Prediction of abortion using three-dimensional ultrasound volumetry of the gestational sac and the amniotic sac in threatened abortion

Automated prediction of early spontaneous miscarriage based on the analyzing ultrasonographic gestational sac imaging by the convolutional neural network: a case-control and cohort study

Background

It is challenging to predict the outcome of the pregnancy when fetal heart activity is detected in early pregnancy. However, an accurate prediction is of importance for obstetricians as it helps to provide appropriate consultancy and determine the frequency of ultrasound examinations. The purpose of this study was to investigate the role of the convolutional neural network (CNN) in the prediction of spontaneous miscarriage risk through the analysis of early ultrasound gestational sac images.

Methods

A total of 2196 ultrasound images from 1098 women with early singleton pregnancies of gestational age between 6 and 8 weeks were used for training a CNN for the prediction of the miscarriage in the retrospective study. The patients who had positive fetal cardiac activity on their first ultrasound but then experienced a miscarriage were enrolled. The control group was randomly selected in the same database from the fetuses confirmed to be normal during follow-up. Diagnostic performance of the algorithm was validated and tested in two separate test sets of 136 patients with 272 images, respectively. Performance in prediction of the miscarriage was compared between the CNN and the manual measurement of ultrasound characteristics in the prospective study.

Results

The accuracy of the predictive model was 80.32% and 78.1% in the retrospective and prospective study, respectively. The area under the receiver operating characteristic curve (AUC) for classification was 0.857 (95% confidence interval [CI], 0.793–0.922) in the retrospective study and 0.885 (95%CI, 0.846–0.925) in the prospective study, respectively. Correspondingly, the predictive power of the CNN was higher compared with manual ultrasound characteristics, for which the AUCs of the crown-rump length combined with fetal heart rate was 0.687 (95%CI, 0.587–0.775).

Conclusions

The CNN model showed high accuracy for predicting miscarriage through the analysis of early pregnancy ultrasound images and achieved better performance than that of manual measurement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-022-04936-0.

Sonographic Parameters for Prediction of Miscarriage: Role of 3-Dimensional Volume Measurement

OBJECTIVES

To evaluate the value of volume measurement using 3-dimensional sonography for prediction of miscarriage.

METHODS

We prospectively enrolled 188 singleton pregnant women at 5 to 9 weeks' gestation. The 3-dimensional sonographic gestational sac volume and yolk sac volume were measured together with the fetal heart rate, gestational sac diameter, and yolk sac diameter. For each sonographic parameter, nomograms were created; z scores were calculated for each measurement, and the values were compared between miscarriage and ongoing pregnancy groups. Sonographic parameters for prediction of miscarriage were evaluated by multivariate analysis, and the screening performance was assessed by a receiver operating characteristic curve.

RESULTS

Among the 188 pregnancies, 30 (16.0%) had miscarriage. Multivariate analysis showed that fetal heart rate below the 5th percentile (odds ratio, 6.43), gestational sac diameter below the 5th percentile (odds ratio, 4.87), gestational sac volume below the 5th percentile (odds ratio, 5.25), and yolk sac diameter below the 2.5th or above the 97.5th percentile (odds ratio, 15.86) were significant predictors of miscarriage (P = .018; P = .018; P = .033; and P < .001, respectively). At a false-positive rate of 30%, the detection rate for miscarriage in screening by a combination of fetal heart rate, gestational sac diameter, gestational sac volume, and yolk sac diameter was 77.8%.

CONCLUSIONS

A small-for-gestational-age gestational sac volume is a significant sonographic predictor of miscarriage, as are fetal bradycardia, a small gestational sac diameter, and a small or large yolk sac diameter.