Sensorless volumetric reconstruction of fetal brain freehand ultrasound scans with deep implicit representation.

Three-dimensional (3D) ultrasound imaging has contributed to our understanding of fetal developmental processes by providing rich contextual information of the inherently 3D anatomies. However, its use is limited in clinical settings, due to the high purchasing costs and limited diagnostic practicality. Freehand 2D ultrasound imaging, in contrast, is routinely used in standard obstetric exams, but inherently lacks a 3D representation of the anatomies, which limits its potential for more advanced assessment.

Birthweight of children with isolated congenital heart disease-A sibling analysis study.

Objective: Congenital heart disease (CHD) is associated with decreased birthweight (BW) compared to population-based references. The aim of this study was to compare the BW of isolated CHD cases to their siblings, thus controlling for unknown and unmeasured confounders within the family.

Methods: All isolated CHD cases in the Leiden University Medical Center were included (2002-2019).

Birthweight and isolated congenital heart defects - A systematic review and meta-analysis.

Background: Birthweight (BW) is an important prognostic factor in newborns with congenital heart defects (CHD).

Objectives: To give an overview of the literature on BW z-score in children with isolated CHD.

Search Strategy: A systematic search was performed on isolated CHD and BW in PubMed, Embase, Web of Science, COCHRANE Library and Emcare.

Subcortical segmentation of the fetal brain in 3D ultrasound using deep learning.

The quantification of subcortical volume development from 3D fetal ultrasound can provide important diagnostic information during pregnancy monitoring. However, manual segmentation of subcortical structures in ultrasound volumes is time-consuming and challenging due to low soft tissue contrast, speckle and shadowing artifacts. For this reason, we developed a convolutional neural network (CNN) for the automated segmentation of the choroid plexus (CP), lateral posterior ventricle horns (LPVH), cavum septum pellucidum et vergae (CSPV), and cerebellum (CB) from 3D ultrasound.

Placenta morphology and biomarkers in pregnancies with congenital heart disease - A systematic review.

Impaired placentation is an important contributing factor to intra-uterine growth restriction and pre-eclampsia in fetuses with congenital heart defects (CHD). These pregnancy complications occur more frequently in pregnancies with fetal CHD. One of the most important factors influencing the life of children with CHD is neurodevelopmental delay, which seems to start already in utero.

Learning to map 2D ultrasound images into 3D space with minimal human annotation.

In fetal neurosonography, aligning two-dimensional (2D) ultrasound scans to their corresponding plane in the three-dimensional (3D) space remains a challenging task. In this paper, we propose a convolutional neural network that predicts the position of 2D ultrasound fetal brain scans in 3D atlas space. Instead of purely supervised learning that requires heavy annotations for each 2D scan, we train the model by sampling 2D slices from 3D fetal brain volumes, and target the model to predict the inverse of the sampling process, resembling the idea of self-supervised learning.

Using three-dimensional ultrasound in predicting complex gastroschisis: A longitudinal, prospective, multicenter cohort study.

Objective: To determine whether complex gastroschisis (ie, intestinal atresia, perforation, necrosis, or volvulus) can prenatally be distinguished from simple gastroschisis by fetal stomach volume and stomach-bladder distance, using three-dimensional (3D) ultrasound.

Methods: This multicenter prospective cohort study was conducted in the Netherlands between 2010 and 2015. Of seven university medical centers, we included the four centers that performed longitudinal 3D ultrasound measurements at a regular basis.