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. In recent years, convolutional neural networks have been employed for polycystic kidney segmentation from magnetic resonance images. However, the use of Transformer-based models, which have shown remarkable performance in a wide range of computer vision and medical image analysis tasks, remains unexplored in this area. With their self-attention mechanism, Transformers excel in capturing global context information, which is crucial for accurate organ delineations. In this paper, we evaluate and compare various convolutional-based, Transformers-based, and hybrid convolutional/Transformers-based networks for polycystic kidney segmentation. Additionally, we propose a dual-task learning scheme, where a common feature extractor is followed by per-kidney decoders, towards better generalizability and efficiency. We extensively evaluate various architectures and learning schemes on a heterogeneous magnetic resonance imaging dataset collected from 112 patients with polycystic kidney disease. Our results highlight the effectiveness of Transformer-based models for polycystic kidney segmentation and the relevancy of exploiting dual-task learning to improve segmentation accuracy and mitigate data scarcity issues. A promising ability in accurately delineating polycystic kidneys is especially shown in the presence of heterogeneous cyst distributions and adjacent cyst-containing organs. This work contribute to the advancement of reliable delineation methods in nephrology, paving the way for a broad spectrum of clinical applications.

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., the way the person walks) using 3D analysis provides highly relevant clinical information. This information is used to guide therapeutic choices; however, it is underused in diagnostic processes, probably because of the lack of standardization of data collection methods. Therefore, 3D gait analysis is currently used as an assessment rather than a diagnostic tool. In this work, we aimed to determine if deep learning could be combined with 3D gait analysis data to diagnose gait disorders in children. We tested the diagnostic accuracy of deep learning methods combined with 3D gait analysis data from 371 children (148 with unilateral cerebral palsy, 60 with neuromuscular disease, 19 toe walkers, 60 with bilateral cerebral palsy, 25 stroke, and 59 typically developing children), with a total of 6400 gait cycles. We evaluated the accuracy, sensitivity, specificity, F1 score, Area Under the Curve (AUC) score, and confusion matrix of the predictions by ResNet, LSTM, and InceptionTime deep learning architectures for time series data. The deep learning-based models had good to excellent diagnostic accuracy (ranging from 0.77 to 0.99) for discrimination between healthy and pathological gait, discrimination between different etiologies of pathological gait (binary and multi-classification); and determining stroke onset time. LSTM performed best overall. This study revealed that the gait pattern contains specific, pathology-related information. These results open the way for an extension of 3D gait analysis from evaluation to diagnosis. Furthermore, the method we propose is a data-driven diagnostic model that can be trained and used without human intervention or expert knowledge. Furthermore, the method could be used to distinguish gait-related pathologies and their onset times beyond those studied in this research.

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. In this work, we propose a segmentation method relying on registration-based label propagation, which provides 3D muscle delineations from a limited number of annotated 2D slices. Based on an unsupervised deep registration scheme, our approach ensures the preservation of anatomical structures by penalizing deformation compositions that do not produce consistent segmentation from one annotated slice to another. Evaluation is performed on MR data from lower leg and shoulder joints. Results demonstrate that the proposed few-shot multi-label segmentation model outperforms state-of-the-art techniques.

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 3.0-T MRI scanner on 10 fingers and 12 ankles from healthy individuals during active motion. Image quality criteria were evaluated on each time frame and compared between these two sequences. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were determined and compared from regions of interest placed on cortical bone, tendon, fat, and muscle. Visualization of anatomical structures and overall image quality appreciation were rated by two radiologists using a 0-10 grading scale.

RESULTS

Mean CNR was significantly higher with bSSFP sequence compared to RF-spoiled sequence. The grading score was in the range of 5-9.3 and was significantly higher with RF-spoiled sequence for bone and joint evaluation and overall image appreciation on the two joints. The standard deviation for SNR, CNR, and grading score during motion was smaller with RF-spoiled sequence for both the joints. The inter-reader reliability was excellent (>0.75) for evaluating anatomical structures in both sequences.

CONCLUSION

A RF-spoiled real-time sequence is recommended for the in vivo clinical evaluation of distal joints on a 3.0-T MRI scanner.

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. Second, an analysis of three bones of the ankle is done to provide a complete view of the ankle joint. Third, a bone shape analysis is carried out at subject level to highlight variability patterns for personnalized understanding of deformities.

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.

METHODS

For this mixed methods sequential explanatory study, we planned to recruit a convenience sample of 45 pregnant women, 45 clinicians from 3 clinical sites, and 15 policy makers. Eligible women were aged >18 years and >16 weeks pregnant or had recently given birth. Eligible clinicians and policy makers were involved in prenatal care. We asked the participants to navigate a computer-based DA. We asked the women about the usefulness of the DA and their self-confidence in decision-making. We asked all participants about usability, quality, acceptability, satisfaction with the content of the DA, and collected sociodemographic data. We explored participants' reactions to the computer-based DA and solicited suggestions. Our interview guide was based on the Mobile App Rating Scale. We performed descriptive analyses of the quantitative data and thematic deductive and inductive analyses of the qualitative data for each participant category.

RESULTS

A total of 45 pregnant women, 14 clinicians, and 8 policy makers participated. Most pregnant women were aged between 25 and 34 years (34/45, 75%) and White (42/45, 94%). Most clinicians were aged between 35 and 44 years (5/14, 36%) and women (11/14, 79%), and all were White (14/14, 100%); the largest proportion of policy makers was aged between 45 and 54 years (4/8, 50%), women (5/8, 62%), and White (8/8, 100%). The mean usefulness score for preparing for decision-making for women was 80/100 (SD 13), and the mean self-efficacy score was 88/100 (SD 11). The mean usability score was 84/100 (SD 14) for pregnant women, 77/100 (SD 14) for clinicians, and 79/100 (SD 23) for policy makers. The mean global score for quality was 80/100 (SD 9) for pregnant women, 72/100 (SD 12) for clinicians, and 80/100 (SD 9) for policy makers. Regarding acceptability, participants found the amount of information just right (52/66, 79%), balanced (58/66, 88%), useful (38/66, 58%), and sufficient (50/66, 76%). The mean satisfaction score with the content was 84/100 (SD 13) for pregnant women, 73/100 (SD 16) for clinicians, and 73/100 (SD 20) for policy makers. Participants thought the DA could be more engaging (eg, more customizable) and suggested strategies for implementation, such as incorporating it into clinical guidelines.

CONCLUSIONS

Pregnant women, clinicians, and policy makers found the DA usable and useful. The next steps are to incorporate user suggestions for improving engagement and implementing the computer-based DA in clinical practice.

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 objective 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). We recruited 61 pregnant women at 10 to 14 weeks' gestation undergoing NIPS. Participants were phlebotomized with Streck and EDTA-gel tubes. EDTA-gel tubes were centrifuged before shipping. Libraries prepared from cell-free DNA (cfDNA) extracted from both types of tubes were sequenced on Illumina NextSeq 500, and fetal fraction was estimated using SeqFF. EDTA-gel tube libraries were size selected on agarose gel to eliminate cfDNA fragments >160 bp and resequenced. The main outcome measure was fetal fraction expressed as percentage of total cfDNA sequenced, calculated from sequence read counts (SeqFF). Streck tube samples showed an average 1% higher fetal fraction than centrifuged EDTA-gel tubes without size selection. This difference increased with temperature. When EDTA-gel samples' libraries were size selected, the mean fetal fraction increased from 7% to 13%, with no sample having fetal fraction <4%. Using EDTA-gel tubes reduces NIPS sampling cost and tube processing time in the laboratory. Also, using EDTA-gel tubes does not lead to cfDNA degradation. Size selection increases fetal fraction, reduces the number of test failures, increases NIPS clinical performance, and may be helpful in situations asking for a higher fetal fraction, such as twin pregnancies or screening for sub-chromosomal imbalances.

Web-Based Training for Nurses on Using a Decision Aid to Support Shared Decision Making about Prenatal Screening: a 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.

Methods

In this 2-arm, parallel controlled trial, French-speaking nurses working with pregnant women in the province of Quebec were recruited by a private survey firm. They were allocated by convenience either to the intervention group (web-based SDM course that included prenatal screening) or to the control group (web-based course focusing on prenatal screening alone, with no SDM content). The primary outcome was the intention to use a decision aid. Secondary outcomes were psychosocial variables of intention, knowledge, satisfaction, acceptability, perceived usefulness, and reaction to the pedagogical approach. All outcomes were self-assessed through web-based questionnaires, including the space for written comments. We used 2-tailed Student t test and Fisher exact test to compare continuous and categorical variables between groups, respectively.

Results

Of the 57 participants assessed for eligibility, 40 (70%) were allocated to the intervention (n=20) or control group (n=20) and 36 (n=18 in each) completed the courses. The mean age of the participants was 41 (SD 9) years. Most were women (39/40, 98%), White (38/40, 95%), clinical nurses (28/40, 70%), and had completed at least a bachelor’s degree (30/40, 75%). After the intervention, the mean score of intention was 6.3 (SD 0.8; 95% CI 5.9-6.7) for the intervention group and 6.0 (SD 1.2; 95% CI 5.42-6.64) for the control group (scale 1-7). The differences in intention and other psychosocial variable scores between the groups were not statistically significant. Knowledge scores for SDM were significantly higher in the intervention group (79%, 95% CI 70-89 vs 64%, 95% CI 57-71; P=.009). The intervention was significantly more acceptable in the intervention group (4.6, 95% CI 4.4-4.8 vs 4.3, 95% CI 4.1-4.5; P=.02), and reaction to the pedagogical approach was also significantly more positive in the intervention group (4.7, 95% CI 4.5-4.8 vs 4.4, 95% CI 4.2-4.5; P=.02). There was no significant difference in overall satisfaction (or in perceived usefulness). Furthermore, 17 participants (9 in the intervention group and 8 in the control group) provided written comments on the intervention.

Conclusions

This study focuses on web-based nursing education and its potential to support pregnant women’s decision-making needs. It shows that nurses’ intention to use a decision aid to enhance SDM in prenatal care is high, with or without training, but that their knowledge about SDM can be improved with web-based training.

International Registered Report Identifier (IRRID)

RR2-10.2196/17878

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.

METHODS

A total of 3,568 maternal blood samples across Canada were collected in either EDTA, or Streck tubes, and processing metrics, maternal body mass index (BMI), gestational age and fetal karyotype and sex were recorded. Plasma samples were sequenced using two different sequencing platforms in separate laboratories. Sequencing data were processed with SeqFF to estimate FF. Linear regression and multivariate imputation by chained equations were used to estimate the adjusted effect of tube type on cfDNA and FF.

RESULTS

We found a positive association between cfDNA quantity and blood shipment time in EDTA tubes, which is significantly reduced with the use of Streck tubes. Furthermore, we show the storage of plasma at -80 °C is associated with a 4.4% annual relative decrease in cfDNA levels. FF was not associated with collection tube type when controlling for confounding variables. However, FF was positively associated with gestational age and trisomy 21, while negatively associated with BMI, male fetus, trisomy 18, Turners syndrome and triploidy.

CONCLUSIONS

Preexamination, maternal and fetal variables are associated with cfDNA quantity and FF. The consideration of these variables in future studies may help to reduce the number of pregnant women with inconclusive tests as a result of low FF.

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. Additionally to the discriminator which enforces the model to create realistic organ delineations, it embeds cascaded partially pre-trained convolutional encoder-decoders as generator. Encoder fine-tuning from a large amount of non-medical images alleviates data scarcity limitations. The network is trained end-to-end to benefit from simultaneous multi-level segmentation refinements using auto-context. Employed for healthy liver, kidneys and spleen segmentation, our pipeline provides promising results by outperforming state-of-the-art encoder-decoder schemes. Followed for the Combined Healthy Abdominal Organ Segmentation (CHAOS) challenge organized in conjunction with the IEEE International Symposium on Biomedical Imaging 2019, it gave us the first rank for three competition categories: liver CT, liver MR and multi-organ MR segmentation. Combining cascaded convolutional and adversarial networks strengthens the ability of deep learning pipelines to automatically delineate multiple abdominal organs, with good generalization capability. The comprehensive evaluation provided suggests that better guidance could be achieved to help clinicians in abdominal image interpretation and clinical decision making.

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). These studies have used a variety of imaging techniques (e.g., fMRI, electroencephalography, diffusion-weighted and myelin-sensitive imaging) and connectivity estimators to model brain networks. Results are promising in terms of interpretability and functional relevance, but methodologies and terminology are variable. The goals of this paper are twofold. First, we summarize recent contributions related to connectivity gradients and graph signal processing, and attempt a clarification of the terminology and methods used in the field, while pointing out current methodological limitations. Second, we discuss the perspective that the functional relevance of connectivity gradients could be fruitfully exploited by considering them as graph Fourier bases of brain activity.

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. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients compared to healthy controls in order to define the cortical and subcortical connections that can reflect the motor outcome.

Methods

Thirty healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1‐weighted and diffusion‐weighted imaging.

Results

Significant disconnections in the lesioned and contra‐lesioned hemispheres of patients were found. Furthermore, significant correlations were detected between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients.

Interpretation

Using the connectivity measures of these links, the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS.

SPLICELECT™: an adaptable cell surface display technology based on alternative splicing allowing the qualitative and quantitative prediction of secreted product at a single-cell level

We describe a mammalian expression construct (SPLICELECT™) that allows the redirection of a proportion of a secreted protein onto the cell surface using alternative splicing: whereas the majority of the RNA is spliced into a transcript encoding a secreted protein, a weak splice donor site yields a secondary transcript encoding, in addition, a C-terminal transmembrane domain. The different sequence elements can be modified in order to modulate the level of cell surface display and of secretion in an independent manner. In this work, we demonstrated that the cell surface display of stable cell lines is correlated with the level of the secreted protein of interest, but also with the level of heterodimerization in the case of a bispecific antibody. It was also shown that this construct may be useful for rapid screening of multiple antibody candidates in binding assays following transient transfection. Thus, the correlation of product quantity and quality of the secreted and of membrane-displayed product in combination with the flexibility of the construct with regards to cell surface display/secretion levels make SPLICELECT™ a valuable tool with many potential applications, not limited to industrial cell line development or antibody engineering.

Investigating the causal role of MRE11A p.E506* in breast and ovarian cancer

The nuclease MRE11A is often included in genetic test panels for hereditary breast and ovarian cancer (HBOC) due to its BRCA1-related molecular function in the DNA repair pathway. However, whether MRE11A is a true predisposition gene for HBOC is still questionable. We determined to investigate this notion by dissecting the molecular genetics of the c.1516G > T;p.E506* truncating MRE11A variant, that we pinpointed in two unrelated French-Canadian (FC) HBOC patients. We performed a case–control study for the variant in ~ 2500 breast, ovarian, and endometrial cancer patients from the founder FC population of Quebec. Furthermore, we looked for the presence of second somatic alterations in the MRE11A gene in the tumors of the carriers. In summary, these investigations suggested that the identified variant is not associated with an increased risk of developing breast or ovarian cancer. We finally performed a systematic review for all the previously reported MRE11A variants in breast and ovarian cancer. We found that MRE11A germline variants annotated as pathogenic on ClinVar often lacked evidence for such classification, hence misleading the clinical management for affected patients. In summary, our report suggests the lack of clinical utility of MRE11A testing in HBOC, at least in the White/Caucasian populations.

Identification of Predictors of Abnormal Calcium, Magnesium and Phosphorus Blood Levels in the Emergency Department: A Retrospective Cohort Study

Purpose

With rising healthcare costs limiting access to care, the judicious use of diagnostic tests has become a critical issue for many jurisdictions. Calcium, magnesium and phosphorus serum levels are regularly performed tests in the emergency department, but their clinical relevance have come into question. Authors sought to determine risk factors that could predict abnormal calcium, magnesium and phosphorus serum levels, as well as identify patients who may need corrective interventions.

Methods

A retrospective cohort study was conducted in two academic hospitals in Québec City. Demographic and clinical characteristics of 1008 patients who had serum calcium and/or magnesium and/or phosphorus levels drawn by an emergency physician were collected. Multivariate logistic regression models were fitted to obtain adjusted odds ratios for each risk factor for abnormal calcium or magnesium or phosphorus blood levels, and for a required intervention.

Results

Among patients for whom calcium, magnesium and phosphorus were tested in the Emergency Department, the most significant risk factors (OR>2) for electrolytic abnormality were as follows: hypocalcemia – respiratory distress, diuretics (excluding loop and thiazide), anti-neoplastic medication, long QTc, chronic kidney disease (CKD); hypercalcemia – bone pain, vitamin D, hallucinations; hypomagnesemia – diabetes, corticosteroids; hypermagnesemia – poor extremity perfusion, CKD, furosemide; hypophosphatemia – seizure; hyperphosphatemia – phosphate-binders, CKD, peripheral vascular atherosclerotic disease. Of all patients tested, 3.4% received a corrective intervention initiated by the emergency physician. Predictors of intervention on an electrolyte abnormality include poor peripheral perfusion, nausea and chronic obstructive pulmonary disease (COPD).

Conclusion

Emergency physicians can potentially reduce the unnecessary testing of calcium, magnesium and phosphorus blood levels by targeting patients with high-acuity conditions or chronic comorbidities such as CKD, diabetes and COPD.

Precision of Fetal DNA Fraction Estimation by Quantitative Polymerase Chain Reaction Quantification of a Differently Methylated Target in Noninvasive Prenatal Testing

BACKGROUND

The performance of noninvasive prenatal testing (NIPT) assays is critically determined by the proportion of fetal DNA or fetal fraction (FF). Fetomaternal differential methylation of certain genomic regions has been proposed as a universal marker of fetal origin, and previous reports have suggested the use of methylation-sensitive restriction enzyme (MSRE) assays to estimate FF.

METHODS

We analyzed the performance of FF estimation using an MSRE assay with duplex quantitative polymerase chain reaction (qPCR). Mixtures of genomic DNA from placental cells and from adult women were digested with 2 MSRE and FF estimates obtained, for a total of 221 pairwise treatment/control comparisons.

RESULTS

The coefficient of variance (CV) of the MSRE assays was high, ranging from 24% to 60%. An alternative in silico FF estimation algorithm, SeqFF, displayed slightly lower variability, with a CV of 22%.

CONCLUSION

These results cast doubts on the usefulness of the MSRE-based assay of differentially methylated markers for FF estimation. The lack of a universal method capable of precisely estimating FF remains an incompletely solved issue.

Validation of a New Protocol to Collect and Isolate Plasma from Pregnant Women for Noninvasive Prenatal Testing (NIPT)

BACKGROUND

Most laboratories use specialized tubes (e.g., Streck) to recover circulating cell-free DNA (ccfDNA) for noninvasive prenatal testing (NIPT). We validated a low cost, simple procedure for collecting NIPT samples in remote laboratories that avoids highspeed centrifugation. EDTA gel blood sampling tube allows simple separation of plasma from blood cells. Decanted plasma is filtered to remove cell debris. The procedure can be performed within a few minutes after the blood centrifugation step, and ccfDNA-grade plasma can be frozen for transportation.

METHODS

We recruited 51 pregnant women and collected blood in one EDTA-gel Greiner tube and two Streck tubes. All tubes were centrifuged at 1600 g x 10 min within 6 h of sample collection. Plasma from EDTA tubes was poured into a syringe cylinder and filtered through a 0.45 µm Millipore filter. Plasma from Streck tubes was recovered with a pipette and one was filtered as above while the second was centrifuged at 16 000 g. The ccfDNA was isolated and NGS sequencing libraries were prepared and sequenced on an Illumina system. Fetal fractions were estimated using SeqFF. This study had a power of 79% to detect a decrease of 1% in fetal fractions with the new method.

RESULTS

We did not observe any significant difference between the three procedures for the fetal fraction nor for the quality or quantity of libraries produced.

CONCLUSION

EDTA-gel tubes with filtration provide high quality plasma for ccfDNA analysis and can be sent frozen to the NIPT laboratory. This is economical and it frees the laboratory of time-consuming steps.

Introducing cell-free DNA noninvasive testing in a Down syndrome public health screening program: a budget impact analysis

BACKGROUND

Non-invasive prenatal testing (NIPT) using cell-free fetal DNA in maternal plasma is a high accurate test for prenatal screening for Down syndrome. Although it has been reported to be cost effective as a contingent test, evidence about its budget impact is lacking.

OBJECTIVE

To evaluate, using computer simulations, the budget impact of implementing NIPT as a contingent test in the Quebec Program of screening for Trisomy 21.

METHODS

A semi-Markov analytic model built to simulate the budget impact of implementing NIPT into the current Quebec Trisomy 21 public Prenatal Screening, Serum Integrated prenatal screening (SIPS). Comparisons were made for a virtual population similar to that of expected Quebec pregnant women in 2015 in terms of size and age. Data input parameters were retrieved from a thorough literature search and in government databases, especially data from Quebec Program of screening for Trisomy 21. The 2015-2016 fiscal year budget impact was estimated from the Quebec healthcare system perspective and was expressed as the difference in the overall costs between the two alternatives (SIPS minus SPS + NIPT).

RESULTS

Our study found that, at a baseline cost for NIPT of CAD$ 795, NIPT as a second-tier test offered to high-risk women identified by current screening program (SIPS + NIPT) may be affordable for Quebec health care system. Compared to the current screening program, it would be implemented at a neutral cost, considering a modest annual savings of $ 80,432 (95% CI $ 79, $ 874-$ 81,462). Results were sensitive to the NIPT costs and the uptake-rate of invasive diagnostic tests.

CONCLUSION

Introducing NIPT as a contingent test in the Quebec Trisomy 21 screening program is an affordable strategy compared to the current practice. Further research is needed to confirm if our results can be reproduced in other healthcare jurisdictions.

Dynamic MRI for articulating joint evaluation on 1.5 T and 3.0 T scanners: setup, protocols, and real-time sequences

Dynamic magnetic resonance imaging (MRI) is a non-invasive method that can be used to increase the understanding of the pathomechanics of joints. Various types of real-time gradient echo sequences used for dynamic MRI acquisition of joints include balanced steady-state free precession sequence, radiofrequency-spoiled sequence, and ultra-fast gradient echo sequence. Due to their short repetition time and echo time, these sequences provide high temporal resolution, a good signal-to-noise ratio and spatial resolution, and soft tissue contrast. The prerequisites of the evaluation of joints with dynamic MRI include suitable patient installation and optimal positioning of the joint in the coil to allow joint movement, sometimes with dedicated coil support. There are currently few recommendations in the literature regarding appropriate protocol, sequence standardizations, and diagnostic criteria for the use of real-time dynamic MRI to evaluate joints. This article summarizes the technical parameters of these sequences from various manufacturers on 1.5 T and 3.0 T MRI scanners. We have reviewed pertinent details of the patient and coil positioning for dynamic MRI of various joints. The indications and limitations of dynamic MRI of joints are discussed.

Is the Blood Oxygenation Level-Dependent fMRI Response to Motor Tasks Altered in Children After Neonatal Stroke?

Functional MRI is increasingly being used in the assessment of brain activation and connectivity following stroke. Many of these studies rely on the Blood Oxygenation Level Dependent (BOLD) contrast. However, the stability, as well as the accuracy of the BOLD response to motor task in the ipsilesional hemisphere, remains ambiguous. In this work, the BOLD signal acquired from both healthy and affected hemispheres was analyzed in 7-year-old children who sustained a Neonatal Arterial Ischemic Stroke (NAIS). Accordingly, a repetitive motor task of the contralesional and the ipsilesional hands was performed by 33 patients with unilateral lesions. These patients were divided into two groups: those without cerebral palsy (NAIS), and those with cerebral palsy (CP). The BOLD signal time course was obtained from distinctly defined regions of interest (ROIs) extracted from the functional activation maps of 30 healthy controls with similar age and demographic characteristics as the patients. An ROI covering both the primary motor cortex (M1) and the primary somatosensory cortex (S1) was also tested. Compared with controls, NAIS patients without CP had similar BOLD amplitude variation for both the contralesional and the ipsilesional hand movements. However, in the case of NAIS patients with CP, a significant difference in the averaged BOLD amplitude was found between the healthy and affected hemisphere. In both cases, no progressive attenuation of the BOLD signal amplitude was observed throughout the task epochs. Besides, results also showed a correlation between the BOLD signal percentage variation of the lesioned hemisphere and the dexterity level. These findings suggest that for patients who sustained a NAIS with no extensive permanent motor impairment, BOLD signal-based data analysis can be a valuable tool for the evaluation of functional brain networks.

SegSRGAN: Super-resolution and segmentation using generative adversarial networks - Application to neonatal brain MRI

BACKGROUND AND OBJECTIVE

One of the main issues in the analysis of clinical neonatal brain MRI is the low anisotropic resolution of the data. In most MRI analysis pipelines, data are first re-sampled using interpolation or single image super-resolution techniques and then segmented using (semi-)automated approaches. In other words, image reconstruction and segmentation are then performed separately. In this article, we propose a methodology and a software solution for carrying out simultaneously high-resolution reconstruction and segmentation of brain MRI data.

METHODS

Our strategy mainly relies on generative adversarial networks. The network architecture is described in detail. We provide information about its implementation, focusing on the most crucial technical points (whereas complementary details are given in a dedicated GitHub repository). We illustrate the behavior of the proposed method for cortex analysis from neonatal MR images.

RESULTS

The results of the method, evaluated quantitatively (Dice, peak signal-to-noise ratio, structural similarity, number of connected components) and qualitatively on a research dataset (dHCP) and a clinical one (Epirmex), emphasize the relevance of the approach, and its ability to take advantage of data-augmentation strategies.

CONCLUSIONS

Results emphasize the potential of our proposed method/software with respect to practical medical applications. The method is provided as a freely available software tool, which allows one to carry out his/her own experiments, and involve the method for the super-resolution reconstruction and segmentation of arbitrary cerebral structures from any MR image dataset.

Regional brain development analysis through registration using anisotropic similarity, a constrained affine transformation

We propose a novel method to quantify brain growth in 3 arbitrary orthogonal directions of the brain or its sub-regions through linear registration. This is achieved by introducing a 9 degrees of freedom (dof) transformation called anisotropic similarity which is an affine transformation with constrained scaling directions along arbitrarily chosen orthogonal vectors. This gives the opportunity to extract scaling factors describing brain growth along those directions by registering a database of subjects onto a common reference. This information about directional growth brings insights that are not usually available in longitudinal volumetric analysis. The interest of this method is illustrated by studying the anisotropic regional and global brain development of 308 healthy subjects betwen 0 and 19 years old. A gender comparison of those scaling factors is also performed for four age-intervals. We demonstrate through these applications the stability of the method to the chosen reference and its ability to highlight growth differences accros regions and gender.

Noninvasive Prenatal Testing for Trisomies 21, 18, and 13, Sex Chromosome Aneuploidies, and Microdeletions in Average-Risk Pregnancies: A Cost-Effectiveness Analysis

OBJECTIVE

The cost effectiveness of noninvasive prenatal testing (NIPT) has been established for high-risk pregnancies but remains unclear for pregnancies at other risk levels. The aim was to assess the cost effectiveness of NIPT in average-risk pregnancies from the perspective of a provincial public payer in Canada.

METHODS

A model was developed to compare traditional prenatal screening (TPS), NIPT as a second-tier test (performed only after a positive TPS result), and NIPT as a first-tier test (performed instead of TPS) for trisomies 21, 18, and 13; sex chromosome aneuploidies; and microdeletions in a hypothetical annual population cohort of average-risk pregnancies (142 000 to 148,000) in Ontario, Canada. A probabilistic analysis was conducted with 5000 repetitions.

RESULTS

Compared with TPS, NIPT as a second-tier test detected more affected fetuses with trisomies 21, 18, and 13 (188 vs. 158), substantially reduced the number of diagnostic tests (i.e., chorionic villus sampling and amniocentesis) performed (660 vs. 3107), and reduced the cost of prenatal screening ($26.7 million vs. $27.6 million) annually. Compared with second-tier NIPT, first-tier NIPT detected an additional 80 cases of trisomies 21, 18, and 13 at an additional cost of $33 million. The incremental cost per additional affected fetus detected was $412 411. Extending first-tier NIPT to include testing for sex chromosome aneuploidies and 22q11.2 deletion would increase the total screening cost.

CONCLUSIONS

NIPT as a second-tier test is cost-saving compared with TPS alone. Compared with second-tier NIPT, first-tier NIPT detects more cases of chromosomal anomalies but at a substantially higher cost.

Temporal resolution enhancement of dynamic MRI sequences within a motion-based framework

Dynamic MRI has made it possible to non-invasively capture the moving human joints in vivo. Real-time Fast Field Echo (FFE) sequences have the potential to reduce the effect of motion artifacts by acquiring the image data within a few milliseconds. However, the short acquisition times affect the temporal resolution of the acquired sequences. In this paper, we propose a post-processing technique to reconstruct the missing frames of the sequence given the reduced amount of acquired data, which leads to recover the entire joint trajectory outside the MR scanner. To do this, we generalize the Log-Euclidean polyrigid registration framework to deal with dynamic three-dimensional articulated structures by adding the time as fourth dimension : we first estimate the rigid motion of each bone from the acquired data using linear intensity-based registration. Then, we fuse these local transformations to compute the non-linear joint deformations between successive images using a spatio-temporal log-euclidean polyrigid framework. The idea is to reconstruct the missing time frames by interpolating the realistic joint deformation fields in the domain of matrix logarithms assuming the motion to be consistent over a short period of time. The algorithm has been applied and validated using dynamic data from five children performing passive ankle dorsi-plantar flexion.

Evaluation of cortical segmentation pipelines on clinical neonatal MRI data

Magnetic Resonance Imaging (MRI) can provide 3D morphological information on brain structures. Such information is particularly relevant for carrying out morphometric brain analysis, especially in the newborn and in the case of prematurity. However, 3D neonatal MRI acquired in clinical environments are low-resolution, anisotropic images, making segmentation a challenging task. In this context, preprocessing techniques aim to increase the image resolution. Interpolation techniques were classically used; super-resolution (SR) techniques have recently appeared as an emerging alternative. In this paper, we evaluate the performance of different SR methods against the classical interpolation in the application of neonatal cortex segmentation. Additionally, we assess the robustness of different segmentation methods for each estimation of high resolution MRI input. Results are evaluated both qualitatively and quantitatively with neonatal clinical MRI.

4D in vivo quantification of ankle joint space width using dynamic MRI

Spatio-temporal evolution of joint space width (JSW) during motion is of great importance to help with making early treatment plans for degenerative joint diseases like osteoarthritis (OA). These diseases can affect people of all ages leading to an acceleration of joint degeneration and to limitations in the activities of daily living. However, only a few studies have attempted to quantify the JSW from moving joints. In this paper, we present a generic pipeline to accurately determine the changes of the JSW during the joint motion cycle. The key idea is to combine spatial information of static MRI with temporal information of low-resolution (LR) dynamic MRI sequences via an intensity-based registration framework, leading to a high-resolution (HR) temporal reconstruction of the joint. This allows the temporal JSW to be measured in the HR domain using an Eulerian approach for solving partial differential equations (PDEs) inside a deforming inter-bone area where the HR reconstructed bone segmentations are considered as temporal Dirichlet boundaries. The proposed approach has been applied and evaluated on in vivo MRI data of five healthy children to non-invasively quantify the spatio-temporal evolution of the JSW of the ankle (tibiotalar joint) during the entire dorsi-plantar flexion motion cycle. Promising results were obtained, showing that this pipeline can be useful to perform large-scale studies containing subjects with OA for different joints like ankle and knee.

Global Perturbation of Initial Geometry in a Biomechanical Model of Cortical Morphogenesis

Cortical folding pattern is a main characteristic of the geometry of the human brain which is formed by gyri (ridges) and sulci (grooves). Several biological hypotheses have suggested different mechanisms that attempt to explain the development of cortical folding and its abnormal evolutions. Based on these hypotheses, biomechanical models of cortical folding have been proposed. In this work, we compare biomechanical simulations for several initial conditions by using an adaptive spherical parameterization approach. Our approach allows us to study and explore one of the most potential sources of reproducible cortical folding pattern: the specification of initial geometry of the brain.

Muscle MRI: A biomarker of disease severity in Duchenne muscular dystrophy? A systematic review

OBJECTIVE

To assess the evidence of a relationship between muscle MRI and disease severity in Duchenne muscular dystrophy (DMD).

METHODS

We conducted a systematic review of studies that analyzed correlations between MRI measurements and motor function in patients with DMD. PubMed, Cochrane, Scopus, and Web of Science were searched using relevant keywords and inclusion/exclusion criteria (January 1, 1990-January 31, 2019). We evaluated article quality using the Joanna Briggs Institute scale. Information regarding the samples included, muscles evaluated, MRI protocols and motor function tests used was collected from each article. Correlations between MRI measurements and motor function were reported exhaustively.

RESULTS

Seventeen of 1,629 studies identified were included. Most patients included were ambulant with a mean age of 8.9 years. Most studies evaluated lower limb muscles. Moderate to excellent correlations were found between MRI measurements and motor function. The strongest correlations were found for quantitative MRI measurements such as fat fraction or mean T2. Correlations were stronger for lower leg muscles such as soleus. One longitudinal study reported that changes in soleus mean T2 were highly correlated with changes in motor function.

CONCLUSION

The findings of this systematic review showed that MRI measurements can be used as biomarkers of disease severity in ambulant patients with DMD. Guidelines are proposed to help clinicians choose the most appropriate MRI measurements and muscles to evaluate. Studies exploring upper limb muscles, other stages of the disease, and sensitivity of measurements to change are needed.

A new deep learning-based method for the detection of gait events in children with gait disorders: Proof-of-concept and concurrent validity

The stance and swing phases of the gait cycle are defined by foot strike (FS) and foot off (FO). Accurate determination of these events is thus an essential component of 3D motion recordings processing. Several methods have been developed for the automatic detection of these events (based on the heuristics of 3D marker position, velocity and acceleration), however the results may be inaccurate due to the high variability that is intrinsic to pathological gait. For this reason, gait events are still commonly determined manually, which is a tedious process. Here we propose a new application (DeepEvent) of a long short term memory recurrent neural network for the automatic detection of gait events. The 3D position and velocity of the markers on the heel, toe and lateral malleolus were used by the network to determine FS and FO. The method was developed from 10526 FS and 9375 FO from 226 children. DeepEvent predicted FS within 5.5 ms and FO within 10.7 ms of the gold standard (automatic determination using force platform data) and was more accurate than common heuristic marker trajectory-based methods proposed in the literature and another deep learning method. A sensitivity analysis showed that DeepEvent mainly used the toe and heel markers (z-axis (longitudinal) position and velocity) at the beginning and end of gait cycle to predict FS, and the toe marker (x-axis (anterior/posterior) velocity and z-axis position and velocity) at around 60% of the gait cycle to predict FO.

An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study

BACKGROUND

Decisions about prenatal screening to assess the risk of genetic conditions such as Down syndrome are complex and should be well informed. Moreover, the number of available tests is increasing. Shared decision making (SDM) about testing could be facilitated by decision aids powered by mobile technology.

OBJECTIVE

In this mixed methods study, we aim to (1) assess women's needs and preferences regarding using an app for considering prenatal screening, (2) develop a decision model using the analytical hierarchy process, and (3) develop an analytical app and assess its usability and usefulness.

METHODS

In phase 1, we will assess the needs of 90 pregnant women and their partners (if available). We will identify eligible participants in 3 clinical sites (a midwife-led birthing center, a family practice clinic, and an obstetrician-led hospital-based clinic) in Quebec City and Montreal, Canada. Using semistructured interviews, we will assess participants' attitudes toward mobile apps for decision making about health, their current use of apps for health purposes, and their expectations of an app for prenatal testing decisions. Self-administered questionnaires will collect sociodemographic information, intentions to use an app for prenatal testing, and perceived importance of decision criteria. Qualitative data will be transcribed verbatim and analyzed thematically. Quantitative data will be analyzed using descriptive statistics and the analytic hierarchy process (AHP) method. In phase 2, we will develop a decision model using the AHP whereby users can assign relative importance to criteria when deciding between options. We will validate the model with potential users and a multidisciplinary team of patients, family physicians, primary care researchers, decision sciences experts, engineers, and experts in SDM, genetics, and bioethics. In phase 3, we will develop a prototype of the app using the results of the first 2 phases, pilot test its usefulness and usability among a sample of 15 pregnant women and their partners (if available), and improve it through 3 iterations. Data will be collected with a self-administered questionnaire. Results will be analyzed using descriptive statistics.

RESULTS

Recruitment for phase 1 will begin in 2019. We expect results to be available in 2021.

CONCLUSIONS

This study will result in a validated analytical app that will provide pregnant women and their partners with up-to-date information about prenatal screening options and their risks and benefits. It will help them clarify their values and enable them to weigh the options to make informed choices consistent with their preferences and values before meeting face-to-face with their health care professional. The app will be easy to update with the latest information and will provide women with a user-friendly experience using their smartphones or tablets. This study and the resulting app will contribute to high-quality SDM between pregnant women and their health care team.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/13321.

Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination

Myelin imaging in the central nervous system is essential for monitoring pathologies involving white matter alterations. Various quantitative MRI protocols relying on the modeling of the interactions of water protons with myelinated tissues have shown sensitivities in case of myelin disruption. Some extracted model parameters are more sensitive to demyelination, such as the bound pool fraction (f) in quantitative magnetization transfer imaging (qMTI), the radial diffusivity in diffusion tensor imaging (DTI), and the myelin water fraction (MWF) in myelin water imaging (MWI). A 3D ultrashort echo time (UTE) sequence within an appropriate water suppression condition (Diff-UTE) is also considered for the direct visualization of the myelin semi-solid matrix (Diff-UTE normalized signal; rSPF). In this paper, we aimed at assessing the sensitivities and correlations of the parameters mentioned above to an immuno-histological study of the myelin basic protein (MBP) in a murine model of demyelination at 7 T. We demonstrated a high sensitivity of the MRI metrics to demyelination, and strong Spearman correlations in the corpus callosum between histology, macromolecular proton fraction (ρ>0.87) and Diff-UTE signal (ρ>0.76), but moderate ones with radial diffusivity and MWF (|ρ|<0.70).

Multiscale brain MRI super-resolution using deep 3D convolutional networks

The purpose of super-resolution approaches is to overcome the hardware limitations and the clinical requirements of imaging procedures by reconstructing high-resolution images from low-resolution acquisitions using post-processing methods. Super-resolution techniques could have strong impacts on structural magnetic resonance imaging when focusing on cortical surface or fine-scale structure analysis for instance. In this paper, we study deep three-dimensional convolutional neural networks for the super-resolution of brain magnetic resonance imaging data. First, our work delves into the relevance of several factors in the performance of the purely convolutional neural network-based techniques for the monomodal super-resolution: optimization methods, weight initialization, network depth, residual learning, filter size in convolution layers, number of the filters, training patch size and number of training subjects. Second, our study also highlights that one single network can efficiently handle multiple arbitrary scaling factors based on a multiscale training approach. Third, we further extend our super-resolution networks to the multimodal super-resolution using intermodality priors. Fourth, we investigate the impact of transfer learning skills onto super-resolution performance in terms of generalization among different datasets. Lastly, the learnt models are used to enhance real clinical low-resolution images. Results tend to demonstrate the potential of deep neural networks with respect to practical medical image applications.

Measuring the chronology of the translational process of molecular genetic discoveries

Background

The process of technology validation and transfer of new molecular diagnostic tests towards the clinic faces challenges and needs to be improved. There is no empirical measure of the chronology and pace of technology transfer of molecular genetic discoveries.

Methods

We studied these for 29 molecular genetic test discoveries in order to (1) provide estimates of the timeframe between discovery of a clinical application and complete clinical implementation, and (2) compare the trajectories between different new tests to identify common patterns. We identified 11 publicly available “timestamps” for the technology transfer process ranging from discovery of the marker to use in a clinical setting. For each test selected, we searched public databases to identify available timestamps and dates. We plotted and compared trajectories of individual tests, including chronology.

Results

We show that there is much variability in the chronology of transfer between biomarkers. The median time between discovery of the marker and availability of the clinical test was 9.5 years (minimum 1). There was a median time of 18 years between test discovery and FDA approval (minimum 7 years), and it took a median of 17 years between discovery and the availability of a certified reference material for the 10 assays that have one (minimum 9 years).

Conclusions

We conclude that new molecular genetic tests take significant time between discovery and clinical implementation, and that further work is needed to pinpoint key factors, including policy and organization factors, that may allow for improving and streamlining this process.

Cardiotrophin-like cytokine (CLCF1) modulates mesenchymal stem cell osteoblastic differentiation

Mesenchymal stem cells (MSCs) are multipotent cells capable of differentiating into adipocytes, chondrocytes, or osteocytes. MSCs secrete an array of cytokines and express the LIFRβ (leukemia inhibitory factor receptor) chain on their surface. Mutations in the gene coding for LIFRβ lead to a syndrome with altered bone metabolism. LIFRβ is one of the signaling receptor chains for cardiotrophin-like cytokine (CLCF1), a neurotrophic factor known to modulate B and myeloid cell functions. We investigated its effect on MSCs induced to differentiate into osteocytes in vitro Our results indicate that CLCF1 binds mouse MSCs, triggers STAT1 and -3 phosphorylation, inhibits the up-regulation of master genes involved in the control of osteogenesis, and markedly prevents osteoblast generation and mineralization. This suggests that CLCF1 could be a target for therapeutic intervention with agents such as cytokine traps or blocking mAbs in bone diseases such as osteoporosis.

Alterations in Cortical Morphology after Neonatal Stroke: Compensation in the Contralesional Hemisphere?

Although neonatal arterial ischemic stroke is now well-studied, its complex consequences on long-term cortical brain development has not yet been solved. In order to understand the brain development after focal early brain lesion, brain morphometry needs to be evaluated using structural parameters. In this work, our aim was to study and analyze the changes in morphometry of ipsi- and contralesional hemispheres in seven-year-old children following neonatal stroke. Therefore, we used surface-based morphometry in order to examine the cortical thickness, surface area, cortical volume, and local gyrification index in two groups of children that suffered from neonatal stroke in the left (n = 19) and right hemispheres (n = 15) and a group of healthy controls (n = 30). Reduced cortical thickness, surface area, and cortical volumes were observed in the ipsilesional hemispheres for both groups in comparison with controls. For the group with left-sided lesions, higher gyrification of the contralesional hemisphere was observed primarily in the occipital region along with higher surface area and cortical volume. As for the group with right-sided lesions, higher gyrification was detected in two separate clusters also in the occipital lobe of the contralesional hemisphere, without a significant change in cortical thickness, surface area, or cortical volume. This is the first time that alterations of structural parameters are detected in the "healthy" hemisphere after unilateral neonatal stroke indicative of a compensatory phenomenon. Moreover, findings presented in this work suggest that lesion lateralization might have an influence on brain development and maturation.

Development of Reference Materials for Noninvasive Prenatal Aneuploidy Testing by Massively Parallel Sequencing: A Proof-of-Concept Study

BACKGROUND

Noninvasive prenatal aneuploidy testing (NIPT) represents the first large-scale clinical application of massively parallel sequencing technology. However, no NIPT reference material (RM) has yet been widely adopted, impeding the development of quality management systems and standardization. Developing an NIPT RM from a biological sample is complicated by the low concentration of cell-free DNA (cfDNA), which implies pooling specimens and frequent resampling.

METHODS

We tested the feasibility of using DNA from immortalized cell lines of a woman and her aneuploid offspring to spike an artificial plasma matrix. Enzymatic fragmentation of extracted DNA was optimized to achieve fragment size profiles with a mode of 150 to 200 bp, similar to biological cfDNA. This synthetic material was compared with routine biological samples from pregnant women by a targeted NIPT assay in a multiplex sequencing run on a Proton platform.

RESULTS

Sequencing statistics were similar between artificially prepared material and routine biological samples, as well as relative chromosomal representation, and no matrix effects could be detected. Estimate of fetal fraction (FF) was within the range of expected value, and aneuploidy detection statistic (z-score) was also comparable between both types of samples.

CONCLUSIONS

Artificial plasma spiked with DNA from cell lines of mother and offspring is a promising strategy for developing NIPT RM. This type of material would offer the advantage of a constant and stable composition, allowing for greater standardization of NIPT assays. Moreover, it preserves the parental relatedness used by targeted assay to estimate FF by identification of paternal alleles in single-nucleotide polymorphisms or other variable regions.

Pregnant women's views on how to promote the use of a decision aid for Down syndrome prenatal screening: a theory-informed qualitative study

Background

For pregnant women and their partners, the decision to undergo Down syndrome prenatal screening is difficult. Patient decision aids (PtDA) can help them make an informed decision. We aimed to identify behaviour change techniques (BCTs) that would be useful in an intervention to promote the use of a PtDA for Down syndrome prenatal screening, and to identify which of these BCTs pregnant women found relevant and acceptable.

Methods

Using the Behaviour Change Wheel and the Theoretical Domains Framework, we conducted a qualitative descriptive study. First, a group of experts from diverse professions, disciplines and backgrounds (eg. medicine, engineering, implementation science, community and public health, shared decision making) identified relevant BCTs. Then we recruited pregnant women consulting for prenatal care in three clinical sites: a family medicine group, a birthing centre (midwives) and a hospital obstetrics department in Quebec City, Canada. To be eligible, participants had to be at least 18 years old, having recently given birth or at least 16 weeks pregnant with a low-risk pregnancy, and have already decided about prenatal screening. We conducted three focus groups and asked questions about the relevance and acceptability of the BCTs. We analysed verbatim transcripts and reduced the BCTs to those the women found most relevant and acceptable.

Results

Our group of experts identified 25 relevant BCTs relating to information, support, consequences, others’ approval, learning, reward, environmental change and mode of delivery. Fifteen women participated in the study with a mean age of 27 years. Of these, 67% (n = 10) were pregnant for the first time, 20% (n = 3) had difficulty making the decision to take the test, and 73% had made the decision with their partner. Of the 25 BCTs identified using the Behaviour Change Wheel, the women found the following 10 to be most acceptable and relevant: goal setting (behaviour), goal setting (results), problem solving, action plan, social support (general), social support (practical), restructuring the physical environment, prompts/cues, credible sources and modelling or demonstration of the behaviour.

Conclusions

An intervention to promote PtDA use among pregnant women for Down syndrome prenatal screening should incorporate the 10 BCTs identified.

Psychosocial Factors of Health Professionals' Intention to Use a Decision Aid for Down Syndrome Screening: Cross-Sectional Quantitative Study

Background

Decisions about prenatal screening for Down syndrome are difficult for women, as they entail risk, potential loss, and regret. Shared decision making increases women’s knowledge of their choices and better aligns decisions with their values. Patient decision aids foster shared decision making but are rarely used in this context.

Objective

One of the most promising strategies for implementing shared decision making is distribution of decision aids by health professionals. We aimed to identify factors influencing their intention to use a DA during prenatal visit for decisions about Down syndrome screening.

Methods

We conducted a cross-sectional quantitative study. Using a Web panel, we conducted a theory-based survey of health professionals in Quebec province (Canada). Eligibility criteria were as follows: (1) family physicians, midwives, obstetrician-gynecologists, or trainees in these professions; (2) involved in prenatal care; and (3) working in Quebec province. Participants watched a video depicting a health professional using a decision aid during a prenatal consultation with a woman and her partner, and then answered a questionnaire based on an extended version of the theory of planned behavior, including some of the constructs of the theoretical domains framework. The questionnaire assessed 8 psychosocial constructs (attitude, anticipated regret, subjective norm, self-identity, moral norm, descriptive norm, self-efficacy, and perceived control), 7 related sets of behavioral beliefs (advantages, disadvantages, emotions, sources of encouragement or discouragement, incentives, facilitators, and barriers), and sociodemographic data. We performed descriptive, bivariate, and multiple linear regression analyses to identify factors influencing health professionals’ intention to use a decision aid.

Results

Among 330 health professionals who completed the survey, 310 met the inclusion criteria: family physicians, 55.2% (171/310); obstetrician-gynecologists, 33.8% (105/310); and midwives, 11.0% (34/310). Of these, 80.9% were female (251/310). Mean age was 39.6 (SD 11.5) years. Less than half were aware of any decision aids at all. In decreasing order of importance, factors influencing their intention to use a decision aid for Down syndrome prenatal screening were as follows: self-identity (beta=.325, P<.001), attitude (beta=.297, P<.001), moral norm (beta=.288, P<.001), descriptive norm (beta=.166, P<.001), and anticipated regret (beta=.099, P=.003). Underlying behavioral beliefs significantly related to intention were that the use of a decision aid would promote decision making (beta=.117, 95% CI 0.043-0.190), would reassure health professionals (beta=.100, 95% CI 0.024-0.175), and might require more time than planned for the consultation (beta=−.077, 95% CI −0.124 to −0.031).

Conclusions

We identified psychosocial factors that could influence health professionals’ intention to use a decision aid about Down syndrome screening. Strategies should remind them of the following: (1) using a decision aid for this purpose should be a common practice, (2) it would be expected of someone in their societal role, (3) the experience of using it will be satisfying and reassuring, and (4) it is likely to be compatible with their moral values.

Cell-free DNA noninvasive prenatal screening for aneuploidy versus conventional screening: A systematic review of economic evaluations

Although noninvasive prenatal testing (NIPT) for aneuploidies using cell-free fetal DNA in maternal blood has been reported to have a high accuracy, only little evidence about its cost-effectiveness is available. We systematically reviewed and assessed quality of economic evaluation studies published between January 1, 2009 and January 1, 2016 where NIPT was compared to the current screening practices consisting of biochemical markers with or without nuchal translucency (NT) and/or maternal age. We included 16 studies and we found that, at current level of NIPT prices, contingent NIPT provide the best value for money, especially for publicly funded screening programs. NIPT as first-line test was found not cost-effective in the majority of studies. The NIPT unit cost, the risk cut-offs for current screening practice, the screening uptake rates (first- and second-line screening) as well as the costs and uptake rates of invasive diagnostic screening were the most common uncertain variables. The overall quality of included studies was fair. Considering a possible drop in prices and an ongoing NIPT expansion to include other chromosomes abnormalities other than T21, T18, T13 and sex chromosomes aneuploidies, future research are needed to examine the potential cost-effectiveness of implementing NIPT as first-line test.

Genomics-based non-invasive prenatal testing for detection of fetal chromosomal aneuploidy in pregnant women

BACKGROUND

Common fetal aneuploidies include Down syndrome (trisomy 21 or T21), Edward syndrome (trisomy 18 or T18), Patau syndrome (trisomy 13 or T13), Turner syndrome (45,X), Klinefelter syndrome (47,XXY), Triple X syndrome (47,XXX) and 47,XYY syndrome (47,XYY). Prenatal screening for fetal aneuploidies is standard care in many countries, but current biochemical and ultrasound tests have high false negative and false positive rates. The discovery of fetal circulating cell-free DNA (ccfDNA) in maternal blood offers the potential for genomics-based non-invasive prenatal testing (gNIPT) as a more accurate screening method. Two approaches used for gNIPT are massively parallel shotgun sequencing (MPSS) and targeted massively parallel sequencing (TMPS).

OBJECTIVES

To evaluate and compare the diagnostic accuracy of MPSS and TMPS for gNIPT as a first-tier test in unselected populations of pregnant women undergoing aneuploidy screening or as a second-tier test in pregnant women considered to be high risk after first-tier screening for common fetal aneuploidies. The gNIPT results were confirmed by a reference standard such as fetal karyotype or neonatal clinical examination.

SEARCH METHODS

We searched 13 databases (including MEDLINE, Embase and Web of Science) from 1 January 2007 to 12 July 2016 without any language, search filter or publication type restrictions. We also screened reference lists of relevant full-text articles, websites of private prenatal diagnosis companies and conference abstracts.

SELECTION CRITERIA

Studies could include pregnant women of any age, ethnicity and gestational age with singleton or multifetal pregnancy. The women must have had a screening test for fetal aneuploidy by MPSS or TMPS and a reference standard such as fetal karyotype or medical records from birth.

DATA COLLECTION AND ANALYSIS

Two review authors independently carried out study selection, data extraction and quality assessment (using the QUADAS-2 tool). Where possible, hierarchical models or simpler alternatives were used for meta-analysis.

MAIN RESULTS

Sixty-five studies of 86,139 pregnant women (3141 aneuploids and 82,998 euploids) were included. No study was judged to be at low risk of bias across the four domains of the QUADAS-2 tool but applicability concerns were generally low. Of the 65 studies, 42 enrolled pregnant women at high risk, five recruited an unselected population and 18 recruited cohorts with a mix of prior risk of fetal aneuploidy. Among the 65 studies, 44 evaluated MPSS and 21 evaluated TMPS; of these, five studies also compared gNIPT with a traditional screening test (biochemical, ultrasound or both). Forty-six out of 65 studies (71%) reported gNIPT assay failure rate, which ranged between 0% and 25% for MPSS, and between 0.8% and 7.5% for TMPS.In the population of unselected pregnant women, MPSS was evaluated by only one study; the study assessed T21, T18 and T13. TMPS was assessed for T21 in four studies involving unselected cohorts; three of the studies also assessed T18 and 13. In pooled analyses (88 T21 cases, 22 T18 cases, eight T13 cases and 20,649 unaffected pregnancies (non T21, T18 and T13)), the clinical sensitivity (95% confidence interval (CI)) of TMPS was 99.2% (78.2% to 100%), 90.9% (70.0% to 97.7%) and 65.1% (9.16% to 97.2%) for T21, T18 and T13, respectively. The corresponding clinical specificity was above 99.9% for T21, T18 and T13.In high-risk populations, MPSS was assessed for T21, T18, T13 and 45,X in 30, 28, 20 and 12 studies, respectively. In pooled analyses (1048 T21 cases, 332 T18 cases, 128 T13 cases and 15,797 unaffected pregnancies), the clinical sensitivity (95% confidence interval (CI)) of MPSS was 99.7% (98.0% to 100%), 97.8% (92.5% to 99.4%), 95.8% (86.1% to 98.9%) and 91.7% (78.3% to 97.1%) for T21, T18, T13 and 45,X, respectively. The corresponding clinical specificities (95% CI) were 99.9% (99.8% to 100%), 99.9% (99.8% to 100%), 99.8% (99.8% to 99.9%) and 99.6% (98.9% to 99.8%). In this risk group, TMPS was assessed for T21, T18, T13 and 45,X in six, five, two and four studies. In pooled analyses (246 T21 cases, 112 T18 cases, 20 T13 cases and 4282 unaffected pregnancies), the clinical sensitivity (95% CI) of TMPS was 99.2% (96.8% to 99.8%), 98.2% (93.1% to 99.6%), 100% (83.9% to 100%) and 92.4% (84.1% to 96.5%) for T21, T18, T13 and 45,X respectively. The clinical specificities were above 100% for T21, T18 and T13 and 99.8% (98.3% to 100%) for 45,X. Indirect comparisons of MPSS and TMPS for T21, T18 and 45,X showed no statistical difference in clinical sensitivity, clinical specificity or both. Due to limited data, comparative meta-analysis of MPSS and TMPS was not possible for T13.We were unable to perform meta-analyses of gNIPT for 47,XXX, 47,XXY and 47,XYY because there were very few or no studies in one or more risk groups.

AUTHORS' CONCLUSIONS

These results show that MPSS and TMPS perform similarly in terms of clinical sensitivity and specificity for the detection of fetal T31, T18, T13 and sex chromosome aneuploidy (SCA). However, no study compared the two approaches head-to-head in the same cohort of patients. The accuracy of gNIPT as a prenatal screening test has been mainly evaluated as a second-tier screening test to identify pregnancies at very low risk of fetal aneuploidies (T21, T18 and T13), thus avoiding invasive procedures. Genomics-based non-invasive prenatal testing methods appear to be sensitive and highly specific for detection of fetal trisomies 21, 18 and 13 in high-risk populations. There is paucity of data on the accuracy of gNIPT as a first-tier aneuploidy screening test in a population of unselected pregnant women. With respect to the replacement of invasive tests, the performance of gNIPT observed in this review is not sufficient to replace current invasive diagnostic tests.We conclude that given the current data on the performance of gNIPT, invasive fetal karyotyping is still the required diagnostic approach to confirm the presence of a chromosomal abnormality prior to making irreversible decisions relative to the pregnancy outcome. However, most of the gNIPT studies were prone to bias, especially in terms of the selection of participants.