Predicting Fetal Weight by Three-Dimensional Limb Volume Ultrasound (AVol/TVol) and Abdominal Circumference

Predicting Fetal Weight by Three-Dimensional Limb Volume Ultrasound (AVol/TVol) and Abdominal Circumference

Fetal weight prediction is a critical aspect of prenatal care, directly impacting maternal and child safety. Accurate estimation of fetal weight helps clinicians make informed decisions regarding delivery methods and manage potential complications such as macrosomia, which is defined as a birth weight exceeding 4000 grams. Macrosomia is associated with increased risks of shoulder dystocia, neonatal respiratory distress, cesarean section, postpartum hemorrhage, and vaginal tearing. Traditional methods of fetal weight estimation, primarily based on two-dimensional (2D) ultrasound measurements, often yield significant errors. This study explores the use of three-dimensional (3D) limb volume ultrasound combined with abdominal circumference (AC) measurements to establish a more accurate model for predicting fetal weight.

The study was conducted at the Beijing Obstetrics and Gynecology Hospital, Capital Medical University, between September 2017 and December 2018. A total of 211 single pregnant women aged 18 years and above, with gestational ages ranging from 28 to 42 weeks, were initially enrolled. Nine cases were excluded due to incomplete information or an interval of more than seven days between ultrasound examination and delivery. The remaining 202 participants were divided into a model group (134 cases, 70%) and a verification group (68 cases, 30%) using a mechanical sampling method.

The study employed a Samsung WS80A high-grade color Doppler ultrasound diagnostic instrument for both 2D and 3D ultrasound examinations. The upper arm volume (AVol) and thigh volume (TVol) of the fetuses were measured using the semi-automated 3D analysis package on the ultrasound system. The AC was measured using 2D ultrasound. The operator, who had over ten years of experience, underwent remote review training and standardized research procedures to ensure consistency in data acquisition and analysis.

The data collected included maternal characteristics such as age, body mass index (BMI), mode of delivery, and the presence of gestational diabetes or hypertension. Neonatal data, including gestational age at birth, sex, delivery style, body length, head circumference (HC), and birth weight, were also recorded. The birth weight was measured using a standard calibrated weighing scale.

The Pearson Chi-squared test was used to evaluate the linear relationship between limb volume (AVol and TVol) and fetal weight. The results showed strong linear correlations, with Pearson correlation coefficients of 0.866 for AC, 0.862 for AVol, and 0.910 for TVol. A multivariate regression analysis was performed on the model group data to establish a prediction model formula: Y = -481.965 + 12.194TVol + 15.358AVol + 67.998AC. The adjusted R-squared value of 0.868 indicated that the model accounted for 86.8% of the factors determining fetal weight.

The accuracy of the prediction model was evaluated using the verification group data and compared with traditional formulas, including Hadlock, Lee2009, and INTERGROWTH-21st. The predicted fetal weights from the model formula and traditional formulas were compared with the actual birth weights using paired t-tests and residual analysis. The results showed no significant difference between the predicted and actual birth weights (t = -1.015, P = 0.314). The residual analysis revealed that the model formula had a mean residual of 35,360.170, indicating better predictive efficiency compared to traditional formulas.

The study also evaluated the predictive value of limb volume and AC for macrosomia using receiver operating characteristic (ROC) curves. The area under the curve (AUC) for TVol, AVol, and AC were 0.923, 0.911, and 0.862, respectively. The sensitivity and specificity of TVol for predicting macrosomia were 81.5% and 87.4%, respectively, at a cut-off value of 100.95 cm³. For AVol, the sensitivity and specificity were 100% and 76%, respectively, at a cut-off value of 40.13 cm³. The model formula demonstrated superior predictive efficiency for macrosomia, with a sensitivity of 87.5% and specificity of 91.7%.

The findings of this study highlight the advantages of using 3D limb volume ultrasound combined with AC measurements for fetal weight prediction. The semi-automated 3D technique provides more accurate volume information compared to traditional 2D methods, which are often limited by irregular tissue morphology and measurement errors. The prediction model established in this study is simple, easy to understand, and highly accurate, making it a valuable tool for clinical practice.

However, the study has some limitations. The model was developed using data from a specific population, and its applicability to other populations, such as those with maternal obesity or twin pregnancies, needs further validation. Additionally, the study did not assess the model’s performance across different fetal weight classes (e.g., 4000 g), which could provide more detailed insights into its predictive accuracy.

In conclusion, the prediction model based on 3D limb volume ultrasound and AC measurements offers a highly accurate, sensitive, and specific method for estimating fetal weight. It outperforms traditional formulas, particularly in the diagnosis of macrosomia. The semi-automated 3D technique is efficient and reliable, making it a promising tool for improving prenatal care and clinical decision-making. Future research should focus on validating the model in broader populations and exploring its application in different clinical scenarios.

doi.org/10.1097/CM9.0000000000001413

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