A Deep-Learning Enabled Automatic Fetal Thalamus Diameter Measurement Algorithm.

The analysis of maternal factors that impact the normal development of the fetal thalamus is an emerging field of research and requires the retrospective measurement of fetal thalamus diameter (FTD). Unfortunately, FTD is not measured in routine 2D ultrasound (2D-US) screenings of fetuses. Manual measurement of FTD is a laborious, difficult, and error-prone process because the thalamus lacks well-defined boundaries in 2D-US images of the fetal brain as it has a similar echogenicity to the surrounding brain tissue. Traditional methods based on statistical shape models (SSMs) perform poorly in measuring FTD due to the noisy textures and fuzzy edges of the fetal thalamus in 2D-US images of the fetal brain. To overcome these difficulties, we propose a deep learning-based automatic FTD measurement algorithm, FTDNet. FTDNet measures FTD by learning to directly detect the measurement landmarks through supervised learning. The algorithm first detects the region of the brain that contains the thalamus structure, and then focuses on processing that region for FTD landmark detection. Our FTD dataset, developed through a consensus between two ultrasonographers, contains 1,111 pairs of landmark coordinates for measuring FTD and verified bounding boxes surrounding the fetal thalamus. To assess FTDNet's measurement consistency compared to the ground truth, we used the intraclass correlation coefficient (ICC). FTDNet achieved an ICC score of 0.734, significantly outperforming the prior SSM method and other baseline comparison methods. Our findings are an important step forward in understanding the maternal factors which influence fetal brain development.Clinical relevance- This work proposes an end-to-end thalamus detection and measurement algorithm for measuring fetal thalamus diameter. Our work represents a significant step in the research of how maternal factors can impact fetal thalamus development. The development of an automatic and accurate method for measuring FTD through deep learning has the potential to greatly advance this field of study.

Effects of 3 months of multi-nutrient supplementation on the immune system and muscle and respiratory function of older adults in aged care (The Pomerium Study): protocol for a randomised controlled trial.

INTRODUCTION: Immunosenescence leads to increased morbidity and mortality associated with viral infections and weaker vaccine responses. This has been well documented for seasonal influenza and the current pandemic with SARS-CoV-2 (COVID-19), which disproportionately impact older adults, particularly those in residential aged care facilities. Inadequate nutrient intakes associated with impaired immunity, respiratory and muscle function are likely to augment the effects of immunosenescence. In this study, we test whether the impact of inadequate nutrition can be reversed using multi-nutrient supplementation, consequently enhancing vaccine responses, reducing the risk of viral infections and improving respiratory and muscle function. METHODS AND ANALYSIS: The Pomerium Study is a 3-month, single-blind, randomised, controlled trial testing the effects of two daily servings of an oral multi-nutrient supplement (330 kcal, 20 g protein, 1.5 g calcium 3-hydroxy-3-methylbutyrate monohydrate (CaHMB), 449 mg calcium, 500 IU vitamin D3 and 25 vitamins and minerals) on the immune system and muscle and respiratory function of older adults in aged care in Melbourne, Australia. 160 older adults (≥75 years old) will be recruited from aged care facilities and randomised to treatment (multi-nutrient supplement) or control (usual care). The primary outcome is a change in T-cell subsets CD8 + and CD28null counts at months 1 and 3. Secondary outcomes measured at baseline and month 3 are multiple markers of immunosenescence (also at 1 month), body composition (bioimpedance), handgrip strength (dynamometer), physical function (short physical performance battery), respiratory function (spirometry) and quality of life (EQ-5D-5L). Incidence and complications of COVID-19 and/or viral infections (ie, hospitalisation, complications or death) will be recorded throughout the trial, including 3 months after supplementation is ceased. ETHICS AND DISSEMINATION: This study was approved by Melbourne Health Human Research Ethics Committee (Ref No. HREC/73985/MH-2021, ERM Ref No. RMH73985, Melbourne Health Site Ref No. 2021.115). Written informed consent will be obtained from participants. Results will be published in peer-reviewed journals and made available to key aged care stakeholders, including providers, residents, and government bodies. TRIAL REGISTRATION NUMBER: ACTRN12621000420842.

The maternal gut microbiome during pregnancy and offspring allergy and asthma.

Environmental exposures during pregnancy that alter both the maternal gut microbiome and the infant's risk of allergic disease and asthma include a traditional farm environment and consumption of unpasteurized cow's milk, antibiotic use, dietary fiber, and psychosocial stress. Multiple mechanisms acting in concert may underpin these associations and prime the infant to acquire immune competence and homeostasis following exposure to the extrauterine environment. Cellular and metabolic products of the maternal gut microbiome can promote the expression of microbial pattern recognition receptors, as well as thymic and bone marrow hematopoiesis relevant to regulatory immunity. At birth, transmission of maternally derived bacteria likely leverages this in utero programming to accelerate postnatal transition from a TH2- to TH1- and TH17-dominant immune phenotype and maturation of regulatory immune mechanisms, which in turn reduce the child's risk of allergic disease and asthma. Although our understanding of these phenomena is rapidly evolving, the field is relatively nascent, and we are yet to translate existing knowledge into interventions that substantially reduce disease risk in humans. Here, we review evidence that the maternal gut microbiome impacts the offspring's risk of allergic disease and asthma, discuss challenges and future directions for the field, and propose the hypothesis that maternal carriage of Prevotella copri during pregnancy decreases the offspring's risk of allergic disease via production of succinate, which in turn promotes bone marrow myelopoiesis of dendritic cell precursors in the fetus.

Decreased maternal serum acetate and impaired fetal thymic and regulatory T cell development in preeclampsia.

Maternal immune dysregulation seems to affect fetal or postnatal immune development. Preeclampsia is a pregnancy-associated disorder with an immune basis and is linked to atopic disorders in offspring. Here we show reduction of fetal thymic size, altered thymic architecture and reduced fetal thymic regulatory T (Treg) cell output in preeclamptic pregnancies, which persists up to 4 years of age in human offspring. In germ-free mice, fetal thymic CD4+ T cell and Treg cell development are compromised, but rescued by maternal supplementation with the intestinal bacterial metabolite short chain fatty acid (SCFA) acetate, which induces upregulation of the autoimmune regulator (AIRE), known to contribute to Treg cell generation. In our human cohorts, low maternal serum acetate is associated with subsequent preeclampsia, and correlates with serum acetate in the fetus. These findings suggest a potential role of acetate in the pathogenesis of preeclampsia and immune development in offspring.

Automatic Measurement of Thalamic Diameter in 2-D Fetal Ultrasound Brain Images Using Shape Prior Constrained Regularized Level Sets.

We derived an automated algorithm for accurately measuring the thalamic diameter from 2-D fetal ultrasound (US) brain images. The algorithm overcomes the inherent limitations of the US image modality: nonuniform density; missing boundaries; and strong speckle noise. We introduced a "guitar" structure that represents the negative space surrounding the thalamic regions. The guitar acts as a landmark for deriving the widest points of the thalamus even when its boundaries are not identifiable. We augmented a generalized level-set framework with a shape prior and constraints derived from statistical shape models of the guitars; this framework was used to segment US images and measure the thalamic diameter. Our segmentation method achieved a higher mean Dice similarity coefficient, Hausdorff distance, specificity, and reduced contour leakage when compared to other well-established methods. The automatic thalamic diameter measurement had an interobserver variability of -0.56 ± 2.29 mm compared to manual measurement by an expert sonographer. Our method was capable of automatically estimating the thalamic diameter, with the measurement accuracy on par with clinical assessment. Our method can be used as part of computer-assisted screening tools that automatically measure the biometrics of the fetal thalamus; these biometrics are linked to neurodevelopmental outcomes.

An emerging model of maternity care: smartphone, midwife, doctor?

BACKGROUND: Mobile technology in the form of the smartphone is widely used, particularly in pregnancy and they are an increasing and influential source of information. AIM: To describe the diverse nature of pregnancy related applications (apps) for the smartphone and to flag that these apps can potentially affect maternity care and should be considered in future planning of care provision. METHODS: The 2 smartphone platforms, Apple and Android, were searched for pregnancy related apps and reviewed for their purpose and popularity. FINDINGS: iTunes and Google Play returned 1059 and 497 pregnancy related apps respectively. Forty percent of the apps were informative, 13% interactive, 19% had features of a medical tool and 11% were social media apps. By far the most popular apps, calculated as the number of reviews multiplied by average reviewer rating, were those with interactive features. DISCUSSION: The popularity of pregnancy-related apps could indicate a shift towards patient empowerment within maternity care provision. The traditional model of 'shared maternity care' needs to accommodate electronic devices into its functioning. Reliance on healthcare professionals may be reduced by the availability of interactive and personalised information delivered via a smartphone. This combined with the fact that smartphones are widely used by many women of childbearing age, has the potential to modify maternity care and experiences of pregnancy. Therefore it is important that healthcare professionals and policy-makers are more aware of these new developments, which are likely to influence healthcare and alter health-seeking behaviour. In addition healthcare professionals need to consider whether to discuss the use of apps in pregnancy with the women in their care.