Prenatal Cell-Free DNA Screening With Fetal Enrichment Enables Sampling From 8 Weeks of Gestational Age.

Cell-free DNA (cfDNA) screening for fetal aneuploidy is typically offered from 10 weeks of gestational age (GA) onward. Fetal fraction (FF) enrichment may enable screening before 10 weeks with a low failure rate. This study aimed to assess the feasibility of cfDNA screening with in vitro enrichment before 10 weeks of gestation.

PMS2 c.2117del (p.Lys706Serfs*19) is the Most Frequent Cancer-Associated Founder Pathogenic Variant in the French-Canadian Population of Quebec, Canada.

We identified a PMS2 variant (NM_000535.7:c.2117del, p.

Burst of gyrification in the human brain after birth.

Gyrification, the intricate folding of the brain's cortex, begins mid-gestation and surges dramatically throughout the perinatal period. Yet, a critical factor has been largely overlooked in neurodevelopmental research: the profound impact of birth on brain structure. Leveraging the largest known perinatal MRI dataset-819 sessions spanning 21 to 45 postconceptional weeks-we reveal a burst in gyrification immediately following birth (~37 weeks post-conception), amounting to half the entire gyrification expansion occurring during the fetal period.

Tools used to appraise the quality of studies included in systematic reviews and meta-analyses in human genetics: a systematic review.

Quality assessment of primary studies is an essential component of systematic reviews (SRs). This methodological review systematically examines the choice, format and utilization of critical appraisal (CA) tools in SRs with or without meta-analyses in the field of human genetics. We searched MEDLINE, Embase, Web of Science, and PubMed up to January 2024.

Intersection-based slice motion estimation for fetal brain imaging.

Fetal MRI offers a broad spectrum of applications, including the investigation of fetal brain development and facilitation of early diagnosis. However, image quality is often compromised by motion artifacts arising from both maternal and fetal movement. To mitigate these artifacts, fetal MRI typically employs ultrafast acquisition sequences.

Comprehensive analysis of supervised learning methods for electrical source imaging.

Electroencephalography source imaging (ESI) is an ill-posed inverse problem: an additional constraint is needed to find a unique solution. The choice of this constraint, or prior, remains a challenge for most ESI methods. This work explores the application of supervised learning methods for spatio-temporal ESI, where the relationship between measurements and sources is learned directly from the data.

Multilabel SegSRGAN-A framework for parcellation and morphometry of preterm brain in MRI.

Magnetic resonance imaging (MRI) is a powerful tool for observing and assessing the properties of brain tissue and structures. In particular, in the context of neonatal care, MR images can be used to analyze neurodevelopmental problems that may arise in premature newborns. However, the intrinsic properties of newborn MR images, combined with the high variability of MR acquisition in a clinical setting, result in complex and heterogeneous images.

Complex Residual Attention U-Net for Fast Ultrasound Imaging from a Single Plane-Wave Equivalent to Diverging Wave Imaging.

Plane wave imaging persists as a focal point of research due to its high frame rate and low complexity. However, in spite of these advantages, its performance can be compromised by several factors such as noise, speckle, and artifacts that affect the image quality and resolution. In this paper, we propose an attention-based complex convolutional residual U-Net to reconstruct improved in-phase/quadrature complex data from a single insonification acquisition that matches diverging wave imaging.

Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning.

Gait abnormalities are frequent in children and can be caused by different pathologies, such as cerebral palsy, neuromuscular disease, toe walker syndrome, etc. Analysis of the "gait pattern" (i.e.

Dual-task kidney MR segmentation with transformers in autosomal-dominant polycystic kidney disease.

Autosomal-dominant polycystic kidney disease is a prevalent genetic disorder characterized by the development of renal cysts, leading to kidney enlargement and renal failure. Accurate measurement of total kidney volume through polycystic kidney segmentation is crucial to assess disease severity, predict progression and evaluate treatment effects. Traditional manual segmentation suffers from intra- and inter-expert variability, prompting the exploration of automated approaches.

Expansion of non-invasive prenatal screening to the screening of 10 types of chromosomal anomalies: a cost-effectiveness analysis.

Objectives: To determine the cost-effectiveness of the addition of chromosomal anomalies detectable by non-invasive prenatal screening (NIPS), in a prenatal screening programme targeting common aneuploidies.

Design, Setting And Participants: A simulation study was conducted to study the addition of chromosomal anomalies detectable by NIPS (sex chromosome aneuploidies, 22q11.2 deletion syndrome, large deletion/duplication >7 Mb and rare autosomal trisomies) to five basic strategies currently aiming the common trisomies: three strategies currently offered by the public healthcare systems in Canada, whose first-tier test is performed with biochemical markers, and two programmes whose first-tier test consists of NIPS-based methods.

Semi-automatic muscle segmentation in MR images using deep registration-based label propagation.

Fully automated approaches based on convolutional neural networks have shown promising performances on muscle segmentation from magnetic resonance (MR) images, but still rely on an extensive amount of training data to achieve valuable results. Muscle segmentation for pediatric and rare diseases cohorts is therefore still often done manually. Producing dense delineations over 3D volumes remains a time-consuming and tedious task, with significant redundancy between successive slices.

Decision impact studies, evidence of clinical utility for genomic assays in cancer: A scoping review.

Background: Decision impact studies have become increasingly prevalent in cancer prognostic research in recent years. These studies aim to evaluate the impact of a genomic test on decision-making and appear to be a new form of evidence of clinical utility. The objectives of this review were to identify and characterize decision impact studies in genomic medicine in cancer care and categorize the types of clinical utility outcomes reported.

Comprehensive personalized ankle joint shape analysis of children with cerebral palsy from pediatric MRI.

Cerebral palsy, a common physical disability in childhood, often causes abnormal patterns of movement and posture. To better understand the pathology and improve rehabilitation of patients, a comprehensive bone shape analysis approach is proposed in this article. First, a group analysis is performed on a clinical MRI dataset using two state-of-the-art shape analysis methods: ShapeWorks and a voxel-based method relying on Advanced Normalization Tools (ANTs) registration.

User Experience of a Computer-Based Decision Aid for Prenatal Trisomy Screening: Mixed Methods Explanatory Study.

Background: Mobile health tools can support shared decision-making. We developed a computer-based decision aid (DA) to help pregnant women and their partners make informed, value-congruent decisions regarding prenatal screening for trisomy.

Objective: This study aims to assess the usability and usefulness of computer-based DA among pregnant women, clinicians, and policy makers.

Improving Fetal Fraction of Noninvasive Prenatal Screening Samples Collected in EDTA-Gel Tubes Using Gel Size Selection: A Head-To-Head Comparison of Methods.

The aim of this study was to compare the use of EDTA-gel blood collection tubes with and without size selection to cell-stabilizing collection tubes for remote blood sampling for noninvasive prenatal screening (NIPS). Sixty-one pregnant women at 10 to 14 weeks' gestation undergoing NIPS were recruited. Participants were phlebotomized with Streck and EDTA-gel tubes.

Assessment and comparison of image quality between two real-time sequences for dynamic MRI of distal joints at 3.0 Tesla.

Background: Real-time sequences allow functional evaluation of various joint structures during a continuous motion and help understand the pathomechanics of underlying musculoskeletal diseases.

Purpose: To assess and compare the image quality of the two most frequently used real-time sequences for joint dynamic magnetic resonance imaging (MRI), acquired during finger and ankle joint motion.

Material And Methods: A real-time dynamic acquisition protocol, including radiofrequency (RF)-spoiled and balanced steady-state free precession (bSSFP) sequences, optimized for temporal resolution with similar spatial resolution, was performed using a 3.

An Iterative Centroid Approach for Diffeomorphic Online Atlasing.

Online atlasing, i.e., incrementing an atlas with new images as they are acquired, is key when performing studies on very large, or still being gathered, databases.

Web-Based Training for Nurses on Using a Decision Aid to Support Shared Decision-making About Prenatal Screening: Parallel Controlled Trial.

Background: Nurses play an important role in supporting pregnant women making decisions about prenatal screening for Down syndrome. We developed a web-based shared decision-making (SDM) training program for health professionals focusing on Down syndrome screening decisions.

Objective: In this study, we aim to assess the impact of an SDM training program on nurses' intention to use a decision aid with pregnant women deciding on prenatal screening for Down syndrome.

Effect of preexamination conditions in a centralized-testing model of non-invasive prenatal screening.

Objectives: Non-invasive prenatal testing requires the presence of fetal DNA in maternal plasma. Understanding how preexamination conditions affect the integrity of cell-free DNA (cfDNA) and fetal fraction (FF) are a prerequisite for test implementation. Therefore, we examined the adjusted effect that EDTA and Streck tubes have on the cfDNA quantity and FF.

Gradients of connectivity as graph Fourier bases of brain activity.

The application of graph theory to model the complex structure and function of the brain has shed new light on its organization, prompting the emergence of network neuroscience. Despite the tremendous progress that has been achieved in this field, still relatively few methods exploit the topology of brain networks to analyze brain activity. Recent attempts in this direction have leveraged on the one hand graph spectral analysis (to decompose brain connectivity into eigenmodes or gradients) and the other graph signal processing (to decompose brain activity "coupled to" an underlying network in graph Fourier modes).

Abdominal multi-organ segmentation with cascaded convolutional and adversarial deep networks.

Abdominal anatomy segmentation is crucial for numerous applications from computer-assisted diagnosis to image-guided surgery. In this context, we address fully-automated multi-organ segmentation from abdominal CT and MR images using deep learning. The proposed model extends standard conditional generative adversarial networks.

The influence of biophysical parameters in a biomechanical model of cortical folding patterns.

Abnormal cortical folding patterns, such as lissencephaly, pachygyria and polymicrogyria malformations, may be related to neurodevelopmental disorders. In this context, computational modeling is a powerful tool to provide a better understanding of the early brain folding process. Recent studies based on biomechanical modeling have shown that mechanical forces play a crucial role in the formation of cortical convolutions.

A connectome-based approach to assess motor outcome after neonatal arterial ischemic stroke.

Objective: Studies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of the motor network can help in the understanding of visual inspection and outcome discrepancy.