Individualized fetal growth assessment: critical evaluation of key concepts in the specification of third trimester size trajectories

Objectives: To characterize second and third trimester fetal growth using Individualized Growth Assessment methods in a larger cohort of fetuses with normal neonatal growth outcomes. Methods: A prospective longitudinal study of 119 pregnancies was performed from 18 weeks, MA, to delivery. Measurements of several 1D and 3D fetal size parameters were obtained from 3D volume data sets at 3-4 week intervals. Regression analyses were used to determine Start Points (SP) and Rossavik model (P = c {t} (k + st)) coefficients c, k and s for each parameter in each fetus. Second trimester growth velocity reference ranges were determined and size model specification functions re-established, the latter used to generate individual size models. Actual measurements were compared to predicted third trimester size trajectories using Percent Deviations. New age-specific reference ranges for the Percent Deviations of each parameter were defined using 2-level statistical modeling. Results: Rossavik models fit the data for all parameters very well (R-2: 99%), with SP's and k values similar to those found in much smaller cohorts. The c* values were strongly related to the second trimester slope (R-2: 97%), as was predicted s* to estimated c* (R-2: 54-95%). Rossavik models predicted third trimester growth with systematic errors close to 0%; random errors (95% range) ranged between 5.7 and 10.9% and 20.0 and 24.3% for 1D and 3D parameters, respectively. Conclusions: IGA procedures for evaluating second and third trimester growth are now established based on a larger cohort (4-6 fold larger). New, more rigorously defined, age-specific standards for the evaluation of third trimester size deviations are now available for nine anatomical parameters and a weight estimation procedure that incorporates a soft tissue parameter (fractional thigh volume). These results provide a means for more reliably assessing fetal growth on an individualized basis, thus minimizing the effect of biological differences in growth.