Fetal Weight Estimation Using Automated Fractional Limb Volume With 2‐Dimensional Size Parameters

Abstract

ObjectivesTo develop new fetal weight prediction models using automated fractional limb volume (FLV).MethodsA prospective multicenter study measured fetal biometry within 4 to 7 days of delivery. Three‐dimensional data acquisition included the automated FLV that was based on 50% of the humerus diaphysis (fractional arm volume [AVol]) or 50% of the femur diaphysis (fractional thigh volume [TVol]) length. A regression analysis provided population sample–specific coefficients to develop 4 weight estimation models. Estimated and actual birth weights (BWs) were compared for the mean percent difference ± standard deviation of the percent differences. Systematic errors were analyzed by the Student t test, and random errors were compared by the Pitman test.ResultsA total of 328 pregnancies were scanned before delivery (BW range, 825–5470 g). Only 71.3% to 72.6% of weight estimations were within 10% of actual BW using original published models by Hadlock et al (Am J Obstet Gynecol 1985; 151:333–337) and INTERGROWTH‐21st (Ultrasound Obstet Gynecol 2017; 49:478–486). All predictions were accurate by using sample‐specific model coefficients to minimize bias in making these comparisons (Hadlock, 0.4% ± 8.7%; INTERGROWTH‐21st, 0.5% ± 10.0%; AVol, 0.3% ± 7.4%; and TVol, 0.3% ± 8.0%). Both AVol‐ and TVol‐based models improved the percentage of correctly classified BW ±10% in 83.2% and 83.9% of cases, respectively, compared to the INTERGROWTH‐21st model (73.8%; P < .01). For BW of less than 2500 g, all models slightly overestimated BW (+2.0% to +3.1%). For BW of greater than 4000 g, AVol (–2.4% ± 6.5%) and TVol (–2.3% ± 6.9%) models) had weight predictions with small systematic errors that were not different from zero (P > .05). For these larger fetuses, both AVol and TVol models correctly classified BW (±10%) in 83.3% and 87.5% of cases compared to the others (Hadlock, 79.2%; INTERGROWTH‐21st, 70.8%) although these differences did not reach statistical significance.ConclusionsIn this cohort, the inclusion of automated FLV measurements with conventional 2‐dimensional biometry was generally associated with improved weight predictions.

Fetal Weight Estimation Using Automated Fractional Limb Volume With 2‐Dimensional Size Parameters in Diabetic Pregnancies

“…Weight estimates, from the inclusion of automated FLV measurements, were accurate and precise, with the greatest proportion of predictions within 10% of actual BW. These results were consistent with a prospective multicenter study of 328 pregnancies 14 . In that study, inclusion of automated FLV measurements improved the percentage of correctly classified BW ±10% in 83.2% (BPD, AC, and AVol) and 83.9% (BPD, AC, and TVol) of cases compared to the INTERGROWTH‐21st (73.8%; HC and AC) and Hadlock (78.7%; BPD, AC, and FDL) models.…”

“…In summary, the combination of automated FLV measurements with conventional 2D biometry was associated with improved weight predictions in this cohort of diabetic pregnancies. This work flow is quick, reproducible, and easy to implement in a clinic environment 12–14 . The relationship of specific body compositional changes (eg, fat versus lean mass) with maternal glucose control warrants additional investigations for different ethnic groups.…”

“…An automated software tool (5D Limb Vol; Samsung Medison Co, Ltd) was used as previously described (Figure 1). 14 Neonatal data collection included birth date, gestational age at delivery, BW, and sex.…”

“…Specific comparison formulas were partly selected by considering the best‐performing weight prediction models using 2D size parameters in diabetic pregnancies 20 . Our results were also compared to new weight estimation models that combined automated FLV with conventional 2D measurements 14 …”

“…However, the practical clinical application of the approach has been primarily limited by the time it takes to manually trace 5 transverse limb circumferences. Automated FLV measurements have been reported as efficient, reproducible, and accurate tools for fetal weight estimation 12–14 . We examined the utility of automated FLV software for EFW assessment in a cohort of diabetic pregnancies.…”