Investigation of the Prediction of Individual Fetal Growth Trajectories Using a Mathematical Formula

Abstract

Fetal growth is a vital factor in assessing the well-being of both the fetus and the expectant mother, as deviations can lead to severe consequences during gestational period. While ultrasound and growth charts have improved fetal biometry assessment, they have limitations in predicting individual fetal growth and some growth models can be cumbersome to apply. This study employs a mathematical formula based on the square root dependence of fetal biometry parameters on gestational age to predict fetal growth trajectories. Data were collected from multiple sources, including medical centers and an online repository, encompassing fetal biometry parameters like Head Circumference, Biparietal Diameter, Abdominal Circumference, and Femur Length. The analysis revealed strong positive linear relationships between these parameters and gestational age, with high correlation coefficients consistently above 0.99. The mathematical formula consistently provided accurate predictions closely aligned with actual measurements. This research contributes significant insights into the applicability of a predictive model for fetal biometric parameters in prenatal care, particularly in terms of their potential for clinical practice. While the predictive model is effective for most gestational ages, it has limitations, especially for later gestational ages. The study recommends ongoing improvement, the use of larger datasets, and consideration of multiple growth factors to capture fetal growth complexities more accurately. Additionally, further research should focus on refining and investigating outliers and discrepancies in the predictive model.