Estimated Fetal Weight Research Articles

Reducing macrosomia-related birth complications in primigravid women: ultrasound- and magnetic resonance imaging–based models

Many complications increase with macrosomia, which is defined as birthweight of ≥4000 g. The ability to estimate when the fetus would exceed 4000 g could help to guide decisions surrounding the optimal timing of delivery. To the best of our knowledge, there is no available tool to perform this estimation independent of the currently available growth charts. This study aimed to develop ultrasound- and magnetic resonance imaging-based models to estimate at which gestational age the birthweight would exceed 4000 g, evaluate their predictive performance, and assess the effect of each model in reducing adverse outcomes in a prospectively collected cohort. This study was a subgroup analysis of women who were recruited for the estimation of fetal weight by ultrasound and magnetic resonance imaging at 36 0/7 to 36 6/7 weeks of gestation. Primigravid women who were eligible for normal vaginal delivery were selected. Multiparous patients, patients with preeclampsia spectrum, patients with elective cesarean delivery, and patients with contraindications for normal vaginal delivery were excluded. Of note, 2 linear models were built for the magnetic resonance imaging- and ultrasound-based models to predict a birthweight of ≥4000 g. Moreover, 2 formulas were created to predict the gestational age at which birthweight will reach 4000 g (predicted gestational age); one was based on the magnetic resonance imaging model, and the second one was based on the ultrasound model. This study compared the adverse birth outcomes, such as intrapartum cesarean delivery, operative vaginal delivery, anal sphincter injury, postpartum hemorrhage, shoulder dystocia, brachial plexus injury, Apgar score of <7 at 5 minutes of life, neonatal intensive care unit admission, and intracranial hemorrhage in the group of patients who delivered after the predicted gestational age according to the magnetic resonance imaging-based or the ultrasound-based models with those who delivered before the predicted gestational age by each model, respectively. Of 2378 patients, 732 (30.8%) were eligible for inclusion in the current study. The median gestational age at birth was 39.86 weeks of gestation (interquartile range, 39.00-40.57), the median birthweight was 3340 g (interquartile range, 3080-3650), and 63 patients (8.6%) had a birthweight of ≥4000 g. Prepregnancy body mass index, geographic origin, gestational age at birth, and fetal body volume were retained for the optimal magnetic resonance imaging-based model, whereas maternal age, gestational diabetes mellitus, diabetes mellitus type 1 or 2, geographic origin, fetal gender, gestational age at birth, and estimated fetal weight were retained for the optimal ultrasound-based model. The performance of the first model was significantly better than the second model (area under the curve: 0.98 vs 0.89, respectively; P<.001). The group of patients who delivered after the predicted gestational age by the first model (n=40) had a higher risk of cesarean delivery, postpartum hemorrhage, and shoulder dystocia (adjusted odds ratio: 3.15, 4.50, and 9.67, respectively) than the group who delivered before this limit. Similarly, the group who delivered after the predicted gestational age by the second model (n=25) had a higher risk of cesarean delivery and postpartum hemorrhage (adjusted odds ratio: 5.27 and 6.74, respectively) than the group who delivered before this limit. The clinical use of magnetic resonance imaging- and ultrasound-based models, which predict a gestational age at which birthweight will exceed 4000 g, may reduce macrosomia-related adverse outcomes in a primigravid population. The magnetic resonance imaging-based model is better for the identification of the highest-risk patients.

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

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. This study aimed to develop and test a deep learning method to automatically estimate fetal weight from fetal abdominal ultrasound video scans. 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. 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. 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.

Diagnostic Accuracy of Ultrasonography for the Detection of Foetal Weight

Background: Ultrasonography is a very useful diagnostic tool for the detection of foetal weight. Objective: The purpose of the present study was to validate the ultrasonography for the detection of foetal weight. Methodology: This prospective cohort study was carried out in the Department of Obstetrics &amp; Gynaecology at Rajshahi Medical Hospital, Rajshahi, Rajshahi, Bangladesh from July 2012 to June 2014 for a period of 2(two) years. Pregnant women with known gestational age at term (38 to 40 weeks of pregnancy), singleton pregnancy with longitudinal lie were included in this study. The patient was then taken to Dept. of Radiology &amp; Imaging, RMCH. Ultrasonographic estimation of foetal weight was done from estimation of foetal abdominal circumference (AC), biparietal diameter (BPD) and foetal femur length (FL). Actual birth weights of babies were measured soon after their birth. The BPD, AC and FL were measured in centimetres and foetal weight was measured in grams. Actual birth weight is the first weight of now-born obtained after birth. This weight was measured within the first hour of life. Result: A total number of 245 pregnant women in term pregnancy were recruited as per inclusion and exclusion criteria. Majority of the women [91(37.1%)] belonged to the age group 19 to 29 years which was 174(71.0%) cases. Low birth weight was found in 12(4.9%) cases ultrasonographic examination and actual low birth weight was found in 15(6.0%) cases. Overweight was found in 13(5.2%) cases ultrasonographic examination and actual birth overweight was found in 9(3.7%) cases. The mean value and SD of foetal weight measured by USG was 2870.41 gms and 424.84 respectively. In case of actual birth weight, the mean and SD was 2936.20 gms and 456.71 respectively (p = 0.05). Conclusion: In conclusion estimation of foetal weight by ultrasonography is not significantly varied. Journal of National Institute of Neurosciences Bangladesh, January 2023;9(1):16-19

Estimation of Foetal Weight by Ultrasonography and Neonate at Birth

Background: Ultrasonography intervention in delivery is highly sensitive and primary important for further tests of foetal well-being. Objective: The purpose of the present study was to observe the correlation of estimated foetal weight with neonatal birth weight. Methodology: This was a cross-sectional study on patients at the Labour Ward of Department of Obstetrics and Gynaecology at Sir Salimullah Medical College and Mitford Hospiptal, Dhaka, Bangladesh for six months. The women were selected who had normal pregnancy with early ultrasounographic examination for confirmation of gestational age, singleton live foetus, ultrasound examination for pregnancy profile done within 3 days before delivery. A sonographic foetal weight was estimated by using measurements of foetal body parts-biparietal diameter, abdominal circumference and femoral length. To measure the femur length, first a projection was made that shows a transverse section of one of the long bones, then scan at 900 to this to obtain a longitudinal section. Results: A total number of 100 patients were recruited for this study. The mean (±SD) sonographically estimated foetal weight was 3074±534gm with ranged from 2100 to 4100 gm. The mean (±SD) neonatal birth weight was 2978±466 gm with ranged from 2500 to 3800 gm (p&lt;0.05). Sonographically estimated foetal weight less than 3000 g were correlated with neonatal birth weight. Out of the 100 cases 57(57.0%) cases had less than 3000 g estimated foetal weight and 43(43.0%) cases had 3000 g or more than 3000gm estimated foetal weight Sonographically. Among the 57 cases, which were less than 3000 g by Sonographically, 41 cases were less than 3000 g and 16 cases were found 3000 g or more than 3000 g in neonatal birth weight. Conclusion: Ultrasonography has definite value in the diagnosis of estimated foetal weight and can be regarded as a sensitive and specific imaging modality for pre-operative discrimination of the pregnant women. Journal of National Institute of Neurosciences Bangladesh, January 2023;9(1):42-47

Effect of Maternal Body Mass Index on The Accuracy of Sonographic Estimation of Foetal Weight in Late Gestation

Effect of Maternal Body Mass Index on The Accuracy of Sonographic Estimation of Foetal Weight in Late Gestation

OP06.04: Comprehensive audit of estimation of fetal weight in preterm and term population in a tertiary centre

OP06.04: Comprehensive audit of estimation of fetal weight in preterm and term population in a tertiary centre

Information sharing and communication in management of large for gestational age babies in non‐diabetic mothers

Key content There is no specific UK guideline on how to identify or manage large for gestational age (LGA) fetuses in non‐diabetic mothers. There is conflicting evidence with regard to the optimal mode and timing of delivery in such women and babies in order to minimise the possible risks. Pre‐delivery patient–clinician discussion on management and mode of delivery in LGA babies can be challenging due to the lack of conclusive evidence and guidance for both screening and interventions, but it is crucial in order to facilitate information sharing, counselling and collaborative decision making. Decision‐making tools could help to facilitate these discussions and ensure ‘material risks’ are discussed. Learning objectives To be aware of the limitations of available methods for screening for LGA fetuses, specifically symphyseal fundal height and ultrasound estimation of fetal weight. To understand the lack of robust evidence for obstetric interventions, which makes it difficult to convey clear information in a practical and useful way. To consider the use of decision‐making tools (such as BRAIN and iDECIDE), which can provide a framework for shared decision making, particularly when the evidence is limited or conflicting. These tools offer a structure which empowers patients to weigh up information as well as assist clinicians in determining what is considered ‘material risk’ when counselling in line with the Montgomery ruling. Ethical issues The Montgomery ruling advises that doctors must discuss any ‘material risks’ involved in a proposed treatment and offer other reasonable alternatives. Clinicians, therefore, have a duty to be transparent about the lack of strong evidence to recommend one mode of birth over another but at the same time acknowledge that individual preference and perceptions need to be explored to enable personalised decision making.

EP14.18: Accuracy of sonographic fetal weight estimation and birthweight discordance in twin pregnancies

EP14.18: Accuracy of sonographic fetal weight estimation and birthweight discordance in twin pregnancies

EP25.13: Comparison of three methods of fetal weight estimation in patients with severe and morbid obesity: a prospective study

EP25.13: Comparison of three methods of fetal weight estimation in patients with severe and morbid obesity: a prospective study

EP25.26: Sonographic fetal weight estimations by residents

EP25.26: Sonographic fetal weight estimations by residents

Predicting Big Babies: Using Amniotic Fluid and Baby Weight Estimates

Background: Macrosomia or big baby is defined as a newborn with a birth weight of more than 4kg. Amniotic fluid index (AFI) which is estimated by adding length of deepest vertical pool in four corners of liquor in uterus is an indicator of fetal well-being. This parameter when combined with ultrasonographic estimated fetal weight can predict macrosomia accurately. Objective: To evaluate diagnostic accuracy of integrated examination with amniotic fluid index (AFI) and estimated fetal weight (EFW) for prediction of macrosomia. Study Design: Cross sectional study. Settings: Department of Obstetrics and Gynecology, Combined Military Hospital (CMH), Rawalpindi Pakistan. Duration: 6 months from 29th October 2019 to 28th April 2020. Methods: After meeting the inclusion criteria 250 females were enrolled. All patients underwent sonographic evaluation for AFI and EFW estimation. Patients were categorized as positive or negative for macrosomia. Then all females were followed-up in OPD till delivery. If birth weight was ≥4000 grams, then macrosomia was confirmed. Results: The average age of the females was 27.21 ± 4.59 years, there were 55(22%) females as nulliparous. The sensitivity, specificity, and diagnostic accuracy of integrated examination of AFI &amp; EFW were 50%, 98.78%, &amp; 98% for definition of macrosomia as base line. Conclusion: This study showed good diagnostic accuracy of integrated amniotic fluid index and ultrasound baby weight estimates as predictor of macrosomia having low sensitivity.

The effects of gestational diabetes mellitus on fetal growth: is it different for low-risk and medium-high-risk pregnant women?

It has been suggested that gestational diabetes mellitus (GDM) alters the growth trajectory of a fetus and increases the risk of abnormal birth weight. In spite of this, there is still a significant debate regarding the mode and optimal timing of diagnosing this condition. Our aim was to determine fetal growth velocity and birth biometry in pregnant women with GDM at varying risk levels. We conducted a cohort study involving 1023 pregnant women at a maternity hospital in Ma'anshan, China. All women completed an oral glucose tolerance test at 24-28 weeks' gestation. We measured fetal head circumference (HC), femoral length (FL), abdominal circumference (AC), biparietal diameter (BPD), and estimate fetal weight (EFW) by ultrasound at 17, 24, 31, and 35 weeks' gestation, respectively. Overall, 5115 ultrasound scans were performed. Among both low-risk and medium-high-risk pregnant women at 17-24 weeks' gestation, GDM exposure was associated with an increase in fetal growth velocity. Neonates born to women with GDM at medium-high risk had significantly larger birth weights than those born to women without GDM, while this was not observed in women at low risk. In medium-high-risk pregnant women, exposure to GDM has a greater effect on the fetus, leading to abnormal fetal growth velocity that lasts beyond week 24. It is evident from our results that the effects of GDM on fetal growth differ between medium-high-risk pregnant women and low-risk pregnant women, and therefore a different screening program based on the risk factor for GDM is warranted.

The adverse impact of maternal ozone exposure on fetal growth in utero and the interaction with residential greenness

This study aimed to investigate the effect of maternal ozone exposure on fetal growth during pregnancy, as well as the combined effect and interaction of ozone and residential greenness. We included a total of 14990 singleton pregnancies from the Fujian Birth Cohort Study. During pregnancy, fetal growth parameters including estimated fetal weight (EFW), femur length (FL), head circumference (HC), and abdominal circumference (AC). To investigate the associations between ozone exposure and the above-mentioned outcomes, generalized estimating equation approach and generalized linear regression were used, as appropriate. In the adjusted models, we observed that the Z scores of EFW (−0.031 (−0.048, −0.014)), FL (−0.021 (−0.038, −0.004)), and AC (−0.025 (−0.042, −0.007)) decreased with per interquartile range (IQR) increase of ozone concentration. Compared to participants with low ozone exposure and high NDVI, those with high ozone exposure and low NDVI experienced the largest decrease in Z scores for EFW (−0.049 (−0.079, −0.02)), FL (−0.034 (−0.063, −0.004)), HC (−0.034 (−0.065, −0.004)), and AC (−0.041 (−0.072, −0.01)), respectively. Interestingly, we discovered the effect modification of NDVI on the relationship between ozone exposure and fetal growth restriction (P for interaction < 0.05). This study established a negative relationship of maternal ozone exposure and fetal growth. Of importance, this study discovered the joint effect and interaction between ozone and residential greenness exposure.

Deep learning-based segmentation of whole-body fetal MRI and fetal weight estimation: assessing performance, repeatability, and reproducibility.

To develop a deep-learning method for whole-body fetal segmentation based on MRI; to assess the method's repeatability, reproducibility, and accuracy; to create an MRI-based normal fetal weight growth chart; and to assess the sensitivity to detect fetuses with growth restriction (FGR). Retrospective data of 348 fetuses with gestational age (GA) of 19-39weeks were included: 249 normal appropriate for GA (AGA), 19 FGR, and 80 Other (having various imaging abnormalities). A fetal whole-body segmentation model with a quality estimation module was developed and evaluated in 169 cases. The method was evaluated for its repeatability (repeated scans within the same scanner, n = 22), reproducibility (different scanners, n = 6), and accuracy (compared with birth weight, n = 7). A normal MRI-based growth chart was derived. The method achieved a Dice = 0.973, absolute volume difference ratio (VDR) = 1.8% and VDR mean difference = 0.75% ([Formula: see text]: - 3.95%, 5.46), and high agreement with the gold standard. The method achieved a repeatability coefficient = 4.01%, ICC = 0.99, high reproducibility with a mean difference = 2.21% ([Formula: see text]: - 1.92%, 6.35%), and high accuracy with a mean difference between estimated fetal weight (EFW) and birth weight of - 0.39% ([Formula: see text]: - 8.23%, 7.45%). A normal growth chart (n = 246) was consistent with four ultrasound charts. EFW based on MRI correctly predicted birth-weight percentiles for all 18 fetuses ≤ 10thpercentile and for 14 out of 17 FGR fetuses below the 3rd percentile. Six fetuses referred to MRI as AGA were found to be < 3rd percentile. The proposed method for automatic MRI-based EFW demonstrated high performance and sensitivity to identify FGR fetuses. Results from this study support the use of the automatic fetal weight estimation method based on MRI for the assessment of fetal development and to detect fetuses at risk for growth restriction. • An AI-based segmentation method with a quality assessment module for fetal weight estimation based on MRI was developed, achieving high repeatability, reproducibility, and accuracy. • An MRI-based fetal weight growth chart constructed from a large cohort of normal and appropriate gestational-age fetuses is proposed. • The method showed a high sensitivity for the diagnosis of small fetuses suspected of growth restriction.

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

To investigate the correlation between fetal clavicle length and gestational age in pregnant patients from 14 and 27weeks of gestation. This was a retrospective cross-sectional study of patients from 14 and 27weeks 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. 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. There was a significant positive correlation between fetal CL (mm) and gestational week. We suggest that the 1mm = 1week rule can be used for patients with anomalies of the cerebellum and vermis, as well as for patients with unknown last menstrual period.

The impact of different growth charts on birthweight prediction: obstetrical ultrasound vs magnetic resonance imaging

The estimation of fetal weight (EFW) by fetal magnetic resonance imaging (MRI) is a simple and rapid method, with a high sensitivity to predict birthweight (BW) in comparison to ultrasound (US). Several national and international growth charts are currently in use but there is substantial heterogeneity among these charts due to: variations in the selected populations from which they were derived, different methodologies and statistical analysis of data. The purpose of this study was to compare the performance of MRI and US for the prediction of BW using three commonly used fetal growth charts: INTERGROWTH-21st (IG-21) project, World Health Organization (WHO), and Fetal Medicine Foundation (FMF). Data derived from a prospective, single center, blinded cohort study that compared the performance of MRI and US between 36+0/7 to 36+6/7 weeks of gestation (WG) for the prediction of BW ≥ 95th percentile was reanalyzed. EFW were categorized as > or < 5th, > or < 10th, > or < 90th, and > or < 95th percentile according to the three growth charts. BW was similarly categorized according to the BW standards of each chart. The performances of US and MRI for the prediction of BW < 5th, < 10th, > 90th, and > 95th percentile using the different growth charts were compared. Data were analysed with R software version 4.1.2. The comparison of sensitivity and specificity was done by McNemar and exact binomial tests. A p-value < 0.05 was considered as statistically significant. 2378 women were eligible for final analysis. US and MRI were performed at a median gestational age of 36+3/7 WG, delivery occurred at a median gestational age of 39+3/7 WG, and median BW was 3380 grams. The incidences of BW < 5th and < 10th percentiles were highest with the FMF chart and lowest with the IG-21 chart, whereas the incidences of BW > 90th and > 95th percentiles were lowest with the FMF chart and highest with the IG-21 chart. The sensitivity of MRI with an EFW > 95th percentile in the prediction of BW > 95th percentile was significantly higher than that of US across the three growth charts, however, its specificity was slightly lower than that of US. In contrast, the sensitivity of MRI with an EFW <10th percentile for predicting BW <10th percentile was significantly lower than US in the IG-21 and FMF charts, whereas the specificity and positive predictive value (PPV) of MRI were significantly higher than US for the three charts. Findings for the prediction of BW > 90th percentile were close to those of BW > 95th percentile, and findings for the prediction of BW < 5th percentile were close to those of BW < 10th percentile. The sensitivity of MRI is superior to US for the prediction of large for gestational age (LGA) fetuses and inferior to US for the prediction of small for gestational age (SGA) fetuses across the three different growth charts. The reverse is true for the specificity of MRI in comparison to the specificity of US.

Do differences in diagnostic criteria for late fetal growth restriction matter?

Criteria for diagnosis of fetal growth restriction differ widely according to national and international guidelines, and further heterogeneity arises from the use of different biometric and Doppler reference charts, making the diagnosis of fetal growth restriction highly variable. This study aimed to compare fetal growth restriction definitions between Delphi consensus and Society for Maternal-Fetal Medicine definitions, using different standards/charts for fetal biometry and different reference ranges for Doppler velocimetry parameters. From the TRUFFLE 2 feasibility study (856 women with singleton pregnancy at 32+0 to 36+6 weeks of gestation and at risk of fetal growth restriction), we selected 564 women with available mid-pregnancy biometry. For the comparison, we used standards/charts for estimated fetal weight and abdominal circumference from Hadlock, INTERGROWTH-21st, and GROW and Chitty. Percentiles for umbilical artery pulsatility index and its ratios with middle cerebral artery pulsatility index were calculated using Arduini and Ebbing reference charts. Sensitivity and specificity for low birthweight and adverse perinatal outcome were evaluated. Different combinations of definitions and reference charts identified substantially different proportions of fetuses within our population as having fetal growth restriction, varying from 38% (with Delphi consensus definition, INTERGROWTH-21st biometric standards, and Arduini Doppler reference ranges) to 93% (with Society for Maternal-Fetal Medicine definition and Hadlock biometric standards). None of the different combinations tested appeared effective, with relative risk for birthweight <10th percentile between 1.4 and 2.1. Birthweight <10th percentile was observed most frequently when selection was made with the GROW/Chitty charts, slightly less with the Hadlock standard, and least frequently with the INTERGROWTH-21st standard. Using the Ebbing Doppler reference ranges resulted in a far higher proportion identified as having fetal growth restriction compared with the Arduini Doppler reference ranges, whereas Delphi consensus definition with Ebbing Doppler reference ranges produced similar results to those of the Society for Maternal-Fetal Medicine definition. Application of Delphi consensus definition with Arduini Doppler reference ranges was significantly associated with adverse perinatal outcome, with any biometric standards/charts. The Society for Maternal-Fetal Medicine definition could not accurately detect adverse perinatal outcome irrespective of estimated fetal weight standard/chart used. Different combinations of fetal growth restriction definitions, biometry standards/charts, and Doppler reference ranges identify different proportions of fetuses with fetal growth restriction. The difference in adverse perinatal outcome may be modest, but can have a significant impact in terms of rate of intervention.

The Impact of the Active Stage of Labor on Estimate Fetal Weight: A Prospective Cohort Study

Objective: In the literature, there have been few data on ultrasound measurements during the active phase of labor. In this study, it was aimed to compare the accuracy of fetal weight estimation by ultrasound in terms of active phase of labor. Methods: This was a prospective cohort study at the obstetrics clinic of Esenler Gynecology and Children's Hospital in Istanbul. A total of 85 patients in active labor were included in the study. All pregnant women were evaluated for estimated fetal weight (EFW) by ultrasound evaluation, and cervical dilation and effacement measurements by pelvic examination, at most 24 hours before labor. Hadlock-4 formula was used for EFW. EFW and actual birth weight (ABW) and absolute errors of pregnant women in active labor were compared. Results: The mean EFW and ABW of the patients were 3161±482 and 3150±476 g, respectively. In terms of EFW and ABW, a finding in favor of the ultrasound was found. The error and error rates between EFW and ABW were found to be 234±191 g and 7.6±6.2, respectively. No significant difference was found in terms of these parameters (p&amp;gt;0.05). A significant and strong (0.80) correlation was found with estimated fetal weights and actual birth weights. Conclusion: Ultrasound can be used as a safe method to measure estimated fetal weight in the active phase of labor.

Fetal weight estimation based on deep neural network: a retrospective observational study

BackgroundImproving the accuracy of estimated fetal weight (EFW) calculation can contribute to decision-making for obstetricians and decrease perinatal complications. This study aimed to develop a deep neural network (DNN) model for EFW based on obstetric electronic health records.MethodsThis study retrospectively analyzed the electronic health records of pregnant women with live births delivery at the obstetrics department of International Peace Maternity & Child Health Hospital between January 2016 and December 2018. The DNN model was evaluated using Hadlock’s formula and multiple linear regression.ResultsA total of 34824 live births (23922 primiparas) from 49896 pregnant women were analyzed. The root-mean-square error of DNN model was 189.64 g (95% CI 187.95 g—191.16 g), and the mean absolute percentage error was 5.79% (95%CI: 5.70%—5.81%), significantly lower compared to Hadlock’s formula (240.36 g and 6.46%, respectively). By combining with previously unreported factors, such as birth weight of prior pregnancies, a concise and effective DNN model was built based on only 10 parameters. Accuracy rate of a new model increased from 76.08% to 83.87%, with root-mean-square error of only 243.80 g.ConclusionsProposed DNN model for EFW calculation is more accurate than previous approaches in this area and be adopted for better decision making related to fetal monitoring.

Corpus callosum-fastigium and tectal lengths in late-onset small fetuses.

To investigate measurements on neurosonography of midbrain morphology, including corpus callosum-fastigium length and tectal length, in late-onset small fetuses subclassified as small-for-gestational-age (SGA) or growth-restricted (FGR). This was a case-control study of consecutive singleton pregnancies delivered at term at a single center between January 2019 and July 2021, including those with late-onset smallness (estimated fetal weight (EFW) < 10th centile) and appropriate-for-gestational-age controls matched by age at neurosonography. Small fetuses were further subdivided into SGA (EFW between 3rd and 9th centile and normal fetoplacental Doppler) and FGR (EFW < 3rd centile or EFW < 10th centile with abnormal cerebroplacental ratio and/or uterine artery Doppler). Transvaginal neurosonography was performed at a mean ± SD gestational age of 33 ± 1 weeks in all fetuses to evaluate corpus callosum-fastigium length and tectal length in the midsagittal plane. Intra- and interobserver agreement was evaluated using the intraclass correlation coefficient and Bland-Altman plots. A total of 70 fetuses with late-onset smallness (29 with SGA and 41 with FGR) and 70 controls were included. Compared with controls, small fetuses showed significantly shorter corpus callosum-fastigium length (median (interquartile range), 44.7 (43.3-46.8) mm vs 43.7 (42.4-45.5) mm, P < 0.001) and tectal length (mean ± SD, 10.5 ± 0.9 vs 9.6 ± 1.0 mm, P < 0.001). These changes were more prominent in FGR fetuses, with a linear trend across groups according to severity of smallness. Corpus callosum-fastigium length and tectal length measurements showed excellent intra- and interobserver reliability. Small fetuses exhibited shorter corpus callosum-fastigium length and tectal length compared with controls, and these differences were more pronounced in fetuses with more severe smallness. These findings illustrate the potential value of midbrain measurements assessed on neurosonography as biomarkers for brain development in a high-risk population. However, further studies correlating these parameters with postnatal functional tests and follow-up are needed. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.