Maternal Serum Heme-Oxygenase-1 (HO-1) Concentrations in Early Pregnancy and Subsequent Risk of Gestational Diabetes Mellitus

Background: Heme oxygenase-1 (HO-1) concentrations have been recently reported to be elevated in impaired glucose tolerance and type 2 diabetes mellitus (T2DM). However, no study has examined the association between HO-1 concentrations and gestational diabetes mellitus (GDM). Methods: In a case-control study, nested within a prospective cohort of pregnant women (186 GDM cases and 191 women who remained eu-glycemic through pregnancy), we assessed the association of maternal serum HO-1 concentrations, measured in samples collected at 16 weeks gestation, on average, with subsequent risk of GDM. Maternal serum HO-1 concentrations were determined using ELISA. We fitted multivariate logistic regression models to derive estimates of odds ratios (ORs) and 95% confidence intervals (CIs). Results: Median serum HO-1 concentrations in early pregnancy were lower in women who subsequently developed GDM compared with those who did not (1.60 vs. 1.80 ng/mL, p-value = 0.002). After adjusting for maternal age, race, family history of T2DM and pre-pregnancy body mass index, women with HO-1≥3.05 ng/mL (highest decile) experienced a 74% reduction of GDM risk (95% CI; 0.09–0.77) compared with women whose concentrations were<1.23 ng/mL (lowest quartile). Conclusion: Serum HO-1 concentrations were inversely associated with subsequent GDM risk. These findings underscore the role of oxidative stress in the pathogenesis of GDM. Additional studies are warranted to confirm the clinical utility of serum HO-1 in diagnosis of GDM, particularly in the early pregnancy

Tetrahedral Image-to-Mesh Conversion Software for Anatomic Modeling of Arteriovenous Malformations

We describe a new implementation of an adaptive multi-tissue tetrahedral mesh generator targeting anatomic modeling of Arteriovenous Malformation (AVM) for surgical simulations. Our method, initially constructs an adaptive Body-Centered Cubic (BCC) mesh of high quality elements. Then, it deforms the mesh surfaces to their corresponding physical image boundaries, hence, improving the mesh fidelity and smoothness. Our deformation scheme, which builds upon the ITK toolkit, is based on the concept of energy minimization, and relies on a multi-material point-based registration. It uses non-connectivity patterns to implicitly control the number of the extracted feature points needed for the registration, and thus, adjusts the trade-off between the achieved mesh fidelity and the deformation speed. While many medical imaging applications require robust mesh generation, there are few codes available to the public. We compare our implementation with two similar open-source image-to-mesh conversion codes: (1) Cleaver from US, and (2) CGAL from EU. Our evaluation is based on five isotropic/anisotropic segmented images, and relies on metrics like geometric & topologic fidelity, mesh quality, gradation and smoothness. The implementation we describe is open- source and it will be available within: (i) the 3D Slicer package for visualization and image analysis from Harvard Medical School, and (ii) an interactive simulator for neurosurgical procedures involving vasculature using SOFA, a framework for real-time medical simulation developed by INRIA

Sleep duration and plasma leptin concentrations in early pregnancy among lean and overweight/obese women: a cross sectional study

Background: Early-pregnancy short sleep duration is predictive of gestational diabetes and preeclampsia; mechanisms for these associations are unknown. Leptin, an adipocyte-derived peptide involved in regulating food intake and energy expenditure, may play a role in these observed associations. Given inconsistent reports linking short sleep duration with leptin, and absence of studies among pregnant women, we examined the association of maternal sleep duration with plasma leptin in early pregnancy. Methods: This cross-sectional study included 830 pregnant women. Plasma leptin was measured in samples collected around 13 weeks gestation. Sleep duration was categorized as: ≤5, 6, 7–8 (reference), and ≥9 hours. Differences in leptin concentrations across categories were estimated using linear regression. Analyses were completed for lean and overweight/obese women. Results: Overall, women with long sleep duration had elevated plasma leptin (p-value = 0.04). However, leptin concentrations were not statistically significantly elevated in women with a short sleep duration. There was no association of leptin with sleep duration among lean women. Among overweight/obese women, a U-shaped relation between leptin and sleep duration was observed: Mean leptin was elevated (β = 21.96 ng/ml, P < 0.001) among women reporting ≤5 hour of sleep compared with reference group; and women reporting ≥9 hours of sleep also had elevated leptin (β = 4.29 ng/ml, P = 0.09). Conclusions: Short sleep duration, and to a lesser extent long sleep duration, were associated with elevated leptin among overweight/obese women. These data add some evidence to help understand mechanistic relationships of sleep duration with pregnancy complications

Robust head CT image registration pipeline for craniosynostosis skull correction surgery

Craniosynostosis is a congenital malformation of the infant skull typically treated via corrective surgery. To accurately quantify the extent of deformation and identify the optimal correction strategy, the patient-specific skull model extracted from a pre-surgical computed tomography (CT) image needs to be registered to an atlas of head CT images representative of normal subjects. Here, the authors present a robust multi-stage, multi-resolution registration pipeline to map a patient-specific CT image to the atlas space of normal CT images. The proposed registration pipeline first performs an initial optimisation at very low resolution to yield a good initial alignment that is subsequently refined at high resolution. They demonstrate the robustness of the proposed method by evaluating its performance on 560 head CT images of 320 normal subjects and 240 craniosynostosis patients and show a success rate of 92.8 and 94.2%, respectively. Their method achieved a mean surface-to-surface distance between the patient and template skull of \u3c2.5 mm in the targeted skull region across both the normal subjects and patients. Keywords: image registration, bone, surgery, medical image processing, computerised tomography, deformation, biomechanics, image resolution, optimisation Keywords: robust head CT image registration pipeline, craniosynostosis skull correction surgery, congenital malformation, infant skull, corrective surgery, deformation, optimal correction strategy, patient-specific skull model extraction, presurgical computed tomography image, robust multistage multiresolution registration pipeline, patient-specihc CT image, normal CT images, initial optimisation, very low resolution, mean surface-to-surface distance, template skull, targeted skull regio