Bi-parietal diameter measurement by ultrasound and its efficacy in estimating the gestational age

Objective: This research aimed to determine the efficacy of Bi-Parietal Diameter (BPD) by ultrasound in estimating the Gestational Age (GA) compared to GA by Naegele’s rule using Last menstrual period (LMP) date. Materials and Methods: This was a prospective observational study of women with a normal spontaneously conceived viable singleton pregnancy, a regular menstrual cycles, and spontaneous onset of labor at term. The LMP was considered certain in all cases. We used ultrasound to scan 2067 fetuses (894 healthy women) and we had 1586Bi-Parietal Diameter (BPD) measurements. Data were collected prospectively and used for statistical analysis. We used Descriptive Statistics to calculate the Mean, Standard Deviation (SD), Median and Percentiles values (3rd, 5th, 10th, 50th, 90th, 95th, and 97th) for BPD measurements on gestational age. We found a regression equation to estimate the GA using BPD measurements. The results of the current study were compared with different studies using the Paired Differences (t-test analysis). The results were represented as tables & diagrams. Results: The best-fit equation for the estimate of GA from BPD (in mm) was: = 7.567 + 0.236 (BPD)i – 1.02*10-4(BPD)i2 + 1.08*10-5 (BPD)i3 The Mean Sum of Squares of regression deviations of the GA regression model using (BPD) was 36939.5 and this value is significant at P <0.001. The standard error of the Estimate (Std.Error) and the standard deviation (SD) for the GA regression model (using BPD measurements) was 1.38 and (0.8, 1.1, 1.4, 1.6, 1.7) weeks when the GA were (12-18, 18-24, 24-30, 30-36, 36-42), respectively. Conclusion: In this study, we presented diagrams and tables for the estimation of GA using BPD measurements in a group of pregnant Syrian women. These results can be useful in women who cannot recall their last menstrual period (LMP). Our criteria will provide useful references for estimating gestational age and fetal care. A larger study might be needed to include a larger sample of the population.