal Medicine, University Hospital Bonn, Germany, are allocated to three groups based on their health and risk status: women with pre-existing conditions, as well as healthy women with obstetric risk factor and healthy women with a low-risk pregnancy. Participants are observed from time of initial consultation until discharge after birth. Analysis focuses on (1) maternal and perinatal outcome, especially rate of severe maternal and neonatal morbidity; (2) costs and reimbursements; and (3) surveys to capture of women's experience and health-related quality of life during the time of reproductive choice, pregnancy, and childbirth in the presence of pre-existing medical conditions. Discussion: With its complex three-dimensional design, the ForMaT-Trial is aiming to provide a comprehensive analysis of pregnancy and childbirth in women with pre-existing conditions. The results may serve as a basis for counseling and care of these women. By analyzing costs of specialized care, data for discussing reimbursement are generated. Lastly, our results may increase awareness for the perception of reproductive choice, pregnancy and motherhood in this continuously rising population.Clinical trial registration: German Clinical Trials Register, DRKS00030061, October 28, 2022.
ABSTRACT
Medical devices directly exposed to blood are commonly used to treat cardiovascular diseases. However, these devices are associated with inflammatory reactions leading to delayed healing, rejection of foreign material or device-associated thrombus formation. We developed a novel recombinant fusion protein as a new biocompatible coating strategy for medical devices with direct blood contact. We genetically fused human serum albumin (HSA) with ectonucleoside triphosphate diphosphohydrolase-1 (CD39), a promising anti-thrombotic and anti-inflammatory drug candidate. The HSA-CD39 fusion protein is highly functional in degrading ATP and ADP, major pro-inflammatory reagents and platelet agonists. Their enzymatic properties result in the generation of AMP, which is further degraded by CD73 to adenosine, an anti-inflammatory and anti-platelet reagent. HSA-CD39 is functional after lyophilisation, coating and storage of coated materials for up to 8 weeks. HSA-CD39 coating shows promising and stable functionality even after sterilisation and does not hinder endothelialisation of primary human endothelial cells. It shows a high level of haemocompatibility and diminished blood cell adhesion when coated on nitinol stents or polyvinylchloride tubes. In conclusion, we developed a new recombinant fusion protein combining HSA and CD39, and demonstrated that it has potential to reduce thrombotic and inflammatory complications often associated with medical devices directly exposed to blood.
