How good is fetal weight estimation using volumetric methods?

Factors influencing the accuracy of fetal weight estimation with a focus on preterm birth at the limit of viability: a systematic literature review

BACKGROUND

Fetal weight estimation (FWE) is an important factor for clinical management decisions, especially in imminent preterm birth at the limit of viability between 23(0/7) and 26(0/7) weeks of gestation. It is crucial to detect and eliminate factors that have a negative impact on the accuracy of FWE.

DATA SOURCES

In this systematic literature review, we investigated 14 factors that may influence the accuracy of FWE, in particular in preterm neonates born at the limit of viability.

RESULTS

We found that gestational age, maternal body mass index, amniotic fluid index and ruptured membranes, presentation of the fetus, location of the placenta and the presence of multiple fetuses do not seem to have an impact on FWE accuracy. The influence of the examiner's grade of experience and that of fetal gender were discussed controversially. Fetal weight, time interval between estimation and delivery and the use of different formulas seem to have an evident effect on FWE accuracy. No results were obtained on the impact of active labor.

DISCUSSION

This review reveals that only few studies investigated factors possibly influencing the accuracy of FWE in preterm neonates at the limit of viability. Further research in this specific age group on potential confounding factors is needed.

Measurement of fetal fat in utero in normal and diabetic pregnancies using magnetic resonance imaging

OBJECTIVES

To assess the reliability of magnetic resonance imaging (MRI) to measure fetal fat volume in utero, and to study fetal growth in women with and without diabetes in view of the increased prevalence of macrosomia in the former.

METHODS

We studied 26 pregnant women, 14 with pre-gestational diabetes and 12 non-diabetic controls. Fetal assessment took place at 24 weeks' gestation and again at 34 weeks by standard ultrasound biometry followed by MRI at 1.5 T. Fetal fat volume was determined from T1-weighted water-suppressed images using a semi-automated approach based on pixel intensity and taking into account partial volume effects. Fetal volume was also determined from the MRI images. Fetal weight was calculated using published fat and lean tissue densities.

RESULTS

There was little fetal fat at 24 weeks' gestation, but at 34 weeks the fetal fat content was considerably higher in the women with diabetes, with a mean fat content of 1090 ± 417 cm(3) compared with 541 ± 348 cm(3) in the controls (P = 0.006). Measurements of fetal fat volume showed low intra- and interobserver variability at 34 weeks, with intraclass correlation coefficients consistently above 0.99. Birth-weight centile correlated with fetal fat volume (R(2)  = 0.496, P < 0.001), percentage of fetal fat (R(2)  = 0.362, P = 0.008) and calculated fetal weight (R(2)  = 0.492, P < 0.001) at 34 weeks.

CONCLUSIONS

MRI appears to be a promising tool for the determination of fetal fat, body composition and weight in utero during the third trimester of pregnancy.

Role of fetal length in the prediction of fetal weight

OBJECTIVES

The purpose of this study was to compare the accuracy of routine fetal biometric indices in the prediction of fetal length and to determine whether more accurate sonographic measures of fetal length can improve the accuracy of fetal weight estimation.

METHODS

The accuracy of the common sonographic fetal biometric indices for predicting fetal length was determined using 3689 sonographic weight estimations performed within 3 days before delivery. The fetal length at the time of the sonographic examination was assumed to be equal to the neonatal length, which is routinely measured within 24 hours of delivery. Two new regression models for fetal weight estimation, one with and one without fetal length as an independent variable, were generated to determine the potential contribution of more accurate predictors of fetal length to the accuracy of fetal weight estimation.

RESULTS

Abdominal circumference was a significantly more accurate predictor of fetal length (r = 0.732) compared with femur length (r = 0.712), biparietal diameter (r = 0.644), and head circumference (r = 0.661; P < .05), although each of these biometric indices explained only about 50% of the variance in fetal length (R(2) = 0.423-0.548). The addition of fetal length as an independent variable to a birth weight prediction model significantly improved the model's correlation with birth weight(r = 0.917 versus 0.903; P = .006), systematic error (0.2% versus 0.6%; P < .001), random error (6.7% versus 7.5%; P < .001), mean absolute percent error, and the proportion of estimations within 5% and 10% of birth weight.

CONCLUSIONS

The correlation between routine biometric indices and fetal length is limited. Identification of new fetal sonographic biometric indices with greater predictive accuracy for fetal length may improve the accuracy of fetal weight estimation.

New fetal weight estimation models using fractional limb volume

OBJECTIVES

The main goal of this study was to determine the accuracy and precision of new fetal weight estimation models, based on fractional limb volume and conventional two-dimensional (2D) sonographic measurements during the second and third trimesters of pregnancy.

METHODS

A prospective cross-sectional study of 271 fetuses was performed using three-dimensional ultrasonography to extract standard measurements-biparietal diameter (BPD), abdominal circumference (AC) and femoral diaphysis length (FDL)-plus fractional arm volume (AVol) and fractional thigh volume (TVol) within 4 days of delivery. Weighted multiple linear regression analysis was used to develop 'modified Hadlock' models and new models using transformed predictors that included soft tissue parameters for estimating birth weight. Estimated and observed birth weights were compared using mean percent difference (systematic weight estimation error) and the SD of the percent differences (random weight estimation error). The proportion of newborns with estimated birth weight within 5 or 10% of actual birth weight were compared using McNemar's test.

RESULTS

Birth weights in the study group ranged from 235 to 5790 g, with equal proportions of male and female infants. Six new fetal weight estimation models were compared with the results for modified Hadlock models with sample-specific coefficients. All the new models were very accurate, with mean percent differences that were not significantly different from zero. Model 3 (which used the natural logarithms of BPD, AC and AVol) and Model 6 (which used the natural logarithms of BPD, AC and TVol) provided the most precise weight estimations (random error = 6.6% of actual birth weight) as compared with 8.5% for the best original Hadlock model and 7.6% for a modified Hadlock model using sample-specific coefficients. Model 5 (which used the natural logarithms of AC and TVol) classified an additional 9.1% and 8.3% of the fetuses within 5% and 10% of actual birth weight and Model 6 classified an additional 7.3% and 4.1% of infants within 5% and 10% of actual birth weight.

CONCLUSION

The precision of fetal weight estimation can be improved by adding fractional limb volume measurements to conventional 2D biometry. New models that consider fractional limb volume may offer novel insight into the contribution of soft tissue development to weight estimation.