Objectives: To evaluate the accuracy of an automated three-dimensional (3D) ultrasound technique for fetal intracranial measurements compared with manual acquisition.
Methods: 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.
Results: One hundred and forty-three women were enrolled in the study. Median body mass index was 24.0 kg/m2 (interquartile range (IQR), 22.5-26.8 kg/m2 ) 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.
Conclusions: 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.
Keywords: artificial intelligence; automated ultrasound; computer-aided analysis; fetal brain; three-dimensional sonography.
© 2020 International Society of Ultrasound in Obstetrics and Gynecology.