Clinical workflow of sonographers performing fetal anomaly ultrasound scans: deep-learning-based analysis.

OBJECTIVE: Despite decades of obstetric scanning, the field of sonographer workflow remains largely unexplored. In the second trimester, sonographers use scan guidelines to guide their acquisition of standard planes and structures; however, the scan-acquisition order is not prescribed. Using deep-learning-based video analysis, the aim of this study was to develop a deeper understanding of the clinical workflow undertaken by sonographers during second-trimester anomaly scans. METHODS: We collected prospectively full-length video recordings of routine second-trimester anomaly scans. Important scan events in the videos were identified by detecting automatically image freeze and image/clip save. The video immediately preceding and following the important event was extracted and labeled as one of 11 commonly acquired anatomical structures. We developed and used a purposely trained and tested deep-learning annotation model to label automatically the large number of scan events. Thus, anomaly scans were partitioned as a sequence of anatomical planes or fetal structures obtained over time. RESULTS: A total of 496 anomaly scans performed by 14 sonographers were available for analysis. UK guidelines specify that an image or videoclip of five different anatomical regions must be stored and these were detected in the majority of scans: head/brain was detected in 97.2% of scans, coronal face view (nose/lips) in 86.1%, abdomen in 93.1%, spine in 95.0% and femur in 92.3%. Analyzing the clinical workflow, we observed that sonographers were most likely to begin their scan by capturing the head/brain (in 24.4% of scans), spine (in 23.2%) or thorax/heart (in 22.8%). The most commonly identified two-structure transitions were: placenta/amniotic fluid to maternal anatomy, occurring in 44.5% of scans; head/brain to coronal face (nose/lips) in 42.7%; abdomen to thorax/heart in 26.1%; and three-dimensional/four-dimensional face to sagittal face (profile) in 23.7%. Transitions between three or more consecutive structures in sequence were uncommon (up to 13% of scans). None of the captured anomaly scans shared an entirely identical sequence. CONCLUSIONS: We present a novel evaluation of the anomaly scan acquisition process using a deep-learning-based analysis of ultrasound video. We note wide variation in the number and sequence of structures obtained during routine second-trimester anomaly scans. Overall, each anomaly scan was found to be unique in its scanning sequence, suggesting that sonographers take advantage of the fetal position and acquire the standard planes according to their visibility rather than following a strict acquisition order. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Fetal cerebellar growth and Sylvian fissure maturation: international standards from Fetal Growth Longitudinal Study of INTERGROWTH-21st Project.

OBJECTIVE: To construct international ultrasound-based standards for fetal cerebellar growth and Sylvian fissure maturation. METHODS: Healthy, well nourished pregnant women, enrolled at < 14 weeks' gestation in the Fetal Growth Longitudinal Study (FGLS) of INTERGROWTH-21st , an international multicenter, population-based project, underwent serial three-dimensional (3D) fetal ultrasound scans every 5 ± 1 weeks until delivery in study sites located in Brazil, India, Italy, Kenya and the UK. In the present analysis, only those fetuses that underwent developmental assessment at 2 years of age were included. We measured the transcerebellar diameter and assessed Sylvian fissure maturation using two-dimensional ultrasound images extracted from available 3D fetal head volumes. The appropriateness of pooling data from the five sites was assessed using variance component analysis and standardized site differences. For each Sylvian fissure maturation score (left or right side), mean gestational age and 95% CI were calculated. Transcerebellar diameter was modeled using fractional polynomial regression, and goodness of fit was assessed. RESULTS: Of those children in the original FGLS cohort who had developmental assessment at 2 years of age, 1130 also had an available 3D ultrasound fetal head volume. The sociodemographic characteristics and pregnancy/perinatal outcomes of the study sample confirmed the health and low-risk status of the population studied. In addition, the fetuses had low morbidity and adequate growth and development at 2 years of age. In total, 3016 and 2359 individual volumes were available for transcerebellar-diameter and Sylvian-fissure analysis, respectively. Variance component analysis and standardized site differences showed that the five study populations were sufficiently similar on the basis of predefined criteria for the data to be pooled to produce international standards. A second-degree fractional polynomial provided the best fit for modeling transcerebellar diameter; we then estimated gestational-age-specific 3rd , 50th and 97th smoothed centiles. Goodness-of-fit analysis comparing empirical centiles with smoothed centile curves showed good agreement. The Sylvian fissure increased in maturation with advancing gestation, with complete overlap of the mean gestational age and 95% CIs between the sexes for each development score. No differences in Sylvian fissure maturation between the right and left hemispheres were observed. CONCLUSION: We present, for the first time, international standards for fetal cerebellar growth and Sylvian fissure maturation throughout pregnancy based on a healthy fetal population that exhibited adequate growth and development at 2 years of age. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology.

Artificial intelligence (AI) uses data and algorithms to aim to draw conclusions that are as good as, or even better than, those drawn by humans. AI is already part of our daily life; it is behind face recognition technology, speech recognition in virtual assistants (such as Amazon Alexa, Apple's Siri, Google Assistant and Microsoft Cortana) and self-driving cars. AI software has been able to beat world champions in chess, Go and recently even Poker. Relevant to our community, it is a prominent source of innovation in healthcare, already helping to develop new drugs, support clinical decisions and provide quality assurance in radiology. The list of medical image-analysis AI applications with USA Food and Drug Administration or European Union (soon to fall under European Union Medical Device Regulation) approval is growing rapidly and covers diverse clinical needs, such as detection of arrhythmia using a smartwatch or automatic triage of critical imaging studies to the top of the radiologist's worklist. Deep learning, a leading tool of AI, performs particularly well in image pattern recognition and, therefore, can be of great benefit to doctors who rely heavily on images, such as sonologists, radiographers and pathologists. Although obstetric and gynecological ultrasound are two of the most commonly performed imaging studies, AI has had little impact on this field so far. Nevertheless, there is huge potential for AI to assist in repetitive ultrasound tasks, such as automatically identifying good-quality acquisitions and providing instant quality assurance. For this potential to thrive, interdisciplinary communication between AI developers and ultrasound professionals is necessary. In this article, we explore the fundamentals of medical imaging AI, from theory to applicability, and introduce some key terms to medical professionals in the field of ultrasound. We believe that wider knowledge of AI will help accelerate its integration into healthcare. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Discovering Salient Anatomical Landmarks by Predicting Human Gaze.

Anatomical landmarks are a crucial prerequisite for many medical imaging tasks. Usually, the set of landmarks for a given task is predefined by experts. The landmark locations for a given image are then annotated manually or via machine learning methods trained on manual annotations. In this paper, in contrast, we present a method to automatically discover and localize anatomical landmarks in medical images. Specifically, we consider landmarks that attract the visual attention of humans, which we term visually salient landmarks. We illustrate the method for fetal neurosonographic images. First, full-length clinical fetal ultrasound scans are recorded with live sonographer gaze-tracking. Next, a convolutional neural network (CNN) is trained to predict the gaze point distribution (saliency map) of the sonographers on scan video frames. The CNN is then used to predict saliency maps of unseen fetal neurosonographic images, and the landmarks are extracted as the local maxima of these saliency maps. Finally, the landmarks are matched across images by clustering the landmark CNN features. We show that the discovered landmarks can be used within affine image registration, with average landmark alignment errors between 4.1% and 10.9% of the fetal head long axis length.

International standards for fetal brain structures based on serial ultrasound measurements from Fetal Growth Longitudinal Study of INTERGROWTH-21st Project.

OBJECTIVE: To create prescriptive growth standards for five fetal brain structures, measured using ultrasound, in healthy, well-nourished women at low risk of impaired fetal growth and poor perinatal outcome, taking part in the Fetal Growth Longitudinal Study (FGLS) of the INTERGROWTH-21st Project. METHODS: This was a complementary analysis of a large, population-based, multicenter, longitudinal study. The sample analyzed was selected randomly from the overall FGLS population, ensuring an equal distribution among the eight diverse participating sites and of three-dimensional (3D) ultrasound volumes across pregnancy (range: 15-36 weeks' gestation). We measured, in planes reconstructed from 3D ultrasound volumes of the fetal head at different timepoints in pregnancy, the size of the parieto-occipital fissure (POF), Sylvian fissure (SF), anterior horn of the lateral ventricle, atrium of the posterior horn of the lateral ventricle (PV) and cisterna magna (CM). Fractional polynomials were used to construct the standards. Growth and development of the infants were assessed at 1 and 2 years of age to confirm their adequacy for constructing international standards. RESULTS: From the entire FGLS cohort of 4321 women, 451 (10.4%) were selected at random. After exclusions, 3D ultrasound volumes from 442 fetuses born without a congenital malformation were used to create the charts. The fetal brain structures of interest were identified in 90% of cases. All structures, except the PV, showed increasing size with gestational age, and the size of the POF, SF, PV and CM showed increasing variability. The 3rd , 5th , 50th , 95th and 97th smoothed centiles are presented. The 5th centiles for the POF and SF were 3.1 mm and 4.7 mm at 22 weeks' gestation and 4.6 mm and 9.9 mm at 32 weeks, respectively. The 95th centiles for the PV and CM were 8.5 mm and 7.5 mm at 22 weeks and 8.6 mm and 9.5 mm at 32 weeks, respectively. CONCLUSIONS: We have produced prescriptive size standards for fetal brain structures based on prospectively enrolled pregnancies at low risk of abnormal outcome. We recommend these as international standards for the assessment of measurements obtained using ultrasound from fetal brain structures. © 2020 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Expected-value bias in routine third-trimester growth scans.

OBJECTIVES: Operators performing fetal growth scans are usually aware of the gestational age of the pregnancy, which may lead to expected-value bias when performing biometric measurements. We aimed to evaluate the incidence of expected-value bias in routine fetal growth scans and assess its impact on standard biometric measurements. METHODS: We collected prospectively full-length video recordings of routine ultrasound growth scans coupled with operator eye tracking. Expected value was defined as the gestational age at the time of the scan, based on the estimated due date that was established at the dating scan. Expected-value bias was defined as occurring when the operator looked at the measurement box on the screen during the process of caliper adjustment before saving a measurement. We studied the three standard biometric planes on which measurements of head circumference (HC), abdominal circumference (AC) and femur length (FL) are obtained. We evaluated the incidence of expected-value bias and quantified the impact of biased measurements. RESULTS: We analyzed 272 third-trimester growth scans, performed by 16 operators, during which a total of 1409 measurements (354 HC, 703 AC and 352 FL; including repeat measurements) were obtained. Expected-value bias occurred in 91.4% of the saved standard biometric plane measurements (85.0% for HC, 92.9% for AC and 94.9% for FL). The operators were more likely to adjust the measurements towards the expected value than away from it (47.7% vs 19.7% of measurements; P < 0.001). On average, measurements were corrected by 2.3 ± 5.6, 2.4 ± 10.4 and 3.2 ± 10.4 days of gestation towards the expected gestational age for the HC, AC, and FL measurements, respectively. Additionally, we noted a statistically significant reduction in measurement variance once the operator was biased (P = 0.026). Comparing the lowest and highest possible estimated fetal weight (using the smallest and largest biased HC, AC and FL measurements), we noted that the discordance, in percentage terms, was 10.1% ± 6.5%, and that in 17% (95% CI, 12-21%) of the scans, the fetus could be considered as small-for-gestational age or appropriate-for-gestational age if using the smallest or largest possible measurements, respectively. Similarly, in 13% (95% CI, 9-16%) of scans, the fetus could be considered as large-for-gestational age or appropriate-for-gestational age if using the largest or smallest possible measurements, respectively. CONCLUSIONS: During routine third-trimester growth scans, expected-value bias frequently occurs and significantly changes standard biometric measurements obtained. © 2019 the Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

On the benefits of using multivariate analysis in mass spectrometric studies of combustion-generated aerosols.

The intricate chemistry of the carbonaceous particle surface layer (which drives their reactivity, environmental and health impacts) results in complex mass spectra. In this respect, detailed molecular-level analysis of combustion emissions may be challenging even with high-resolution mass spectrometry. Building on a recently proposed comprehensive methodology (encompassing all stages from sampling to data reduction), we propose herein a comparative analysis of soot particles produced by three different sources: a miniCAST standard generator, a laboratory diffusion flame and a single cylinder internal combustion engine. The surface composition is probed by either laser or secondary ion mass spectrometry. Two examples of multivariate analysis, Principal component analysis and hierarchical clustering analysis proved their efficiency in both identifying general trends and evidencing subtle differences that otherwise would remain unnoticed in the plethora of data generated during mass spectrometric analyses. Chemical information extracted from these multivariate statistical procedures contributes to a better understanding of fundamental combustion processes and also opens to practical applications such as the tracing of engine emissions.

Spatio-Temporal Partitioning and Description of Full-Length Routine Fetal Anomaly Ultrasound Scans.

This paper considers automatic clinical workflow description of full-length routine fetal anomaly ultrasound scans using deep learning approaches for spatio-temporal video analysis. Multiple architectures consisting of 2D and 2D + t CNN, LSTM, and convolutional LSTM are investigated and compared. The contributions of short-term and long-term temporal changes are studied, and a multi-stream framework analysis is found to achieve the best top-1 accuracy=0.77 and top-3 accuracy=0.94. Automated partitioning and characterisation on unlabelled full-length video scans show high correlation (ρ=0.95, p=0.0004) with workflow statistics of manually labelled videos, suggesting practicality of proposed methods.

Quality-improvement program for ultrasound-based fetal anatomy screening using large-scale clinical audit.

OBJECTIVE: A large-scale audit and peer review of ultrasound images may improve sonographer performance, but is rarely performed consistently as it is time-consuming and expensive. The aim of this study was to perform a large-scale audit of routine fetal anatomy scans to assess if a full clinical audit cycle can improve clinical image-acquisition standards. METHODS: A large-scale, clinical, retrospective audit was conducted of ultrasound images obtained during all routine anomaly scans performed from 18 + 0 to 22 + 6 weeks' gestation at a UK hospital during 2013 (Cycle 1), to build a baseline understanding of the performance of sonographers. Targeted actions were undertaken in response to the findings with the aim of improving departmental performance. A second full-year audit was then performed of fetal anatomy ultrasound images obtained during the following year (Cycle 2). An independent pool of experienced sonographers used an online tool to assess all scans in terms of two parameters: scan completeness (i.e. were all images archived?) and image quality using objective scoring (i.e. were images of high quality?). Both were assessed in each audit at the departmental level and at the individual sonographer level. A random sample of 10% of scans was used to assess interobserver reproducibility. RESULTS: In Cycle 1 of the audit, 103 501 ultrasound images from 6257 anomaly examinations performed by 22 sonographers were assessed; in Cycle 2, 153 557 images from 6406 scans performed by 25 sonographers were evaluated. The analysis was performed including the images obtained by the 20 sonographers who participated in both cycles. Departmental median scan completeness improved from 72% in the first year to 78% at the second assessment (P < 0.001); median image-quality score for all fetal views improved from 0.83 to 0.86 (P < 0.001). The improvement was greatest for those sonographers who performed poorest in the first audit; with regards to scan completeness, the poorest performing 15% of sonographers in Cycle 1 improved by more than 30 percentage points, and with regards to image quality, the poorest performing 11% in Cycle 1 showed a more than 10% improvement. Interobserver repeatability of scan completeness and image-quality scores across different fetal views were similar to those in the published literature. CONCLUSIONS: A clinical audit and a set of targeted actions helped improve sonographer scan-acquisition completeness and scan quality. Such adherence to recommended clinical acquisition standards may increase the likelihood of correct measurement and thereby fetal growth assessment, and should allow better detection of abnormalities. As such a large-scale audit is time consuming, further advantages would be achieved if this process could be automated. © 2018 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

The antepartum stillbirth syndrome: risk factors and pregnancy conditions identified from the INTERGROWTH-21st Project.

OBJECTIVES: To identify risk factors for antepartum stillbirth, including fetal growth restriction, among women with well-dated pregnancies and access to antenatal care. DESIGN: Population-based, prospective, observational study. SETTING: Eight international urban populations. POPULATION: Pregnant women and their babies enrolled in the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project. METHODS: Cox proportional hazard models were used to compare risks among antepartum stillborn and liveborn babies. MAIN OUTCOME MEASURES: Antepartum stillbirth was defined as any fetal death after 16 weeks' gestation before the onset of labour. RESULTS: Of 60 121 babies, 553 were stillborn (9.2 per 1000 births), of which 445 were antepartum deaths (7.4 per 1000 births). After adjustment for site, risk factors were low socio-economic status, hazard ratio (HR): 1.6 (95% CI, 1.2-2.1); single marital status, HR 2.0 (95% CI, 1.4-2.8); age ≥40 years, HR 2.2 (95% CI, 1.4-3.7); essential hypertension, HR 4.0 (95% CI, 2.7-5.9); HIV/AIDS, HR 4.3 (95% CI, 2.0-9.1); pre-eclampsia, HR 1.6 (95% CI, 1.1-3.8); multiple pregnancy, HR 3.3 (95% CI, 2.0-5.6); and antepartum haemorrhage, HR 3.3 (95% CI, 2.5-4.5). Birth weight <3rd centile was associated with antepartum stillbirth [HR, 4.6 (95% CI, 3.4-6.2)]. The greatest risk was seen in babies not suspected to have been growth restricted antenatally, with an HR of 5.0 (95% CI, 3.6-7.0). The population-attributable risk of antepartum death associated with small-for-gestational-age neonates diagnosed at birth was 11%. CONCLUSIONS: Antepartum stillbirth is a complex syndrome associated with several risk factors. Although small babies are at higher risk, current growth restriction detection strategies only modestly reduced the rate of stillbirth. TWEETABLE ABSTRACT: International stillbirth study finds individual risks poor predictors of death but combinations promising.

SonoEyeNet: Standardized Fetal Ultrasound Plane Detection Informed by Eye Tracking.

We present a novel automated approach for detection of standardized abdominal circumference (AC) planes in fetal ultrasound built in a convolutional neural network (CNN) framework, called SonoEyeNet, that utilizes eye movement data of a sonographer in automatic interpretation. Eye movement data was collected from experienced sonographers as they identified an AC plane in fetal ultrasound video clips. A visual heatmap was generated from the eye movements for each video frame. A CNN model was built using ultrasound frames and their corresponding visual heatmaps. Different methods of processing visual heatmaps and their fusion with image feature maps were investigated. We show that with the assistance of human visual fixation information, the precision, recall and F1-score of AC plane detection was increased to 96.5%, 99.0% and 97.8% respectively, compared to 73.6%, 74.1% and 73.8% without using eye fixation information.

Quality control of ultrasound for fetal biometry: results from the INTERGROWTH-21st Project.

OBJECTIVE: To assess a comprehensive package of ultrasound quality control in the Fetal Growth Longitudinal Study of the INTERGROWTH-21st Project, a large multicenter study of fetal growth. METHODS: Quality control (QC) measures were performed for 20 313 ultrasound scan images obtained prospectively from 4321 fetuses at 14-41 weeks' gestation in eight geographical locations. At the time of each ultrasound examination, three fetal biometric variables (head circumference (HC), abdominal circumference (AC) and femur length (FL)) were measured in triplicate on separately generated images. All measurements were taken in a blinded fashion. QC had two elements: (1) qualitative QC: visual assessment by sonographers at each study site of their images based on specific criteria, with 10% of images being re-assessed at the Oxford-based Ultrasound Quality Unit (compared using an adjusted kappa statistic); and (2) quantitative QC: assessment of measurement data by comparing the first, second and third measurements (intraobserver variability), remeasurement of caliper replacement in 10% (interobserver variability), both by Bland-Altman plots and plotting frequency histograms of the SD of triplicate measurements and assessing how many were above or below 2 SD of the expected distribution. The system allowed the sonographers' performances to be monitored regularly. RESULTS: A high level of agreement between self- and external scoring was demonstrated for all measurements (κ = 0.99 (95% CI, 0.98-0.99) for HC, 0.98 (95% CI, 0.97-0.99) for AC and 0.96 (95% CI, 0.95-0.98) for FL). Intraobserver 95% limits of agreement (LoA) of ultrasound measures for HC, AC and FL were ± 3.3%, ± 5.6% and ± 6.2%, respectively; the corresponding values for interobserver LoA were ± 4.4%, ± 6.0% and ± 5.6%. The SD distribution of triplicate measurements for all biometric variables showed excessive variability for three of 31 sonographers, allowing prompt identification and retraining. CONCLUSIONS: Qualitative and quantitative QC monitoring was feasible and highly reproducible in a large multicenter research study, which facilitated the production of high-quality ultrasound images. We recommend that the QC system we developed is implemented in future research studies and clinical practice. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Formation of coronene:water complexes: FTIR study in argon matrices and theoretical characterisation.

In this paper, we report a combined theoretical and experimental study of coronene:water interactions in low temperature argon matrices. The theoretical calculations were performed using the mixed density functional-based tight binding/force field approach. The results are discussed in the light of experimental matrix isolation FTIR spectroscopic data. We show that, in the solid phase, (C24H12)(H2O)n (n ≤ 6) σ-type complexes, i.e. with water molecules coordinated on the edge of coronene, are formed, whereas in the gas phase, π-interaction is preferred. These σ-complexes are characterised by small shifts in water absorption bands and a larger blue shift of the out-of-plane γ(CH) deformation of coronene, with the shift increasing with the number of complexed water molecules. Such σ interaction is expected to favour photochemical reaction between water and coronene at the edges of the coronene molecule, leading to the formation of oxidation products at low temperature, even in the presence of only a few water molecules and at radiation energies below the ionisation potential of coronene.

A framework for analysis of linear ultrasound videos to detect fetal presentation and heartbeat.

Confirmation of pregnancy viability (presence of fetal cardiac activity) and diagnosis of fetal presentation (head or buttock in the maternal pelvis) are the first essential components of ultrasound assessment in obstetrics. The former is useful in assessing the presence of an on-going pregnancy and the latter is essential for labour management. We propose an automated framework for detection of fetal presentation and heartbeat from a predefined free-hand ultrasound sweep of the maternal abdomen. Our method exploits the presence of key anatomical sonographic image patterns in carefully designed scanning protocols to develop, for the first time, an automated framework allowing novice sonographers to detect fetal breech presentation and heartbeat from an ultrasound sweep. The framework consists of a classification regime for a frame by frame categorization of each 2D slice of the video. The classification scores are then regularized through a conditional random field model, taking into account the temporal relationship between the video frames. Subsequently, if consecutive frames of the fetal heart are detected, a kernelized linear dynamical model is used to identify whether a heartbeat can be detected in the sequence. In a dataset of 323 predefined free-hand videos, covering the mother's abdomen in a straight sweep, the fetal skull, abdomen, and heart were detected with a mean classification accuracy of 83.4%. Furthermore, for the detection of the heartbeat an overall classification accuracy of 93.1% was achieved.

International estimated fetal weight standards of the INTERGROWTH-21st Project.

OBJECTIVE: Estimated fetal weight (EFW) and fetal biometry are complementary measures used to screen for fetal growth disturbances. Our aim was to provide international EFW standards to complement the INTERGROWTH-21st Fetal Growth Standards that are available for use worldwide. METHODS: Women with an accurate gestational-age assessment, who were enrolled in the prospective, international, multicenter, population-based Fetal Growth Longitudinal Study (FGLS) and INTERBIO-21st Fetal Study (FS), two components of the INTERGROWTH-21st Project, had ultrasound scans every 5 weeks from 9-14 weeks' until 40 weeks' gestation. At each visit, measurements of fetal head circumference (HC), biparietal diameter, occipitofrontal diameter, abdominal circumference (AC) and femur length (FL) were obtained blindly by dedicated research sonographers using standardized methods and identical ultrasound machines. Birth weight was measured within 12 h of delivery by dedicated research anthropometrists using standardized methods and identical electronic scales. Live babies without any congenital abnormality, who were born within 14 days of the last ultrasound scan, were selected for inclusion. As most births occurred at around 40 weeks' gestation, we constructed a bootstrap model selection and estimation procedure based on resampling of the complete dataset under an approximately uniform distribution of birth weight, thus enriching the sample size at extremes of fetal sizes, to achieve consistent estimates across the full range of fetal weight. We constructed reference centiles using second-degree fractional polynomial models. RESULTS: Of the overall population, 2404 babies were born within 14 days of the last ultrasound scan. Mean time between the last scan and birth was 7.7 (range, 0-14) days and was uniformly distributed. Birth weight was best estimated as a function of AC and HC (without FL) as log(EFW) = 5.084820 - 54.06633 × (AC/100)3 - 95.80076 × (AC/100)3 × log(AC/100) + 3.136370 × (HC/100), where EFW is in g and AC and HC are in cm. All other measures, gestational age, symphysis-fundus height, amniotic fluid indices and interactions between biometric measures and gestational age, were not retained in the selection process because they did not improve the prediction of EFW. Applying the formula to FGLS biometric data (n = 4231) enabled gestational age-specific EFW tables to be constructed. At term, the EFW centiles matched those of the INTERGROWTH-21st Newborn Size Standards but, at < 37 weeks' gestation, the EFW centiles were, as expected, higher than those of babies born preterm. Comparing EFW cross-sectional values with the INTERGROWTH-21st Preterm Postnatal Growth Standards confirmed that preterm postnatal growth is a different biological process from intrauterine growth. CONCLUSIONS: We provide an assessment of EFW, as an adjunct to routine ultrasound biometry, from 22 to 40 weeks' gestation. However, we strongly encourage clinicians to evaluate fetal growth using separate biometric measures such as HC and AC, as well as EFW, to avoid the minimalist approach of focusing on a single value. © 2016 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Ultrasound-based gestational-age estimation in late pregnancy.

OBJECTIVE: Accurate gestational-age (GA) estimation, preferably by ultrasound measurement of fetal crown-rump length before 14 weeks' gestation, is an important component of high-quality antenatal care. The objective of this study was to determine how GA can best be estimated by fetal ultrasound for women who present for the first time late in pregnancy with uncertain or unknown menstrual dates. METHODS: INTERGROWTH-21st was a large, prospective, multicenter, population-based project performed in eight geographically defined urban populations. One of its principal components, the Fetal Growth Longitudinal Study, aimed to develop international fetal growth standards. Each participant had their certain menstrual dates confirmed by first-trimester ultrasound examination. Fetal head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), abdominal circumference (AC) and femur length (FL) were measured every 5 weeks from 14 weeks' gestation until delivery. For each participant, a single, randomly selected ultrasound examination was used to explore all candidate biometric variables and permutations to build models to predict GA. Regression equations were ranked based upon minimization of the mean prediction error, goodness of fit and model complexity. An automated machine learning algorithm, the Genetic Algorithm, was adapted to evaluate > 64 000 potential polynomial equations as predictors. RESULTS: Of the 4607 eligible women, 4321 (94%) had a pregnancy without major complications and delivered a live singleton without congenital malformations. After other exclusions (missing measurements in GA window and outliers), the final sample comprised 4229 women. Two skeletal measures, HC and FL, produced the best GA prediction, given by the equation loge (GA) = 0.03243 × (loge (HC))2 + 0.001644 × FL × loge (HC) + 3.813. When FL was not available, the best equation based on HC alone was loge (GA) = 0.05970 × (loge (HC))2 + 0.000000006409 × (HC)3 + 3.3258. The estimated uncertainty of GA prediction (half width 95% interval) was 6-7 days at 14 weeks' gestation, 12-14 days at 26 weeks' gestation and > 14 days in the third trimester. The addition of FL to the HC model led to improved prediction intervals compared with using HC alone, but no further improvement in prediction was afforded by adding AC, BPD or OFD. Equations that included other measurements (BPD, OFD and AC) did not perform better. CONCLUSIONS: Among women initiating antenatal care late in pregnancy, a single set of ultrasound measurements combining HC and FL in the second trimester can be used to estimate GA with reasonable accuracy. We recommend this tool for underserved populations but considerable efforts should be implemented to improve early initiation of antenatal care worldwide. © 2016 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

KIR haplotypes are associated with late-onset type 1 diabetes in European-American families.

Classical human leukocyte antigens (HLA) genes confer the strongest, but not the only, genetic susceptibility to type 1 diabetes. Killer cell immunoglobulin-like receptors (KIR), on natural killer (NK) cells, bind ligands including class I HLA. We examined presence or absence, with copy number, of KIR loci in 1698 individuals, from 339 multiplex type 1 diabetes families, from the Human Biological Data Interchange, previously genotyped for HLA. Combining family data with KIR copy number information allowed assignment of haplotypes using identity by descent. This is the first disease study to use KIR copy number typing and unambiguously define haplotypes by gene transmission. KIR A1 haplotypes were positively associated with T1D in the subset of patients without the high T1D risk HLA genotype, DR3/DR4 (odds ratio=1.29, P=0.0096). The data point to a role for KIR in type 1 diabetes risk in late-onset patients. In the top quartile (age of onset>14), KIR A2 haplotype was overtransmitted (63.4%, odds ratio=1.73, P=0.024) and KIR B haplotypes were undertransmitted (41.1%, odds ratio=0.70, P=0.0052) to patients. The data suggest that inhibitory 'A' haplotypes are predisposing and stimulatory 'B' haplotypes confer protection in both DR3/DR4-negative and late-onset patient groups.

Diffusion of molecules in the bulk of a low density amorphous ice from molecular dynamics simulations.

The diffusion of molecules in interstellar ice is a fundamental phenomenon to take into account while studying the formation of complex molecules in this ice. This work presents a theoretical study on the diffusion of H2O, NH3, CO2, CO, and H2CO in the bulk of a low density amorphous (LDA) ice, while taking into account the physical conditions prevailing in space, i.e. temperatures below 150 K and extremely low pressure. This study was undertaken by means of molecular dynamics simulations. For CO2 for which no experimental data were available we conducted our own experiments. From our calculations we show that, at low temperatures, the diffusion of molecules in the bulk of a LDA ice is driven by the self-diffusion of water molecules in the ice. With this study we demonstrate that molecular dynamics allows the calculation of diffusion coefficients for small molecules in LDA ice that are convincingly comparable to experimentally measured diffusion coefficients. We also provide diffusion coefficients for a series of molecules of astrochemical interest.

Infrared photoisomerization of 1-propanol CD3 and OD trapped in four cryogenic matrices: Ne, N2, Ar, and Xe.

The conformational equilibria and isomerization processes of 1-propanol -OD and -CD3 have been studied by vibrational spectroscopy at low temperatures in four cryogenic matrices to investigate the effect of deuteration on their photochemistry. These isotopic species were selectively irradiated in the νOH and νOD domains, resulting in the identification of several conformers that are able to interconvert upon selective IR irradiation. The experimental results were compared with theoretical geometries obtained at the B3LYP/6-311+G(d) level of theory. Alkyl chain isomerization can be induced in rare gas and nitrogen cryogenic matrices by suitable selective irradiation. Selective excitation of the OH and OD stretches of two Gauche isomers transfers the alkyl chain from the gauche to the trans form. The competition between intramolecular vibrational energy relaxation and the matrix-dopant interaction determines the torsional subspace dynamics of the vibrationally excited propanol molecules.