Use of Z-scores to select a fetal biometric reference curve

Abstract

Objective: Fetal biometric data are a major part of prenatal ultrasound screening in the general population. The aim of this study was to analyze the effect of choice of reference curve on the quality of screening for growth abnormalities, using a statistical tool based on Z-scores.

Methods: The biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC) and femur length (FL) were measured in 9699 ultrasound scans during the second trimester (20-24 weeks of gestation) and 8100 scans during the third trimester (30-34 weeks of gestation). These biometric data were all transformed retrospectively into Z-scores, calculated using five reference curves: those published by Snijders and Nicolaides (1994), Chitty et al. (1994), Kurmanavicius et al. (1999) and Salomon et al. (2006), and curves used at our ultrasound unit generated from a sample of the local population. The Z-score distribution was compared with the expected normal distribution by calculation of the mean and SD, and using the Kolmogorov-Smirnov test. The sensitivity and specificity of each reference curve were calculated to determine the capacity of these curves to identify fetuses with measurements < 5(th) percentile or > 95(th) percentile for each parameter.

Results: Most of the distribution curves determined from the Z-scores of the measurements taken differed significantly from a non-skewed standard normal curve (mean of 0 and SD of 1). In our population, the Chitty reference curves gave the best results for identifying fetuses with abnormal (< 5(th) percentile or > 95(th) percentile) BPD (sensitivity, 100%; specificity, 97.24%), HC (sensitivity, 96.07%; specificity, 98.89%) and FL (sensitivity, 96.46%; specificity, 98.80%). The best reference for AC was the Salomon curve (sensitivity, 72.25%; specificity, 99.64%).

Conclusions: Checking for good concordance between the study population and chosen reference data is a key initial step in quality control. Z-scores are a simple tool for evaluating the performance of each reference curve for a given population in order to optimize the sensitivity and specificity of screening for fetal growth abnormalities.