Evaluation of the effect of SARS-COV-2 infection on Doppler ultrasound and placental findings of pregnant women: a systematic review and meta-analysis.

PURPOSE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect the human placenta and has been shown to have an adverse effect on Doppler ultrasound parameters and placental features. However, the specific effects of the SAS-CoV-2 infection on the fetal-placental unit in pregnant women remain unclear. The aim of this systematic review and meta-analysis was to evaluate the impact of SARS-CoV-2 infection on Doppler ultrasound and placental findings in pregnant women. METHODS: A systematic search was conducted using four electronic databases (PubMed, Embase, Scopus, and Cochrane Library) to select publications published in peer-reviewed journals written in English. Odds ratios (ORs) were calculated, along with their 95% confidence intervals (CIs). Heterogeneity was assessed using Cochrane Q and I² statistics and the appropriate P-value. The analysis used RevMan 5.3. RESULTS: This meta-analysis included 1,210 pregnant women from 10 case-control studies. SARS-CoV-2-infected pregnant women exhibited higher likelihoods of placental abnormalities (OR, 2.62; 95% CI, 1.66 to 4.13), aberrant Doppler values (OR, 1.95; 95% CI, 1.16 to 3.27), an abnormal cerebroplacental ratio (OR, 2.68; 95% CI, 1.52 to 4.75), altered fetoplacental circulation (OR, 1.56; 95% CI, 1.07 to 2.28), and increased placental thickness and placental venous lakes (OR, 1.85; 95% CI, 1.25 to 2.72). CONCLUSION: According to this meta-analysis, pregnant women infected with SARS-CoV-2 are more likely to experience altered Doppler ultrasonography parameters and placental abnormalities, including increased placental thickness, placental venous lakes, altered fetoplacental circulation, and cerebroplacental ratio. However, the limited number of case-control studies requires larger sample sizes to validate and enhance the evidence.

Assessment of fetal development during mid and late term pregnancies by standard B-Mode ultrasonography in Shetland ponies.

Transrectal and transabdominal ultrasonography is an established method to monitor pregnancy, fetal growth and wellbeing in different species. Growth charts with multiple bio-morphometric parameters to estimate days of gestation and days before parturition exist in small companion animals, sheep and goats, riding type horses and large ponies but not in small horse breeds like Shetland ponies. The aim of this study was to apply fetal biometric assessment and detailed description of physiologic fetal development to mid and late term pregnancies in Shetland mares and to generate reference data for clinical practice and for future research. Fetal parameters were collected starting on day 101 of pregnancy in five Shetland mares. The fetal biometric parameters determined consisted of aortic diameter, eye diameter, combined rib and intercostal distance (CRID), stomach length and width and different heart morphology parameters in sagittal and frontal plane. Additionally, fetal activity and organ development in terms of differentiation and changes in echogenicity were recorded. Considering reliably assessable parameters, fetal CRID was the best predictor for gestational age with ± 13.6 days and fetal aortic diameter the most accurate for prediction of days until parturition with ± 16.2 days.

Unisex and Sex-Specific Prescriptive Fetal Growth Charts for Improved Detection of Small-for-Gestational-Age Babies in a Low-Risk Population: A post hoc Analysis of a Cluster-Randomized Study.

INTRODUCTION: Our aim was to develop and evaluate the performance of population-based sex-specific and unisex prescriptive fetal abdominal circumference growth charts in predicting small-for-gestational-age (SGA) birthweight, severe SGA (sSGA) birthweight, and severe adverse perinatal outcomes (SAPO) in a low-risk population. METHODS: This is a post hoc analysis of the Dutch nationwide cluster-randomized IRIS study, encompassing ultrasound data of 7,704 low-risk women. IRIS prescriptive unisex and IRIS sex-specific abdominal circumference (AC) fetal growth charts were derived using quantile regression. As a comparison, we used the descriptive unisex Verburg chart, which is commonly applied in the Netherlands. Diagnostic parameters were calculated based on the 34-36 weeks' ultrasound. RESULTS: Sensitivity rates for predicting SGA and sSGA birthweights were more than twofold higher based on the IRIS prescriptive sex-specific (respectively SGA 43%; sSGA 59%) and unisex (SGA 39%; sSGA 55%) charts, compared to the Verburg chart (SGA 16%; sSGA 23% both p < 0.01). Specificity rates were highest for Verburg (SGA 99%; sSGA 98%) and lowest for IRIS sex-specific (SGA 94%; sSGA 92%). Results for predicting SGA with SAPO were similar for the prescriptive charts (44%), and again higher than the Verburg chart (20%). The IRIS sex-specific chart identified significantly more males as SGA and sSGA (respectively, 42%; 60%, p < 0.001) than the IRIS unisex chart (respectively, 35%; 53% p < 0.01). CONCLUSION: Our study demonstrates improved performance of both the IRIS sex-specific and unisex prescriptive fetal growth compared to the Verburg descriptive chart, doubling detection rates of SGA, sSGA, and SGA with SAPO. Additionally, the sex-specific chart outperformed the unisex chart in detecting SGA and sSGA. Our findings suggest the potential benefits of using prescriptive AC fetal growth charts in low-risk populations and emphasize the importance of considering customizing fetal growth charts for sex. Nevertheless, the increased sensitivity of these charts should be weighed against the decrease in specificity.

Fetal size monitoring in women with gestational diabetes and normal glucose tolerance.

AIMS: To monitor fetal size and identify predictors for birthweight in women with gestational diabetes (GDM) and normal glucose tolerance (NGT). METHODS: Cohort study of 1843 women universally screened for GDM, with routine ultrasounds each trimester. Women with GDM and NGT were categorized in subgroups by birthweight centile. RESULTS: Of the total cohort, 231 (12.5%) women were diagnosed with GDM. Fetal size, incidence of large-for-gestational age (LGA: 12.3% of GDM vs. 12.9% of NGT, p = 0.822) and small-for-gestational age (SGA) neonates (4.8% of GDM vs. 5.1% of NGT, p = 0.886) were similar between GDM and NGT. GDM women with LGA neonates were more insulin resistant at baseline and had more often estimated fetal weight (EFW) ≥ P90 on the 28-33 weeks ultrasound (p = 0.033) than those with AGA (appropriate-for-gestational age) neonates. Compared to NGT women with AGA neonates, those with LGA neonates were more often obese and multiparous, had higher fasting glycemia, a worse lipid profile, and higher insulin resistance between 24 -28 weeks, with more often excessive gestational weight gain. On the 28-33 weeks ultrasound, abdominal circumference ≥ P95 had a high positive predictive value for LGA neonates in GDM (100%), whereas, in both GDM and NGT, EFW ≥ P90 and ≤ P10 had a high negative predictive value for LGA and SGA neonates (> 88%), respectively. CONCLUSIONS: There were no differences in fetal size throughout pregnancy nor in LGA incidence between GDM and NGT women. EFW centile at 28-33 weeks correlated well with birthweight. This indicates that GDM treatment is effective and targeted ultrasound follow-up is useful. TRIAL REGISTRATION CLINICALTRIALS.GOV: NCT02036619. Registration date: January 15, 2014. https://clinicaltrials.gov/ct2/show/NCT02036619 .

Next-generation monitoring in obstetrics: Assessing the accuracy of non-piezo portable ultrasound technology.

INTRODUCTION: The emergence of handheld ultrasound devices capable of connecting to cell phones or tablets heralds a significant advancement in medical technology, particularly within the field of obstetrics. These devices offer the promise of immediate bedside ultrasound examinations, potentially revolutionizing patient care by enabling fetal assessments in diverse settings. MATERIAL AND METHODS: This prospective study aimed to validate the reliability of non-piezo, chip-based handheld ultrasound devices in clinical obstetric practice. Conducted in a university hospital obstetric ward, the study included 100 pregnant women between 17 and 41 weeks of gestation. Participants underwent ultrasound examinations using both conventional and portable point-of-care ultrasound (POCUS) devices to compare the accuracy in estimating fetal weight and other parameters, such as cardiac activity, fetal presentation, placental location, and amniotic fluid volume. The reliability and agreement between the devices were assessed using intraclass correlation coefficients, Bland-Altman plots, and Pearson correlation coefficients. RESULTS: The results show a near-perfect agreement (0.98) and correlation (r = 0.98, p < 0.001) for estimated fetal weight and most biometry measurements between the two types of ultrasound devices, with slight deviations in head circumference and amniotic fluid index measurements. Subgroup analysis revealed variations in agreement and correlation rates with higher BMI and advanced gestational age, indicating areas for further refinement. CONCLUSIONS: These findings affirm the high reliability of handheld ultrasound devices for basic obstetric ultrasound evaluations, supporting their integration into daily clinical practice. This technology improves the flexibility and immediacy of prenatal care, although further research is needed to optimize its application across patient populations and treatment settings.

RTSeg-net: A lightweight network for real-time segmentation of fetal head and pubic symphysis from intrapartum ultrasound images.

The segmentation of the fetal head (FH) and pubic symphysis (PS) from intrapartum ultrasound images plays a pivotal role in monitoring labor progression and informing crucial clinical decisions. Achieving real-time segmentation with high accuracy on systems with limited hardware capabilities presents significant challenges. To address these challenges, we propose the real-time segmentation network (RTSeg-Net), a groundbreaking lightweight deep learning model that incorporates innovative distribution shifting convolutional blocks, tokenized multilayer perceptron blocks, and efficient feature fusion blocks. Designed for optimal computational efficiency, RTSeg-Net minimizes resource demand while significantly enhancing segmentation performance. Our comprehensive evaluation on two distinct intrapartum ultrasound image datasets reveals that RTSeg-Net achieves segmentation accuracy on par with more complex state-of-the-art networks, utilizing merely 1.86 M parameters-just 6 % of their hyperparameters-and operating seven times faster, achieving a remarkable rate of 31.13 frames per second on a Jetson Nano, a device known for its limited computing capacity. These achievements underscore RTSeg-Net's potential to provide accurate, real-time segmentation on low-power devices, broadening the scope for its application across various stages of labor. By facilitating real-time, accurate ultrasound image analysis on portable, low-cost devices, RTSeg-Net promises to revolutionize intrapartum monitoring, making sophisticated diagnostic tools accessible to a wider range of healthcare settings.

Fetal Biometric Parameter Reference Charts of a Central Anatolian Turkish Population.

PURPOSE: The assessment of fetal biometry using ultrasound provides accurate pregnancy dating and also screening of fetal growth. Fetal biometry, which is common practice in the second and third trimesters of pregnancy, is fetal morphometry, which involves taking measurements of the different anatomical body parts. These fetal dimensions vary on ethnicity. The aim of this study is to demonstrate fetal biometric parameters measurement results of the Central Anatolia Turkish population with detailed percentile tables and graphs to screen fetal growth more accurately. METHODS: This cross-sectional study was performed on a total of 1132 fetuses (47% girl, and 53% boy) between 15 and 40 weeks of gestation. Biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) measurements are performed in a standardized manner every gestational week. BPD and HC were measured at the level of the thalami on the horizontal plane of the fetal head. HC was measured using the ellipse method. AC measurement was taken at the circular cross-section of the upper fetal abdomen. FL was measured along with the ossified diaphysis of the femur. All measurements were taken in millimeters. RESULTS: Pregnant women's mean age was 27.58 (17-43), and the mean body mass index was 27.68 (15.06-50.78) as demographic data. 38.13% of women had their first, 29.74% had their second, and 32.13% had three or more gestations within our study. Percentile data of fetuses for each parameter (BPD, HC, AC, and FL) and for each week were shown as tables and percentile graphics. Fetal 50th percentile measurements were compared between our study and other studies from different countries. The Kruskal-Wallis test results showed that BPD (p = 0.827), HC (p = 0.808), AC (p = 0.846), and FL (p = 0.725) values have a statistically similar mean in all studies. Hierarchical cluster analysis results showed that our results for BPD, HC, AC, and FL percentile curves have been found closer to Italian population results. However, our results were statistically different from Asian, Nigerian, non-Hispanic American, and Brazilian populations for each of the different parameters. CONCLUSION: The specialization of fetal biometric charts for a particular population can ensure a more accurate assessment of fetal growth rate. We showed fetal biometric percentile tables and graphics of the Central Anatolian Turkish population in this study. These results may provide a valuable contribution to obstetrical practice. Further studies can be conducted in different regions of Turkiye, thus comparisons could be possible over the country.

Fetal Gestational Age Estimation Using Ultrasonic Transverse Cerebellar Diameter in a Sub-Saharan African Population.

Background: To explore the relationship between fetal Transverse Cerebellar Diameter (TCD) and menstrual gestational age (GA) and to generate normative references (nomogram) of the fetal TCD in some pregnant women in Southwest Nigeria. Methods: Four hundred pregnant women with a singleton fetus between 14 and 38 weeks GA were enrolled. The TCD and other biometric parameters (biparietal diameter, head circumference, abdominal circumference, and femur length) as well as the cerebellar appearance were analyzed and correlated with the GA. Results: The mean TCD increased from 13.3 ± 0.3 mm at 14 weeks to 52.3 ± 3.3 mm at 38 weeks of pregnancy. A strong positive correlation was observed between TCD and GA, which was best represented by a linear regression equation: Predicted GA = 0.557 × TCD + 8.840. The regression analysis indicated a statistically significant strong positive relationship between TCD and GA (r = 0.972 and P < 0.001). The cerebellar appearance based on shape and echogenicity was graded into Grade I: 230 fetuses (57.5%); Grade II: 74 fetuses (18.5%) and Grade III: 96 fetuses (24.0%). Median GA and TCD were 21 weeks and 21.2 mm for Grade I; 29 weeks and 35.5 mm for Grade II; and 35 weeks and 48.1 mm for Grade III, respectively. Conclusion: The TCD increased in a linear fashion with advancing GA in the evaluated fetuses. The TCD is, therefore, a good marker for GA estimation. There is a gradual ultrasonographic change in fetal cerebellar appearance with advancing gestation.

Automating the Human Action of First-Trimester Biometry Measurement from Real-World Freehand Ultrasound.

OBJECTIVE: Automated medical image analysis solutions should closely mimic complete human actions to be useful in clinical practice. However, more often an automated image analysis solution represents only part of a human task, which restricts its practical utility. In the case of ultrasound-based fetal biometry, an automated solution should ideally recognize key fetal structures in freehand video guidance, select a standard plane from a video stream and perform biometry. A complete automated solution should automate all three subactions. METHODS: In this article, we consider how to automate the complete human action of first-trimester biometry measurement from real-world freehand ultrasound. In the proposed hybrid convolutional neural network (CNN) architecture design, a classification regression-based guidance model detects and tracks fetal anatomical structures (using visual cues) in the ultrasound video. Several high-quality standard planes that contain the mid-sagittal view of the fetus are sampled at multiple time stamps (using a custom-designed confident-frame detector) based on the estimated probability values associated with predicted anatomical structures that define the biometry plane. Automated semantic segmentation is performed on the selected frames to extract fetal anatomical landmarks. A crown-rump length (CRL) estimate is calculated as the mean CRL from these multiple frames. RESULTS: Our fully automated method has a high correlation with clinical expert CRL measurement (Pearson's p = 0.92, R-squared [R2] = 0.84) and a low mean absolute error of 0.834 (weeks) for fetal age estimation on a test data set of 42 videos. CONCLUSION: A novel algorithm for standard plane detection employs a quality detection mechanism defined by clinical standards, ensuring precise biometric measurements.

Evaluation of fetal kidney length as a marker for fetal biometry.

BACKGROUND: The precise determination of gestational age is essential for effectively managing and prognosis of all pregnancies. Through careful biometry, timely interventions can be implemented, leading to positive outcomes for both the mother and fetus. In routine fetal biometry, parameters such as biparietal diameter (BPD), femur length (FL), head circumference (HC), and abdominal circumference (AC) have been traditionally used. This study aims to evaluate the usefulness of fetal kidney length (FKL) as a marker for fetal biometry. METHODOLOGY: This prospective, observational, and cross-sectional study was conducted in the Radiodiagnosis and Obstetrics and Gynaecology departments, including a diverse group of pregnant women from various socio-economic backgrounds, with adherence to ethical standards. Women with singleton pregnancies between 22 and 40 weeks of gestation who met the inclusion and exclusion criteria were examined through ultrasound. The data collected were subsequently analyzed. RESULT: In the current study, 280 participants with an average age of 26.71 ± 3.6 years were included. The agreement between the mean fetal kidney length and standard biometry parameters was almost perfect, with a strength of agreement exceeding 0.99. A strong and statistically significant positive correlation existed between fetal kidney length and the estimated gestational period calculated using DLMP/standard biometric measurements. CONCLUSION: Fetal kidney length is a reliable indicator of gestational age and can supplement standard biometric measurements to provide a more precise estimation of gestational age, especially in the later stages when obtaining such standard measurements may be challenging.

Subsequent pregnancy in women who have undergone bilateral uterine artery ligation during cesarean section: A case series.

Bilateral uterine artery ligation (BUAL) serves as an effective surgical devascularization procedure in obstetric emergencies. However, concerns regarding the impact of uterine devascularization have evoked dispute. Here, the fetal growth index and obstetrical outcomes during the subsequent pregnancy of women who had undergone BUAL during cesarean section are reported. The case series of women who underwent BUAL during cesarean section and had another delivery later at the Xiamen Women and Children's Hospital between 2011 and 2020 is described. Pregnancies that did not continue beyond 20 weeks of gestation were excluded. Cases were identified from neonatal and obstetric databases and the clinical data of all cases were extracted. A total of 12 cases were identified retrospectively. Fetal biometric parameters of subsequent pregnancies in all cases including biparietal diameter, head circumference, abdominal circumference, and femur length are presented graphically across the different gestational ages and were all within the range of the 3rd-97th percentile. No maternal or neonatal morbidity was observed. BUAL did not appear to compromise a woman's subsequent obstetric outcomes. As a safe and simple surgical technique, it is safe to recommend BUAL in clinical practice.

Use of focus point for plane acquisition to improve reproducibility in fetal biometry.

OBJECTIVE: To assess the reproducibility of ultrasound measurements of fetal biometry using a 'focus point' to assist the acquisition of the relevant plane. METHODS: This was a study of 80 women with a singleton non-anomalous pregnancy who attended University College London Hospital, London, UK, between 18 and 37 weeks' gestation. Planes to measure head circumference (HC), abdominal circumference (AC) and femur length (FL) were obtained four times by two different sonographers with different levels of experience, who were blinded to one another; the first set of images was obtained with reference to a standard image, and the second set of images was obtained using the focus point technique. The focus point was defined as a unique fetal anatomical landmark in each plane (cavum septi pellucidi for HC, two-thirds of the umbilical vein for AC and one of the two extremities of the diaphysis for FL). Once identified, the focus point was maintained in view while the sonographer rotated the probe along three axes (x, y, z) to acquire the relevant plane. Sonographers were either in training or had > 3000 scans worth of experience. Intra- and interobserver reproducibility were assessed using Bland-Altman plots, and absolute values and percentages for mean difference and 95% limits of agreement (LoA) were reported. RESULTS: Overall reproducibility was good, with all 95% LoA < 8%. Reproducibility was improved by use of the focus point compared with the standard technique for both intraobserver comparison (95% LoA, < 4% vs < 6%) and interobserver comparison (95% LoA, < 7% vs < 8%). These findings were independent of sonographer seniority and plane acquired. CONCLUSIONS: Reproducibility of fetal biometry assessment is improved with use of the focus point for plane acquisition, regardless of sonographer experience. We propose that this method should be implemented in clinical practice and training programs in fetal biometry. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Accuracy of portable ultrasound for obstetric biometry.

OBJECTIVE: We assessed the accuracy of two portable ultrasound machines (PUM) in obtaining fetal biometry and estimating gestational age. METHODS: We analyzed data from the Fetal Age Machine Learning Initiative, an observational study of pregnant women in the United States and Zambia. Each participant underwent assessment by an experienced sonographer using both a high-specification ultrasound machine (HSUM) and a PUM (either Butterfly iQ or Clarius C3) to measure fetal biometry and calculate estimated gestational age (EGA) at each visit. Through comparison of paired PUM-HSUM scans, we estimated agreement between individual biometry measurements and aggregate gestational age estimates by reporting mean difference, along with intraclass correlation coefficient (ICC) and Bland-Altman plots, adjusting for trend. RESULTS: 881 participants contributed 1386 paired PUM-HSUM ultrasound studies between April and December 2021. PUM studies included 991 Butterfly and 395 Clarius. Gestational age at scan ranged from 7 to 38 weeks. Compared to HSUM, the Butterfly PUM had a mean difference of -0.20 days (95%CI±0.40) in the 1st trimester and -0.68 days (95%CI±0.68) in the 2nd/3rd trimesters. Also compared to HSUM, the Clarius PUM had a mean difference of 0.47 days (95%CI±0.64) in the 1st trimester and -1.67 days (95%CI±0.43) in the 2nd/3rd trimesters. ICCs were 0.989 or greater throughout. Increasing gestational age was associated with increasing error and absolute error. Both PUM devices demonstrated a modest trend toward underestimation of EGA at advancing gestational ages in 2nd/3rd trimester scans, compared to HSUM. CONCLUSION: Both the Butterfly iQ and Clarius C3 PUM devices were highly accurate in performing fetal biometry in a diverse population from the US and Zambia. This article is protected by copyright. All rights reserved.

Deep learning for estimation of fetal weight throughout the pregnancy from fetal abdominal ultrasound.

BACKGROUND: Fetal weight is currently estimated from fetal biometry parameters using heuristic mathematical formulas. Fetal biometry requires measurements of the fetal head, abdomen, and femur. However, this examination is prone to inter- and intraobserver variability because of factors, such as the experience of the operator, image quality, maternal characteristics, or fetal movements. Our study tested the hypothesis that a deep learning method can estimate fetal weight based on a video scan of the fetal abdomen and gestational age with similar performance to the full biometry-based estimations provided by clinical experts. OBJECTIVE: This study aimed to develop and test a deep learning method to automatically estimate fetal weight from fetal abdominal ultrasound video scans. STUDY DESIGN: A dataset of 900 routine fetal ultrasound examinations was used. Among those examinations, 800 retrospective ultrasound video scans of the fetal abdomen from 700 pregnant women between 15 6/7 and 41 0/7 weeks of gestation were used to train the deep learning model. After the training phase, the model was evaluated on an external prospectively acquired test set of 100 scans from 100 pregnant women between 16 2/7 and 38 0/7 weeks of gestation. The deep learning model was trained to directly estimate fetal weight from ultrasound video scans of the fetal abdomen. The deep learning estimations were compared with manual measurements on the test set made by 6 human readers with varying levels of expertise. Human readers used standard 3 measurements made on the standard planes of the head, abdomen, and femur and heuristic formula to estimate fetal weight. The Bland-Altman analysis, mean absolute percentage error, and intraclass correlation coefficient were used to evaluate the performance and robustness of the deep learning method and were compared with human readers. RESULTS: Bland-Altman analysis did not show systematic deviations between readers and deep learning. The mean and standard deviation of the mean absolute percentage error between 6 human readers and the deep learning approach was 3.75%±2.00%. Excluding junior readers (residents), the mean absolute percentage error between 4 experts and the deep learning approach was 2.59%±1.11%. The intraclass correlation coefficients reflected excellent reliability and varied between 0.9761 and 0.9865. CONCLUSION: This study reports the use of deep learning to estimate fetal weight using only ultrasound video of the fetal abdomen from fetal biometry scans. Our experiments demonstrated similar performance of human measurements and deep learning on prospectively acquired test data. Deep learning is a promising approach to directly estimate fetal weight using ultrasound video scans of the fetal abdomen.

An analytical cross-sectional study: determining gestational age using fetal clavicle length during the second trimester.

PURPOSE: To investigate the correlation between fetal clavicle length and gestational age in pregnant patients from 14 and 27 weeks of gestation. METHODS: This was a retrospective cross-sectional study of patients from 14 and 27 weeks of gestation. Ultrasonographic measurements such as abdominal circumference (AC), femur length (FL), humerus length (HL), clavicle length (CL), head circumference (HC), biparietal diameter (BPD), estimated fetal weight (EFW), and transverse cerebellum diameter (TCD) were made and compared. RESULTS: A total of 552 patients were evaluated in our clinic and CL was measured properly and successfully in all fetuses. Fetal AC, FL, HL, CL, BPD, HC, EFW and TCD measurements were significantly and strongly correlated with gestational week, and Pearson's correlation values were 0.964, 0.965, 0.959, 0.965, 0.951, 0.917, 0.925, and 0.954, respectively (p < 0.001). In the regression analysis equation, gestational week = 0.894 + CL × 0.961. CONCLUSION: There was a significant positive correlation between fetal CL (mm) and gestational week. We suggest that the 1 mm = 1 week rule can be used for patients with anomalies of the cerebellum and vermis, as well as for patients with unknown last menstrual period.

Automatic Deep Learning-Based Pipeline for Automatic Delineation and Measurement of Fetal Brain Structures in Routine Mid-Trimester Ultrasound Images.

INTRODUCTION: The aim of this study was to develop a pipeline using state-of-the-art deep learning methods to automatically delineate and measure several of the most important brain structures in fetal brain ultrasound (US) images. METHODS: The dataset was composed of 5,331 images of the fetal brain acquired during the routine mid-trimester US scan. Our proposed pipeline automatically performs the following three steps: brain plane classification (transventricular, transthalamic, or transcerebellar plane); brain structures delineation (9 different structures); and automatic measurement (from the structure delineations). The methods were trained on a subset of 4,331 images and each step was evaluated on the remaining 1,000 images. RESULTS: Plane classification reached 98.6% average class accuracy. Brain structure delineation obtained an average pixel accuracy higher than 96% and a Jaccard index higher than 70%. Automatic measurements get an absolute error below 3.5% for the four standard head biometries (head circumference, biparietal diameter, occipitofrontal diameter, and cephalic index), 9% for transcerebellar diameter, 12% for cavum septi pellucidi ratio, and 26% for Sylvian fissure operculization degree. CONCLUSIONS: The proposed pipeline shows the potential of deep learning methods to delineate fetal head and brain structures and obtain automatic measures of each anatomical standard plane acquired during routine fetal US examination.

Capacidad del diámetro biparietal para predecir los recién nacidos grandes para edad gestacional. Estudio de cohorte retrospectivo / Ability of biparietal diameter to predict large for gestational age newborns. A retrospective cohort study

Fundamento: Predecir el recién nacido grande para la edad gestacional es una acción de salud que necesita de herramientas tecnológicas de probada eficiencia. Objetivo: Determinar la capacidad predictiva del diámetro biparietal en los recién nacidos grandes para la edad gestacional. Metodología: Estudio de cohorte retrospectivo que incluyó 1959 gestantes cubanas con embarazo simple con captación y término del embarazo entre enero del 2009 y diciembre de 2017. En cada trimestre de gestación se compararon las condiciones tróficas adecuado para la edad gestacional (AEG) y grandes para la edad gestacional (GEG) mediante estadígrafos de tendencia central (media) y de dispersión (rango, desviación estándar) correspondientes al diámetro biparietal. Se calculó además el intervalo de confianza (IC) de 95 % para la diferencia de medias del diámetro biparietal. Asimismo, se realizó un análisis de curvas ROC para determinar si el diámetro biparietal y el peso fetal predicen la condición trófica grande para la edad gestacional en el segundo y tercer trimestre de gestación. Los datos fueron recogidos del libro registro de genética del área de salud. Resultados: El diámetro biparietal en el segundo y tercer trimestre de gestación tuvo un área bajo curva de 0.60 (IC 95 %: 0.54-0.65) y 0.59 (IC 95 %: 0.54-0.64) respectivamente. Los puntos de corte establecidos (T2: 56.55 mm, T3: 81.55 mm) tienen una especificidad y exactitud superior al 78 %. Conclusiones: El diámetro biparietal y los modelos de regresión de Shepard y de Hadlock V mostraron capacidad para discriminar el nacimiento grande para la edad gestacional del adecuado para la edad gestacional, a partir del segundo trimestre de gestación siendo más eficaces en el tercero.

Background: Predicting large for gestational age newborns is a medical action that requires technological tools with proven efficiency. Objective: To determine the predictive ability of biparietal diameter in large newborns for gestational age. Methodology: Retrospective cohort study that included 1959 Cuban pregnant women with a singleton pregnancy, with recruitment and pregnancy term between January 2009 and December 2017. In each gestational trimester, trophic conditions appropriate for gestational age (GAW) were compared and large for gestational age (GA) using central tendency (mean) and dispersion (range, standard deviation) statistics corresponding to the biparietal diameter. The 95% confidence interval (CI) for mean biparietal diameter difference was also calculated. In addition, an analysis of ROC curves was performed to determine if biparietal diameter and fetal weight predict large trophic condition for gestational age in the second and third gestational trimester. Data were gathered from the health area genetics registry book. Results: Biparietal diameter in the second and third trimester of gestation had an area under curve of 0.60 (95% CI: 0.54-0.65) and 0.59 (95% CI: 0.54-0.64) respectively. The established cut-off points (T2: 56.55 mm, T3: 81.55 mm) have a specificity and accuracy greater than 78%. Conclusions: Biparietal diameter and the Shepard and Hadlock V regression models showed ability to discriminate large for gestational age birth from adequate for gestational age birth from the second trimester of gestation onward, being more effective in the third trimester.

Relación entre biometría fetal, producto de acumulación de los lípidos y condición trófica al nacer / Relationship between fetal biometry, lipid accumulation product and the trophic condition at birth

Fundamento: Las alteraciones del estado nutricional materno generalmente se relacionan con desviaciones del crecimiento fetal, que pueden detectarse por los parámetros biofísicos fetales e identifican la posible condición trófica al nacer. Objetivo: Determinar la posible relación entre los parámetros biométricos fetales, la condición trófica al nacer y el producto de acumulación de los lípidos. Metodología: Se realizó un estudio transversal en el Policlínico Chiqui Gómez Lubian del municipio Santa Clara, durante el año 2019, en una población de 253 gestantes normopeso supuestamente sanas al inicio de la gestación. La muestra no probabilística fue de 144 gestantes. Las variables de estudio fueron: producto de acumulación de los lípidos, biometría fetal y condición trófica al nacer. Se utilizaron métodos teóricos, empíricos y estadísticos. Resultados: En el segundo trimestre ningún parámetro biométrico coincidió con la condición al nacer de pequeño, mientras que para el grande coincidieron las circunferencias cefálica y abdominal. En el tercer trimestre la longitud del fémur y la circunferencia abdominal coinciden en la identificación del pequeño y del grande. El PAL se correlacionó con la circunferencia abdominal del tercer trimestre y con el peso al nacer; presentando mayor frecuencia de valores en el tercer tertil para los nacimientos grandes. Conclusiones: La circunferencia abdominal fue el parámetro biométrico con mayor coincidencia con la condición trófica al nacer, la que se asoció con valores en el tercer tertil del PAL para la detección de nacimientos grandes, relacionándose el fenotipo normopeso metabólicamente obeso con el crecimiento fetal por exceso.

Background: Maternal nutritional status disorders are usually related to fetal growth deviations, which can be detected by fetal biophysical parameters and identify the possible trophic condition at birth. Objective: To determine the possible relationship between fetal biometric parameters, the birth trophic state and lipid accumulation product. Methodology: A cross-sectional study was conducted at the Chiqui Gómez Lubian Polyclinic in Santa Clara municipality, during 2019, in a population of 253 normal-weight pregnant women who were apparently healthy at the beginning of their gestation. The non-probability sample was made up of 144 pregnant women. Study variables were: lipid accumulation product, fetal biometry and trophic condition at birth. Theoretical, empirical and statistical methods were used. Results: In the second trimester, none of the biometric parameters matched the condition at birth as a small child, while in the large one the head and abdominal circumferences matched. In the third trimester, femoral length and abdominal circumference coincide in identifying the small one and the large one. LAP correlated with third trimester abdominal circumference and birth weight, presenting higher frequency of values in the third tertile for large births. Conclusions: Abdominal circumference was the biometric parameter with the highest coincidence with trophic condition at birth, associated with values in the third tertile of the LAP for detecting large births, relating the metabolically obese normal weight phenotype with excessive fetal growth.

Geometric Reliability of Super-Resolution Reconstructed Images from Clinical Fetal MRI in the Second Trimester.

Fetal Magnetic Resonance Imaging (MRI) is an important noninvasive diagnostic tool to characterize the central nervous system (CNS) development, significantly contributing to pregnancy management. In clinical practice, fetal MRI of the brain includes the acquisition of fast anatomical sequences over different planes on which several biometric measurements are manually extracted. Recently, modern toolkits use the acquired two-dimensional (2D) images to reconstruct a Super-Resolution (SR) isotropic volume of the brain, enabling three-dimensional (3D) analysis of the fetal CNS.We analyzed 17 fetal MR exams performed in the second trimester, including orthogonal T2-weighted (T2w) Turbo Spin Echo (TSE) and balanced Fast Field Echo (b-FFE) sequences. For each subject and type of sequence, three distinct high-resolution volumes were reconstructed via NiftyMIC, MIALSRTK, and SVRTK toolkits. Fifteen biometric measurements were assessed both on the acquired 2D images and SR reconstructed volumes, and compared using Passing-Bablok regression, Bland-Altman plot analysis, and statistical tests.Results indicate that NiftyMIC and MIALSRTK provide reliable SR reconstructed volumes, suitable for biometric assessments. NiftyMIC also improves the operator intraclass correlation coefficient on the quantitative biometric measures with respect to the acquired 2D images. In addition, TSE sequences lead to more robust fetal brain reconstructions against intensity artifacts compared to b-FFE sequences, despite the latter exhibiting more defined anatomical details.Our findings strengthen the adoption of automatic toolkits for fetal brain reconstructions to perform biometry evaluations of fetal brain development over common clinical MR at an early pregnancy stage.

Ultrasound evaluation of normal rhesus macaque fetal biometry and uteroplacental hemodynamics.

Nonhuman primates are important preclinical models for translational, reproductive, and developmental science. Clinical evaluation of human fetal development is performed using standard sonographic-derived fetal biometry, assessments of amniotic fluid, and uteroplacental hemodynamics. These noninvasive in utero measurements provide important information regarding fetal growth and pregnancy well-being. Abnormalities in fetal growth, amniotic fluid volume, or placental vascular function are associated with placental insufficiency and adverse perinatal outcomes including stillbirth. The fetal biometric parameters most commonly assessed are biparietal diameter, head circumference, abdominal circumference, and femur diaphysis length. Evaluation of amniotic fluid volume includes measuring the fluid in four quadrants of the uterus to generate an Amniotic Fluid Index. Measures of uteroplacental hemodynamics typically include doppler assessment of the umbilical artery and ductus venosus, but can also include interrogation of the uterine artery and umbilical vein. In this study, we compile prenatal ultrasound data of fetal biometry, amniotic fluid measurements, and uteroplacental hemodynamics obtained from pregnancy studies conducted at the Oregon National Primate Research Center. The data included are from control unperturbed pregnant animals who have not undergone in utero experimental manipulations. This is the first report of comprehensive sonographic measurements following standardized clinical obstetric protocols utilized in rhesus macaques. The outcome is a large, prenatal ultrasound resource to be used by laboratory animal researchers in future nonhuman primate pregnancy studies for antenatal assessment.