Ambroise Grandjean Gaëlle, Dap Matthieu, Ciofolo-Veit Cybele, Rouet Laurence, Damas Yohan, Banasiak Claire, Bourguignon Laurence, Collin Adeline, Morel Olivier, Hossu Gabriela
Obstetrics Department, Centre Hospitalier Régional Universitaire, Nancy, France.
Inserm, IADI, Université de Lorraine, Nancy, France.
Int J Gynaecol Obstet. 2025 Aug;170(2):647-655. doi: 10.1002/ijgo.70041. Epub 2025 Mar 18.
Detection algorithms targeting anatomic landmarks in three-dimensional (3D) ultrasound (US) volume (three-dimensional US) appear to be a relevant and easy-to-implement option to address junior and occasional operators' difficulties in probe positioning for two-dimensional (2D) fetal biometry.
This study assesses the feasibility of complete automation for fetal biometry and the resulting agreement with standard 2D (US) measurements. The secondary objectives were to assess the impact of software-driven measurement on image quality scoring, reproducibility, and agreement with human-driven measurements issued from the same volumes.
Datasets were collected from a consecutive sample of women attending standard US follow-up (singleton, 16-30 weeks of gestation). Each dataset contained 2D measurements for reference (head and abdomen circumference and femoral length) and 3D US volume acquisitions of the fetal head, abdomen, and thigh. Both algorithm-based and operator-based detection of the targeted plans and calipers positioning were applied to the 3D volumes to produce software-driven and human-driven measurements. The resulting 3D measurements were assessed for completion rates, image quality, and reproducibility.
On 175 datasets collected, completion rates in achieving software-driven 3D measurements ranged between 94% (abdomen) and 100% (head). A modest weakening in quality (of uncertain clinical significance) was notable for the head and abdomen measurements. Compared to the 2D measurements, the software-driven tended to slightly overestimate the estimated fetal weight (EFW; e.g., 95% confidence interval ranging from 445 to 635 g for a 525 g-sized fetus at 22 weeks of gestation). The random error tended to be inflated for fetuses >700 g. Intra- and inter-operator reproducibility were appropriate (intraclass correlation coefficient intervals ranged from 0.8 to 0.99).
Complete automation of US biometry appears feasible and presents appropriate reproducibility and image quality scoring, but third-trimester biometry needs improvement. Before clinical implementation, it is time to assess the impact of point-of-care use on large populations.
针对三维（3D）超声（US）容积中的解剖标志的检测算法似乎是一种切实可行且易于实施的选择，可解决初级和偶尔使用超声设备的操作人员在二维（2D）胎儿生物测量中探头定位的困难。
本研究评估胎儿生物测量完全自动化的可行性以及由此产生的测量结果与标准二维（US）测量结果的一致性。次要目的是评估软件驱动测量对图像质量评分、可重复性以及与来自相同容积的人工驱动测量结果一致性的影响。
从接受标准超声检查随访的连续样本女性（单胎妊娠，妊娠16 - 30周）中收集数据集。每个数据集包含用于参考的二维测量值（头围、腹围和股骨长度）以及胎儿头部、腹部和大腿的三维US容积采集数据。基于算法和人工的目标平面检测及卡尺定位均应用于三维容积数据，以生成软件驱动和人工驱动的测量结果。对由此产生的三维测量结果进行完成率、图像质量和可重复性评估。
在收集到的175个数据集中，实现软件驱动三维测量的完成率在94%（腹部）至100%（头部）之间。头部和腹部测量的质量有适度减弱（临床意义不确定）。与二维测量相比，软件驱动的测量往往会略微高估估计胎儿体重（EFW；例如，对于妊娠22周时体重为525g的胎儿，95%置信区间为445至635g）。对于体重>700g的胎儿，随机误差往往会增大。操作者内和操作者间的可重复性良好（组内相关系数区间为0.8至0.99）。
超声生物测量的完全自动化似乎可行，具有适当的可重复性和图像质量评分，但孕晚期生物测量需要改进。在临床应用之前，有必要评估床旁使用对大量人群的影响。
