Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, University of California Los Angeles, CA, USA.
Department of Urology, University of California Los Angeles, CA, USA.
Ultrasound Obstet Gynecol. 2021 May;57(5):798-803. doi: 10.1002/uog.22171.
To evaluate the accuracy of an automated three-dimensional (3D) ultrasound technique for fetal intracranial measurements compared with manual acquisition.
This was a prospective observational study of patients presenting for routine anatomical survey between 18 + 0 and 22 + 6 weeks' gestation. After providing informed consent, each patient underwent two consecutive ultrasound examinations of the fetal head, one by a sonographer and one by a physician. Each operator obtained manual measurements of the biparietal diameter (BPD), head circumference (HC), transcerebellar diameter (TCD), cisterna magna (CM) and posterior horn of the lateral ventricle (Vp), followed by automated measurements of these structures using an artificial intelligence-based tool, SonoCNS® Fetal Brain. Both operators repeated the automated approach until all five measurements were obtained in a single sweep, up to a maximum of three attempts. The accuracy of automated measurements was compared with that of manual measurements using intraclass correlation coefficients (ICC) by operator type, accounting for patient and ultrasound characteristics.
One hundred and forty-three women were enrolled in the study. Median body mass index was 24.0 kg/m (interquartile range (IQR), 22.5-26.8 kg/m ) and median subcutaneous thickness was 1.6 cm (IQR, 1.3-2.0 cm). Fifteen (10%) patients had at least one prior Cesarean delivery, 17 (12%) had other abdominal surgery and 78 (55%) had an anterior placenta. Successful acquisition of the automated measurements was achieved on the first, second and third attempts in 70%, 22% and 3% of patients, respectively, by sonographers and in 76%, 16% and 3% of cases, respectively, by physicians. The automated algorithm was not able to identify and measure all five structures correctly in six (4%) and seven (5%) patients scanned by the sonographers and physicians, respectively. The ICCs reflected good reliability (0.80-0.88) of the automated compared with the manual approach for BPD and HC and poor to moderate reliability (0.23-0.50) for TCD, CM and Vp. Fetal lie, head position, placental location, maternal subcutaneous thickness and prior Cesarean section were not associated with the success or accuracy of the automated technique.
Automated 3D ultrasound imaging of the fetal head using SonoCNS reliably identified and measured BPD and HC but was less consistent in accurately identifying and measuring TCD, CM and Vp. While these results are encouraging, further optimization of the automated technology is necessary prior to incorporation of the technique into routine sonographic protocols. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.
评估一种自动三维（3D）超声技术在胎儿颅内测量方面的准确性，与手动采集相比。
这是一项前瞻性观察性研究，纳入了 18 周+0 至 22 周+6 周妊娠期间进行常规解剖检查的患者。在提供知情同意后，每位患者都进行了两次连续的胎儿头部超声检查，一次由超声医师进行，一次由医生进行。每位操作者都获得了双顶间径（BPD）、头围（HC）、小脑横径（TCD）、脑池（CM）和侧脑室后角（Vp）的手动测量值，然后使用基于人工智能的工具 SonoCNS®胎儿大脑进行这些结构的自动测量。每位操作者重复自动方法，直到在单次扫描中获得所有五个测量值，最多尝试三次。通过操作者类型的组内相关系数（ICC）比较自动测量的准确性与手动测量的准确性，同时考虑了患者和超声特征。
本研究纳入了 143 名女性。中位数体重指数为 24.0kg/m（四分位距（IQR），22.5-26.8kg/m），中位数皮下厚度为 1.6cm（IQR，1.3-2.0cm）。15 名（10%）患者至少有一次剖宫产史，17 名（12%）有其他腹部手术史，78 名（55%）有前胎盘。超声医师在 70%、22%和 3%的患者中，在第一次、第二次和第三次尝试中成功获得了自动测量值，而在 76%、16%和 3%的病例中，医生成功获得了自动测量值。在 6 名（4%）和 7 名（5%）由超声医师和医生扫描的患者中，自动算法无法正确识别和测量所有五个结构。与手动方法相比，自动方法的 ICC 反映了 BPD 和 HC 的可靠性较好（0.80-0.88），而 TCD、CM 和 Vp 的可靠性较差到中等（0.23-0.50）。胎儿位置、头部位置、胎盘位置、母体皮下厚度和剖宫产史与自动技术的成功率或准确性无关。
使用 SonoCNS 的自动 3D 超声成像可可靠地识别和测量 BPD 和 HC，但在准确识别和测量 TCD、CM 和 Vp 方面的一致性较差。虽然这些结果令人鼓舞，但在将该技术纳入常规超声协议之前，需要进一步优化自动技术。©2020 年国际妇产科超声学会。
