Fetal weight estimation in gestational diabetic pregnancies: comparison between conventional and three-dimensional fractional thigh volume methods using gestation-adjusted projection

Prediction of large-for-gestational age at 36 weeks' gestation: two-dimensional ultrasound vs three-dimensional ultrasound vs magnetic resonance imaging

OBJECTIVE

To compare the performance of two-dimensional ultrasound (2D-US), three-dimensional ultrasound (3D-US) and magnetic resonance imaging (MRI) at 36 weeks' gestation in predicting the delivery of a large-for-gestational-age (LGA) neonate, defined as birth weight ≥ 95th percentile, in patients at high and low risk for macrosomia.

METHODS

This was a secondary analysis of a prospective observational study conducted between January 2017 and February 2019. Women with a singleton pregnancy at 36 weeks' gestation underwent 2D-US, 3D-US and MRI within 15 min for estimation of fetal weight. Weight estimations and birth weight were plotted on a growth curve to obtain percentiles for comparison. Participants were considered high risk if they had at least one of the following risk factors: diabetes mellitus, estimated fetal weight ≥ 90th percentile at the routine third-trimester ultrasound examination, obesity (prepregnancy body mass index ≥ 30 kg/m2) or excessive weight gain during pregnancy. The outcome was the diagnostic performance of each modality in the prediction of birth weight ≥ 95th percentile, expressed as the area under the receiver-operating-characteristics curve (AUC), sensitivity, specificity and positive and negative predictive values.

RESULTS

A total of 965 women were included, of whom 533 (55.23%) were high risk and 432 (44.77%) were low risk. In the low-risk group, the AUCs for birth weight ≥ 95th percentile were 0.982 for MRI, 0.964 for 2D-US and 0.962 for 3D-US; pairwise comparisons were non-significant. In the high-risk group, the AUCs were 0.959 for MRI, 0.909 for 2D-US and 0.894 for 3D-US. A statistically significant difference was noted between MRI and both 2D-US (P = 0.002) and 3D-US (P = 0.002), but not between 2D-US and 3D-US (P = 0.503). In the high-risk group, MRI had the highest sensitivity (65.79%) compared with 2D-US (36.84%, P = 0.002) and 3D-US (21.05%, P < 0.001), whereas 3D-US had the highest specificity (98.99%) compared with 2D-US (96.77%, P = 0.005) and MRI (96.97%, P = 0.004).

CONCLUSIONS

At 36 weeks' gestation, MRI has better performance compared with 2D-US and 3D-US in predicting birth weight ≥ 95th percentile in patients at high risk for macrosomia, whereas the performance of 2D-US and 3D-US is comparable. For low-risk patients, the three modalities perform similarly. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Association of maternal obesity with growth of fetal fractional limb volume

BACKGROUND

Maternal obesity influences birth weight and newborn adiposity. Fetal fractional limb volume has recently been introduced as a useful parameter for the proxy of fetal adiposity. However, the association between maternal adiposity and the growth of fetal fractional limb volume has not been examined.

AIMS

To investigate the association of maternal pre-pregnancy BMI with the growth of fetal fractional limb volume.

STUDY DESIGN

Prospective cohort study.

SUBJECTS

Women with singleton uncomplicated pregnancies enrolled between July 2017 and June 2020.

OUTCOME MEASURES

Fetal fractional limb volume was assessed between 20 and 40 weeks' gestation, measured as cylindrical limb volume based on 50 % of the total diaphysis length. The measured fractional limb volume at each gestational week were converted to z-scores based on a previous report. The association between pre-pregnancy BMI and fetal fractional limb volume was examined. Maternal age, parity, gestational weight gain and fetal sex were considered as potential confounding variables.

RESULTS

Ultrasound scans of 455 fractional arm volume and thigh volume were obtained. Fractional limb volume increased linearly until the second trimester of gestation, then increased exponentially in the third trimester. Maternal pre-pregnancy BMI was significantly correlated with z-scores of fractional arm volume and thigh volume across gestation. The post-hoc analysis showed the association between pre-pregnancy BMI and fractional arm volume was significant especially between 34 and 40 weeks.

CONCLUSIONS

Maternal obesity influences the growth pattern of fetal fractional limb volume. Fractional arm volume may potentially provide a useful surrogate marker of fetal nutritional status in late gestation.

Semiautomatic Assessment of Fetal Fractional Limb Volume for Weight Prediction in Clinical Praxis: How Does It Perform in Routine Use?

OBJECTIVES

Semiautomatic fractional limb volume (FLV) models have recently produced promising results for fetal birth weight (BW) estimation. We tested those models in a more unselected population hypothesizing that the FLV models would improve accuracy and precision of fetal BW estimation compared to the Hadlock model.

METHODS

We compared the performance of different BW prediction models: Hadlock (biparietal diameter [BPD], abdominal circumference (AC), femur diaphysis length) and modified Lee thigh volume (TVol) and arm volume (AVol) (BPD, AC, automated fractional TVol, and AVol). Accuracy (systematic errors, mean percent differences) and precision (random errors, ± 1 SD of percent differences) were calculated.

RESULTS

A total of 75 fetuses were included for final analysis. The Hadlock model showed the most consistent results with accurate BW estimation not significantly different from zero (-0.37 ± 8.53%). The modified fractional thigh and arm volume models were less accurate but trended toward more precise results (-2.63 ± 7.69% and -3.85 ± 7.47%, respectively). In addition, the modified TVol model showed the trend to predict more BWs within ±10% of the actual BW compared to the Hadlock model (81.3 versus 74.67%, ns).

CONCLUSIONS

Based on our results, fetal weight estimation using the modified semiautomatic FLV models generates less accurate results in third-trimester fetuses compared to the Hadlock model. Those models recently published might improve the results of BW prediction by showing a higher precision than conventional models, especially in small and large fetuses. Further studies are needed to investigate the clinical usefulness of the new models.

Fetal weight estimation by automated three-dimensional limb volume model in late third trimester compared to two-dimensional model: a cross-sectional prospective observational study

Background

Accurate estimation of fetal weight is important for prenatal care and for detection of fetal growth abnormalities. Prediction of fetal weight entails the indirect measurement of fetal biometry by ultrasound that is then introduced into formulae to calculate the estimated fetal weight. The aim of our study was to evaluate the accuracy of fetal weight estimation of Chinese fetuses in the third trimester using an automated three-dimensional (3D) fractional limb volume model, and to compare this model with the traditional two-dimensional (2D) model.

Methods

Prospective 2D and 3D ultrasonography were performed among women with singleton pregnancies 7 days before delivery to obtain 2D data, including fetal biparietal diameter, abdominal circumference and femur length, as well as 3D data, including the fractional arm volume (AVol) and fractional thigh volume (TVol). The fetal weight was estimated using the 2D model and the 3D fractional limb volume model respectively. Percentage error was defined as (estimated fetal weight - actual birth weight) divided by actual birth weight and multiplied by 100. Systematic errors (accuracy) were evaluated as the mean percentage error (MPE). Random errors (precision) were calculated as ±1 SD of percentage error. The intraclass correlation coefficient (ICC) was used to analyze the inter-observer reliability of the 3D ultrasound measurements of fractional limb volume.

Results

Ultrasound examination was performed on 56 fetuses at 39.6 ± 1.4 weeks’ gestation. The average birth weight of the newborns was 3393 ± 530 g. The average fetal weight estimated by the 2D model was 3478 ± 467 g, and the MPE was 3.2 ± 8.9. The average fetal weights estimated by AVol and TVol of the 3D model were 3268 ± 467 g and 3250 ± 485 g, respectively, and the MPEs were − 3.3 ± 6.6 and − 3.9 ± 6.1, respectively. For the 3D TVol model, the proportion of fetuses with estimated error ≤ 5% was significantly higher than that of the 2D model (55.4% vs. 33.9%, p < 0.05). For fetuses with a birth weight < 3500 g, the accuracy of the AVol and TVol models were better than the 2D model (− 0.8 vs. 7.0 and − 2.8 vs. 7.0, both p < 0.05). Moreover, for these fetuses, the proportions of estimated error ≤ 5% of the AVol and TVol models were 58.1 and 64.5%, respectively, significantly higher than that of the 2D model (19.4%) (both p < 0.05). The inter-observer reliability of measuring fetal AVol and TVol were high, with the ICCs of 0.921 and 0.963, respectively.

Conclusion

In this cohort, the automated 3D fractional limb volume model improves the accuracy of weight estimation in most third-trimester fetuses. Prediction accuracy of the 3D model for neonatal BW, particularly < 3500 g was higher than that of the traditional 2D model.

Predicting fetal weight by three-dimensional limb volume ultrasound (AVol/TVol) and abdominal circumference

BACKGROUND

Fetal weight is an important parameter to ensure maternal and child safety. The purpose of this study was to use three-dimensional (3D) limb volume ultrasound combined with fetal abdominal circumference (AC) measurement to establish a model to predict fetal weight and evaluate its efficiency.

METHODS

A total of 211 participants with single pregnancy (28-42 weeks) were selected between September 2017 and December 2018 in the Beijing Obstetrics and Gynecology Hospital of Capital Medical University. The upper arm (AVol)/thigh volume (TVol) of fetuses was measured by the 3D limb volume technique. Fetal AC was measured by two-dimensional ultrasound. Nine cases were excluded due to incomplete information or the interval between examination and delivery >7 days. The enrolled 202 participants were divided into a model group (134 cases, 70%) and a verification group (68 cases, 30%) by mechanical sampling method. The linear relationship between limb volume and fetal weight was evaluated using Pearson Chi-squared test. The prediction model formula was established by multivariate regression with data from the model group. Accuracy of the model formula was evaluated with verification group data and compared with traditional formulas (Hadlock, Lee2009, and INTERGROWTH-21st) by paired t-test and residual analysis. Receiver operating characteristic curves were generated to predict macrosomia.

RESULTS

AC, AVol, and TVol were linearly related to fetal weight. Pearson correlation coefficient was 0.866, 0.862, and 0.910, respectively. The prediction model based on AVol/TVol and AC was established as follows: Y = -481.965 + 12.194TVol + 15.358AVol + 67.998AC, R2adj = 0.868. The scatter plot showed that when birth weight fluctuated by 5% (i.e., 95% to 105%), the difference between the predicted fetal weight by the model and the actual weight was small. A paired t-test showed that there was no significant difference between the predicted fetal weight and the actual birth weight (t = -1.015, P = 0.314). Moreover, the residual analysis showed that the model formula's prediction efficiency was better than the traditional formulas with a mean residual of 35,360.170. The combined model of AVol/TVol and AC was superior to the Lee2009 and INTERGROWTH-21st formulas in the diagnosis of macrosomia. Its predictive sensitivity and specificity were 87.5% and 91.7%, respectively.

CONCLUSION

Fetal weight prediction model established by semi-automatic 3D limb volume combined with AC is of high accuracy, sensitivity, and specificity. The prediction model formula shows higher predictive efficiency, especially for the diagnosis of macrosomia.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03002246; https://clinicaltrials.gov/ct2/show/NCT03002246?recrs=e&cond=fetal&draw=8&rank=67.

Defining the Normal Growth Curve of Fetal Fractional Limb Volume in a Japanese Population

Fetal fractional limb volume is a useful measure for predicting birth weight and newborn adiposity; however, a normal growth curve has been reported solely in the United States. As the birth weight of neonates in Japan is significantly lower than that in the US, fetal fractional limb volume is likely to be smaller in the Japanese population. This study aimed to define the normal growth curve of fractional arm volume (AVol) and thigh volume (TVol) in the Japanese population. Ultrasound scans of 453 AVol and TVol pairs were obtained; each AVol and TVol percentile at each gestational age was calculated. The measured AVol and TVol at each gestational week were also converted to z-scores based on a previous report. The growth curves increased linearly until the second trimester and exponentially in the third trimester. Linear regression showed a significant negative correlation between gestational age and AVol and TVol z-scores. The growth pattern of fetal fractional limb volume in the Japanese population is consistent with, but smaller than, that reported in the US; this difference becomes greater as the gestational age progresses.

Fetal Weight Estimation Using Automated Fractional Limb Volume With 2-Dimensional Size Parameters: A Multicenter Study

OBJECTIVES

To develop new fetal weight prediction models using automated fractional limb volume (FLV).

METHODS

A prospective multicenter study measured fetal biometry within 4 to 7 days of delivery. Three-dimensional data acquisition included the automated FLV that was based on 50% of the humerus diaphysis (fractional arm volume [AVol]) or 50% of the femur diaphysis (fractional thigh volume [TVol]) length. A regression analysis provided population sample-specific coefficients to develop 4 weight estimation models. Estimated and actual birth weights (BWs) were compared for the mean percent difference ± standard deviation of the percent differences. Systematic errors were analyzed by the Student t test, and random errors were compared by the Pitman test.

RESULTS

A total of 328 pregnancies were scanned before delivery (BW range, 825-5470 g). Only 71.3% to 72.6% of weight estimations were within 10% of actual BW using original published models by Hadlock et al (Am J Obstet Gynecol 1985; 151:333-337) and INTERGROWTH-21st (Ultrasound Obstet Gynecol 2017; 49:478-486). All predictions were accurate by using sample-specific model coefficients to minimize bias in making these comparisons (Hadlock, 0.4% ± 8.7%; INTERGROWTH-21st, 0.5% ± 10.0%; AVol, 0.3% ± 7.4%; and TVol, 0.3% ± 8.0%). Both AVol- and TVol-based models improved the percentage of correctly classified BW ±10% in 83.2% and 83.9% of cases, respectively, compared to the INTERGROWTH-21st model (73.8%; P < .01). For BW of less than 2500 g, all models slightly overestimated BW (+2.0% to +3.1%). For BW of greater than 4000 g, AVol (-2.4% ± 6.5%) and TVol (-2.3% ± 6.9%) models) had weight predictions with small systematic errors that were not different from zero (P > .05). For these larger fetuses, both AVol and TVol models correctly classified BW (±10%) in 83.3% and 87.5% of cases compared to the others (Hadlock, 79.2%; INTERGROWTH-21st, 70.8%) although these differences did not reach statistical significance.

CONCLUSIONS

In this cohort, the inclusion of automated FLV measurements with conventional 2-dimensional biometry was generally associated with improved weight predictions.

Pregestational diabetes in pregnancy: Complications, management, surveillance, and mechanisms of disease-A review

Diabetes is an increasingly common diagnosis among pregnant women. Pregestational diabetes is associated with an increase in many adverse pregnancy outcomes, which impact both on the woman and her fetus. The models of pregnancy care for women with diabetes are based largely on observational data or consensus opinion. Strategies for aneuploidy screening and monitoring for fetal well-being should be modified in women with diabetes. There is an increasing understanding of the mechanisms by which congenital anomalies and disorders of fetal growth occur, involving epigenetic modifications, changes in gene expression in critical developmental pathways, and oxidative stress. This knowledge may lead to pathways for improved care for these high-risk pregnancies.

Prediction of fetal macrosomia using two-dimensional and three-dimensional ultrasound

OBJECTIVE

The estimation of the fetal weight by three-dimensional (3D) ultrasound (US) with fractional thigh volume (TVol) has been suggested to be more accurate than two-dimensional (2D) US particularly within the context of fetuses at risk of macrosomia. The objective of this study was to compare the accuracy of 2D US and 3D US with two different methods of projection for the identification of fetal macrosomia at term.

STUDY DESIGN

Prospective study which included women at risk for fetal macrosomia referred for fetal biometry between 34⁺⁰-36⁺⁶ weeks. The estimated fetal weight (EFW) was computed using 2D US and the Hadlock Model IV or through 3D US and the Model VI by Lee et al. The projection of the EFW at the time of delivery was performed by using Yudkin's chart percentiles and the gestation-adjusted projection (GAP) method.

RESULTS

Overall, 230 patients were included. Paired comparison between 2D-US-EFW and 3D-US-EFW with either method of projection of the EFW at birth suggested different properties of the techniques, being 2D-US-EFW associated with higher sensitivity and 3D-US-EFW with higher specificity, PPV and LR + . At ROC curve no difference was found in the prediction of birthweight ≥90th centile using 2D-US-EFW or 3D-US-EFW (AUC 0.831, 95%CI 0.768-0.894 versus AUC 0.860, 95%CI 0.799-0.920, respectively, p 0.37) nor in the prediction of birthweight >95th centile with 2D-US-EFW compared to 3D-US-EFW (0.803, 95%CI 0.731-0.874 versus 0.866, 95%CI 0.805-0.926, respectively, p 0.07). Similarly, a non-significant difference in the accuracy of the prediction of birthweight >4000 g (AUC 0.788, 95%CI 0.716-0.859 for 2D-US-EFW vs AUC 0.802, 95%CI 0.723-0.880 for 3D-US-EFW, p 0.72) and >4500 g (0.828, 95%CI 0.720-0.936 for 2D-US-EFW vs 0.858, 95%CI 0.759-0.956 for 3D-US-EFW, p 0.71) with the GAP method could be demonstrated.

CONCLUSIONS

Within a population at risk of fetal macrosomia the performance of 3D-US-EFW is similar to that of 2D-US-EFW in the prediction of macrosomia at term regardless of the method used for the projection of the EFW, however different properties were noted between the two techniques. Such finding suggests a potential complementary role of the techniques which warrants evaluation in future research.

Two-dimensional fetal biometry versus three-dimensional fractional thigh volume for ultrasonographic prediction of birthweight

OBJECTIVE

To develop and validate birthweight prediction models using fetal fractional thigh volume (TVol) in an Indian population, comparing them with existing prediction models developed for other ethnicities.

METHODS

A prospective observational study was conducted among 131 pregnant women (>36 weeks) attending a tertiary hospital in New Delhi, India, for prenatal care between December 1, 2014, and November 1, 2016. Participants were randomly divided into formulating (n=100) and validation (n=31) groups. Multiple regression analysis was performed to generate four models to predict birthweight using various combinations of two-dimensional (2D) ultrasonographic parameters and a three-dimensional (3D) ultrasonographic parameter (TVol). The best fit model was compared with previously published 2D and 3D models.

RESULTS

The best fit model comprised biparietal diameter, head circumference, abdominal circumference, and TVol. This model had the lowest mean percentage error (0.624 ± 8.075) and the highest coefficient of determination (R² =0.660). It correctly predicted 70.2% and 91.6% of birthweights within 5% and 10% of actual weight, respectively. Compared with previous models, attributability for the 2D and 3D models was 0.65 and 0.55, respectively. Accuracy was -0.05 ± 1.007 and -2.54 ± 1.11, respectively.

CONCLUSION

Models that included TVol provided good prediction of birthweight in the target population.

Fractional fetal thigh volume in the prediction of normal and abnormal fetal growth during the third trimester of pregnancy

Background

Currently, 2-dimensional ultrasound estimation of fetal size rather than fetal growth is used to define fetal growth restriction, but single estimates in late pregnancy lack sensitivity and may identify small for gestational age rather than growth restriction. Single or longitudinal measures of 3-dimensional fractional thigh volume may address this problem.

Objective

We sought to derive normal values for 3-dimensional fractional thigh volume in the third trimester, determine if fractional thigh volume is superior to 2-dimensional ultrasound biometry alone for detecting fetal growth restriction, and determine whether individualized growth assessment parameters have the potential to identify fetal growth restriction remote from term delivery.

Study Design

This was a longitudinal prospective cohort study of 115 unselected pregnancies in a tertiary referral unit (St Mary’s Hospital, Manchester, United Kingdom). Standard 2-dimensional ultrasound biometry measurements were obtained, along with fractional thigh volume measurements (based on 50% of the femoral diaphysis length). Measurements were used to calculate estimated fetal weight (Hadlock). Individualized growth assessment parameters and percentage deviations in longitudinally measured biometrics were determined using a Web-based system (iGAP; http://iGAP.research.bcm.edu). Small for gestational age was defined <10th and fetal growth restriction <3rd customized birthweight centile. Logistic regression was used to compare estimated fetal weight (Hadlock), estimated fetal weight (biparietal diameter–abdominal circumference–fractional thigh volume), fractional thigh volume, and abdominal circumference for the prediction of small for gestational age or fetal growth restriction at birth. Screening performance was assessed using area under the receiver operating characteristic curve.

Results

There was a better correlation between fractional thigh volume and estimated fetal weight ((biparietal diameter–abdominal circumference–fractional thigh volume) obtained at 34-36 weeks with birthweight than between 2-dimensional biometry measures such as abdominal circumference and estimated fetal weight (Hadlock). There was also a modest improvement in the detection of both small for gestational age and fetal growth restriction using fractional thigh volume–derived measures compared to standard 2-dimensional measurements (area under receiver operating characteristic curve, 0.86; 95% confidence interval, 0.79–0.94, and area under receiver operating characteristic curve, 0.92; 95% confidence interval, 0.85–0.99, respectively).

Conclusion

Fractional thigh volume measurements offer some improvement over 2-dimensional biometry for the detection of late-onset fetal growth restriction at 34-36 weeks.

Automated Fractional Limb Volume Measurements Improve the Precision of Birth Weight Predictions in Late Third-Trimester Fetuses

OBJECTIVES

Fetal soft tissue can be assessed by using fractional limb volume as a proxy for in utero nutritional status. We investigated automated fractional limb volume for rapid estimate fetal weight assessment.

METHODS

Pregnant women were prospectively scanned for 2- and 3-dimensional fetal biometric measurements within 4 days of delivery. Performance of birth weight prediction models was compared: (1) Hadlock (Am J Obstet Gynecol 1985; 151:333-337; biparietal diameter, abdominal circumference, and femur diaphysis length); and (2) Lee (Ultrasound Obstet Gynecol 2009; 34:556-565; biparietal diameter, abdominal circumference, and automated fractional limb volume). Percent differences were calculated: [(estimated birth weight - actual birth weight) ÷ (actual birth weight] × 100. Systematic errors (accuracy) were summarized as signed mean percent differences. Random errors (precision) were calculated as ± 1 SD of percent differences.

RESULTS

Fifty neonates were delivered at 39.4 weeks' gestation. The Hadlock model generated the most accurate birth weight (0.31%) with a mean random error of ±7.9%. Despite systematic underestimations, the most precise results occurred with fractional arm volume (-9.1% ± 5.1%) and fractional thigh (-5.2% ± 5.2%) models. The size and distribution of these prediction errors were improved after correction for systematic errors.

CONCLUSIONS

Automated fractional limb volume measurements can improve the precision of weight predictions in third-trimester fetuses. Correction factors may be necessary to adjust underestimated systematic errors when using automated fractional limb volume with prediction models that are based on manual tracing of fetal limb soft tissue borders.

Comparison of Errors of 35 Weight Estimation Formulae in a Standard Collective

Issue: The estimation of foetal weight is an integral part of prenatal care and obstetric routine. In spite of its known susceptibility to errors in cases of underweight or overweight babies, important obstetric decisions depend on it. In the present contribution we have examined the accuracy and error distribution of 35 weight estimation formulae within the normal weight range of 2500-4000 g. The aim of the study was to identify the weight estimation formulae with the best possible correspondence to the requirements of clinical routine. Materials and Methods: 35 clinically established weight estimation formulae were analysed in 3416 foetuses with weights between 2500 and 4000 g. For this we determined and compared the mean percentage error (MPE), the mean absolute percentage error (MAPE), and the proportions of estimates within the error ranges of 5, 10, 20 and 30 %. In addition, separate regression lines were calculated for the relationship between estimated and actual birth weights for the weight range 2500-4000 g. The formulae were thus examined for possible inhomogeneities. Results: The lowest MPE were achieved with the Hadlock III and V formulae (0.8 %, STW 9.2 % or, respectively, -0.8 %, STW 10.0 %). The lowest absolute error (6.6 %) as well as the most favourable frequency distribution in cases below 5 % and 10 % error (43.9 and 77.5) were seen for the Halaska formula. In graphic representations of the regression lines, 16 formulae revealed a weight overestimation in the lower weight range and an underestimation in the upper range. 14 formulae gave underestimations and merely 5 gave overestimations over the entire tested weight range. Conclusion: The majority of the tested formulae gave underestimations of the actual birth weight over the entire weight range or at least in the upper weight range. This result supports the current strategy of a two-stage weight estimation in which a formula is first chosen after a pre-estimation of the weight range.

Three-Versus Two-Dimensional Sonographic Biometry for Predicting Birth Weight and Macrosomia in Diabetic Pregnancies

OBJECTIVES

The purpose of this study was to test the hypothesis that a formula incorporating 3-dimensional (3D) fractional thigh volume would be superior to the conventional 2-dimensional (2D) formula of Hadlock et al (Am J Obstet Gynecol 1985; 151:333-337) for predicting birth weight and macrosomia.

METHODS

We conducted a prospective cohort study of pregnancies complicated by pregestational or gestational diabetes and delivered after 38 weeks. Two-dimensional and 3D sonographic examinations were performed for fetal biometry and factional thigh volumes at 34 to 37 weeks. Fetal weight was estimated by Hadlock's 2D formula IV, which uses only 2D biometry, and formula 6 from Lee et al (Ultrasound Obstet Gynecol 2009; 34:556-565), which incorporates 3D fractional thigh volume and 2D biometry. The gestation-adjusted projection method was used to estimate predicted birth weights from 2D and 3D estimates. The primary outcome was fetal macrosomia, which was defined as birth weight of 4000 g or higher.

RESULTS

A total of 115 women with diabetes met inclusion criteria, and 17 (14.8%) delivered macrosomic neonates. The mean percentage error was significantly lower for the 2D than the 3D projected estimate (1.0% versus 12.0%; P < .01). The standard deviation of the mean percentage error was also significantly lower for the 2D projected estimate (10.2% versus 17.2%; P< .01). Two-dimensional biometry was overall superior to 3D biometry for predicting macrosomia (area under the receiver operating characteristic curve, 0.88 versus 0.75; P = .03). Specificity was significantly higher for 2D biometry (85% versus 66%; P < .01), whereas the difference in sensitivity was not statistically significant (59% versus 71%; P = .22).

CONCLUSIONS

In this study, the Hadlock 2D formula was superior to the 3D method for predicting birth weight and macrosomia in diabetic women when used approximately 2 weeks before delivery, based on the gestation-adjusted projection method.

A Novel Semiautomated Fractional Limb Volume Tool for Rapid and Reproducible Fetal Soft Tissue Assessment

The purpose of this study was to document the reproducibility and efficiency of a semiautomated image analysis tool that rapidly provides fetal fractional limb volume measurements. Fifty pregnant women underwent 3-dimensional sonographic examinations for fractional arm and thigh volumes at a mean menstrual age of 31.3 weeks. Manual and semiautomated fractional limb volume measurements were calculated, with the semiautomated measurements calculated by novel software (5D Limb Vol; Samsung Medison, Seoul, Korea). The software applies an image transformation method based on the major axis length, minor axis length, and limb center coordinates. A transformed image is used to perform a global optimization technique for determination of an optimal limb soft tissue boundary. Bland-Altman analysis defined bias with 95% limits of agreement (LOA) between methods, and timing differences between manual versus automated methods were compared by a paired t test. Bland-Altman analysis indicated an acceptable bias with 95% LOA between the manual and semiautomated methods: mean arm volume ± SD, 1.7% ± 4.6% (95% LOA, -7.3% to 10.7%); and mean thigh volume, 0.0% ± 3.8% (95% LOA, -7.5% to 7.5%). The computer-assisted software completed measurements about 5 times faster compared to manual tracings. In conclusion, semiautomated fractional limb volume measurements are significantly faster to calculate when compared to a manual procedure. These results are reproducible and are likely to reduce operator dependency. The addition of computer-assisted fractional limb volume to standard biometry may improve the precision of estimated fetal weight by adding a soft tissue component to the weight estimation process.

Comparison of 2- and 3-Dimensional Sonography for Estimation of Birth Weight and Neonatal Adiposity in the Setting of Suspected Fetal Macrosomia

OBJECTIVES

To compare the accuracy of 2-dimensional (2D) and 3-dimensional (3D) fetal measurements for prediction of birth weight Z score and neonatal adiposity (percent body fat) in the setting of suspected fetal macrosomia.

METHODS

We conducted a prospective observational study of term singleton pregnancies with suspected macrosomia. Patients were enrolled on admission to labor and delivery and underwent sonographic examinations. Within 48 hours of delivery, neonatal anthropometric measurements were obtained.

RESULTS

Thirty-four neonates were included in the analysis. Mothers were very obese (mean body mass index ± SD, 39.1 ± 7.8 kg/m(2)); 56.5% were white; and 39.1% had diabetes. Neonates were 38% female and had a mean birth weight of 3940.0 ± 496.8 g, percent body fat of 18.5% ± 4.0%, and Ponderal index of 2.8 ± 0.3 g/cm(3). Mean 2D estimated fetal weight was 3973 ± 443 g; mean 3D estimated fetal weight was 3803 ± 528 g; and mean thigh volume was 102.5 ± 19.6 cm(3). Both 2D and 3D measurements accounted for about half the variance in predicted birth weight (R(2) for 2D = 0.53, 71% within 10% of birth weight; R(2) for 3D = 0.47, 65% within 10% of birth weight). Thigh volume Z score was the prenatal parameter most highly correlated with both birth weight Z score (R(2) = 0.52; r = 0.72; 95% confidence interval, 0.54-0.84; P < .001) and percent body fat (R(2) = 0.22; r = 0.47; 95% confidence interval, 0.17-0.69; P = .04).

CONCLUSIONS

In our population of fetuses with suspected macrosomia, fractional thigh volume was the best sonographic estimate of neonatal percent body fat and birth weight Z score. Future research on prediction of neonatal weight and adiposity in macrosomic fetuses should include an estimate of fetal soft tissue given the generalized increase in body fat of these fetuses.

3D and 2D ultrasound-based fetal weight estimation: a single center experience

OBJECTIVE

Evaluate two new 3D and two new 2D ultrasound formulae for fetal weight estimation against the modified Hadlock formula and compare their estimation to the actual fetal weight.

METHODS

Fifty pregnant females were included.

INCLUSION CRITERIA

singleton pregnancy, within five days of delivery and normal or IUGR pregnancy. 3D evaluation of the fetal thigh and arm was done to calculate mid-thigh and mid-arm volumes. The actual fetal weight was recorded at delivery and compared to the estimated weights.

RESULTS

Modified Hadlock formula had higher accuracy, whereas fractional limb volume method had higher precision. Systematic errors for the modified Hadlock formula, Model 6 of fractional limb volume and the original mid-thigh soft tissue thickness methods were 2.3%, -4.8% and 11%, respectively, whereas the random errors were 7.7%, 6.2% and 13.8%, respectively. The percentage of cases estimated within 5%, 10% and 15% of actual fetal weight were 48%, 86% and 92%, respectively, for the modified Hadlock method, whereas for the fractional limb volume method, these were 40%, 78% and 98%, respectively.

CONCLUSION

Fractional limb volume method is a very promising method for fetal weight estimation. Its performance is not significantly different from the modified Hadlock method.

Fetal weight estimation in diabetic pregnancies using the gestation-adjusted projection method: comparison of two timing strategies for third-trimester sonography

OBJECTIVES

The gestation-adjusted projection method extrapolates birth weight using third-trimester sonography. This technique is shown to be more accurate for sonographic examinations from 34 weeks to 36 weeks 6 days than 37 weeks to 38 weeks 6 days. Our objective was to determine whether even earlier sonographic examinations (31 weeks-33 weeks 6 days) further improves birth weight prediction in patients with diabetes.

METHODS

We conducted a retrospective cohort analysis of 388 pregnant women with pregestational or gestational diabetes who delivered at 37 weeks or later and had a sonographic examination performed between 31 weeks and 36 weeks 6 days. Sonographic examinations were categorized as "early" if performed at 31 weeks to 33 weeks 6 days or "late" if performed at 34 weeks to 36 weeks 6 days. We estimated birth weight using the gestation-adjusted projection method, compared errors in prediction of birth weight using the t test and Mann-Whitney U test, and performed a 2-sample test of proportions to compare prediction of macrosomia (birth weight >4000 g).

RESULTS

The early and late groups had similar mean gestational ages at birth (38 weeks 4 days versus 38 weeks 5 days; P = .13) and rates of macrosomia (10.7% versus 12.4%; P = .63). The early group had a greater mean absolute error (336 versus 297 g; P = .03) and percent error (9.9% versus 7.9%; P = .01) in birth weight prediction but a lower mean birth weight (3303 versus 3426 g; P = .02). Sensitivity for prediction of macrosomia was 19% in the early group versus 45% in the late group (P = .07), whereas specificity was similar (98% versus 96%; P = .27).

CONCLUSIONS

Using the gestation-adjusted projection method in our patients with diabetes, we found that sonographic examinations performed at 34 weeks to 36 weeks 6 days better predicted birth weight than those performed at 31 weeks to 33 weeks 6 days.

Statistical limits in sonographic estimation of birth weight

PURPOSE

The accuracy of sonographic estimation of birth weight (EBW) is compromised by the precision of the biometrical measurements and the quality of the algorithms. This prospective study was to evaluate technical aspects to derive new equations for the EBW.

METHODS

Three consecutive phases were carried out (1) to recruit a homogenous population, (2) to derive eight new algorithms using a multiple stepwise mathematical/statistical method, and (3) to test the accuracy of the developed equations. Only those patients with a singleton pregnancy who delivered within 48 h from the scan were considered for the analysis.

RESULTS

The study population was made of 473 women. Four polynomial, two square root and two logarithmic algorithms were derived from a balanced study group of 200 women selected from the original study population. These formulas were subsequently applied and compared between them and showed a significant correlation with birth weight (p < 0.0001) and satisfactory statistical performances (r > 0.9), nevertheless they performed similarly to other equations previously published.

CONCLUSIONS

The present findings define better the limitations associated with the intrinsic properties of algorithms and highlight that the possibility to improve the precision of sonographic measurements remains the only point at issue to increase the accuracy in the prediction of birth weight.