Mack Lauren M, Kim Sung Yoon, Lee Sungmin, Sangi-Haghpeykar Haleh, Lee Wesley
Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, Texas, USA.
Samsung Medison Research and Development Center, Seoul, Korea.
J Ultrasound Med. 2017 Aug;36(8):1649-1655. doi: 10.7863/ultra.16.08087. Epub 2017 Apr 25.
Fetal soft tissue can be assessed by using fractional limb volume as a proxy for in utero nutritional status. We investigated automated fractional limb volume for rapid estimate fetal weight assessment.
Pregnant women were prospectively scanned for 2- and 3-dimensional fetal biometric measurements within 4 days of delivery. Performance of birth weight prediction models was compared: (1) Hadlock (Am J Obstet Gynecol 1985; 151:333-337; biparietal diameter, abdominal circumference, and femur diaphysis length); and (2) Lee (Ultrasound Obstet Gynecol 2009; 34:556-565; biparietal diameter, abdominal circumference, and automated fractional limb volume). Percent differences were calculated: [(estimated birth weight - actual birth weight) ÷ (actual birth weight] × 100. Systematic errors (accuracy) were summarized as signed mean percent differences. Random errors (precision) were calculated as ± 1 SD of percent differences.
Fifty neonates were delivered at 39.4 weeks' gestation. The Hadlock model generated the most accurate birth weight (0.31%) with a mean random error of ±7.9%. Despite systematic underestimations, the most precise results occurred with fractional arm volume (-9.1% ± 5.1%) and fractional thigh (-5.2% ± 5.2%) models. The size and distribution of these prediction errors were improved after correction for systematic errors.
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.
通过使用肢体体积分数作为子宫内营养状况的替代指标来评估胎儿软组织。我们研究了自动肢体体积分数以快速估计胎儿体重。
对孕妇在分娩前4天内进行前瞻性二维和三维胎儿生物测量扫描。比较出生体重预测模型的性能:(1)哈德洛克模型(《美国妇产科杂志》1985年;151:333 - 337;双顶径、腹围和股骨干长度);(2)李模型(《超声妇产科》2009年;34:556 - 565;双顶径、腹围和自动肢体体积分数)。计算百分比差异:[(估计出生体重 - 实际出生体重)÷(实际出生体重)]×100。系统误差(准确性)总结为有符号平均百分比差异。随机误差(精密度)计算为百分比差异的±1标准差。
50例新生儿在孕39.4周时分娩。哈德洛克模型得出的出生体重最准确(0.31%),平均随机误差为±7.9%。尽管存在系统性低估,但手臂体积分数(-9.1%±5.1%)和大腿体积分数(-5.2%±5.2%)模型得出的结果最精确。在校正系统误差后,这些预测误差的大小和分布得到了改善。
自动肢体体积分数测量可提高孕晚期胎儿体重预测的精度。当将自动肢体体积分数与基于手动描绘胎儿肢体软组织边界的预测模型一起使用时,可能需要校正因子来调整低估的系统误差。