Biparietal diameter measurements using the outer-to-outer versus outer-to-inner measurement: A question of pedantry?

BabyNet＋＋: Fetal birth weight prediction using biometry multimodal data acquired less than 24 hours before delivery

Accurate prediction of fetal weight at birth is essential for effective perinatal care, particularly in the context of antenatal management, which involves determining the timing and mode of delivery. The current standard of care involves performing a prenatal ultrasound 24 hours prior to delivery. However, this task presents challenges as it requires acquiring high-quality images, which becomes difficult during advanced pregnancy due to the lack of amniotic fluid. In this paper, we present a novel method that automatically predicts fetal birth weight by using fetal ultrasound video scans and clinical data. Our proposed method is based on a Transformer-based approach that combines a Residual Transformer Module with a Dynamic Affine Feature Map Transform. This method leverages tabular clinical data to evaluate 2D+t spatio-temporal features in fetal ultrasound video scans. Development and evaluation were carried out on a clinical set comprising 582 2D fetal ultrasound videos and clinical records of pregnancies from 194 patients performed less than 24 hours before delivery. Our results show that our method outperforms several state-of-the-art automatic methods and estimates fetal birth weight with an accuracy comparable to human experts. Hence, automatic measurements obtained by our method can reduce the risk of errors inherent in manual measurements. Observer studies suggest that our approach may be used as an aid for less experienced clinicians to predict fetal birth weight before delivery, optimizing perinatal care regardless of the available expertise.

Intrauterine growth pattern in Butajira HDSS, Southern Ethiopia: BUNMAP pregnancy cohort

BACKGROUND

Abnormal fetal growth pattern during pregnancy including excessive fetal size and intrauterine growth restrictions are the major determinants for perinatal outcomes and postnatal growth. Ultrasonography is a useful tool in monitoring fetal growth for appropriate care and interventions. However, there are few longitudinal studies using serial ultrasonography in low and middle-income countries. Moreover, the reference charts used for fetal growth monitoring in low-income countries comes from high income countries with distinct population features. Therefore, the purpose of this study was to evaluate the intrauterine growth pattern of the fetus using serial ultrasonography.

METHODS

We conducted a prospective community-based cohort study from March 2018 to December 2019. Pregnant women with gestational age of 24 weeks or below living in the Butajira HDSS were enrolled. We followed the pregnant women until delivery. Serial ultrasound measurements were taken, and fetal weight was estimated using the Hadlock algorithm based on biparietal diameter, head circumference, abdominal circumference, and femur length. The z-scores and percentiles of biometric measurements were calculated and compared to the INTERGROWTH-21st International Standards for Fetal Growth.

RESULTS

We reviewed a total of 2055 ultrasound scans and 746 women who fulfill the inclusion criteria were involved". We found similar distribution patterns of biometric measurements and estimated fetal weight compared to the previous study done in Ethiopia, the WHO and INTERGROWTH-21st references. In our study, the 5th,50th and 95th percentiles of estimated fetal weight distribution have a similar pattern to the WHO and INTERGROWTH-21st charts. The 50th and 95th percentile had also a similar distribution pattern with the previous study conducted in Ethiopia. We found that 10% of the fetus were small for gestational age (below the 10th percentile) based on the Z-score of estimated fetal weight.

CONCLUSION

Our study evaluated the fetal growth patterns in rural community of Ethiopia using serial ultrasound biometric measurements. We found similar IUG patterns to the WHO and INTERGROWTH-21st reference standards as well as the previous study conducted in Ethiopia.

Update Reference Charts: Fetal Biometry between the 15th and 42nd Week of Gestation

OBJECTIVES

This study was designed to establish new reference charts for BPD (biparietal diameter), OFD (occipitofrontal diameter), HC (head circumference), CM (cisterna magna), TCD (transverse cerebellar diameter), PCV (posterior cerebral ventricle), AC (abdominal circumference), FL (femur length), and HL (humerus length) and extend known charts to 42 weeks of gestation. These new charts were compared to studies carried out by Snijders and Nicolaides, the INTERGROWTH 21st Project, and the WHO Fetal Growth Charts.

METHODS

In this retrospective cross-sectional single-center study of 12,972 low-risk pregnancies, biometric data between the 15th and 42nd weeks of gestation were evaluated. Only one examination per pregnancy was selected for statistical analysis. Descriptive analysis for the 5th, 50th, and 95th quantile was performed for each parameter as listed above. Regression models were used to fit the mean and the SD at each gestational age.

RESULTS

Initially the reference curves for BPD, OFD, HC, AC, FL, and HL show a linear increase, which changes into a cubic increase towards the end of pregnancy. The results of this study show statistically noticeable differences from the percentile curves of the studies listed above.

CONCLUSIONS

The percentile curves in this study differ from the commonly used ones. The presented standard curves can be used as a reference in prenatal diagnostics.

Deep learning fetal ultrasound video model match human observers in biometric measurements

Objective.This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, biparietal diameter, abdominal circumference and femur length, and to estimate gestational age and fetal weight using fetal ultrasound videos.Approach.We developed a novel multi-task CNN-based spatio-temporal fetal US feature extraction and standard plane detection algorithm (called FUVAI) and evaluated the method on 50 freehand fetal US video scans. We compared FUVAI fetal biometric measurements with measurements made by five experienced sonographers at two time points separated by at least two weeks. Intra- and inter-observer variabilities were estimated.Main results.We found that automated fetal biometric measurements obtained by FUVAI were comparable to the measurements performed by experienced sonographers The observed differences in measurement values were within the range of inter- and intra-observer variability. Moreover, analysis has shown that these differences were not statistically significant when comparing any individual medical expert to our model.Significance.We argue that FUVAI has the potential to assist sonographers who perform fetal biometric measurements in clinical settings by providing them with suggestions regarding the best measuring frames, along with automated measurements. Moreover, FUVAI is able perform these tasks in just a few seconds, which is a huge difference compared to the average of six minutes taken by sonographers. This is significant, given the shortage of medical experts capable of interpreting fetal ultrasound images in numerous countries.