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.

Automated fractional limb volume measurements can improve the precision of weight predictions in third-trimester fetuses. Correction factors may be necessary to adjust underestimated systematic errors when using automated fractional limb volume with prediction models that are based on manual tracing of fetal limb soft tissue borders.

Visualization of nuchal septations during first-trimester genetic screening is a powerful risk factor for chromosomal anomalies, independent of increased NT.

The purpose of this study was to document the reproducibility and efficiency of a semiautomated image analysis tool that rapidly provides fetal fractional limb volume measurements. Fifty pregnant women underwent 3-dimensional sonographic examinations for fractional arm and thigh volumes at a mean menstrual age of 31.3 weeks. Manual and semiautomated fractional limb volume measurements were calculated, with the semiautomated measurements calculated by novel software (5D Limb Vol; Samsung Medison, Seoul, Korea). The software applies an image transformation method based on the major axis length, minor axis length, and limb center coordinates. A transformed image is used to perform a global optimization technique for determination of an optimal limb soft tissue boundary. Bland-Altman analysis defined bias with 95% limits of agreement (LOA) between methods, and timing differences between manual versus automated methods were compared by a paired t test. Bland-Altman analysis indicated an acceptable bias with 95% LOA between the manual and semiautomated methods: mean arm volume ± SD, 1.7% ± 4.6% (95% LOA, -7.3% to 10.7%); and mean thigh volume, 0.0% ± 3.8% (95% LOA, -7.5% to 7.5%). The computer-assisted software completed measurements about 5 times faster compared to manual tracings. In conclusion, semiautomated fractional limb volume measurements are significantly faster to calculate when compared to a manual procedure. These results are reproducible and are likely to reduce operator dependency. The addition of computer-assisted fractional limb volume to standard biometry may improve the precision of estimated fetal weight by adding a soft tissue component to the weight estimation process.