Congenital heart disease is the birth defect with the highest incidence in China. Its timely and accurate prenatal diagnosis is critical for appropriate perinatal and postnatal management and salvage treatment. With improvements in the diagnostic capabilities of ultrasound and clinical manipulation techniques, prenatal diagnosis is conducted increasingly early and with greater accuracy. However, the representations of tiny blood vessels and the determination of abnormal spatial structures in the fetal period continue to cause difficulties in prenatal diagnosis. In theory, spatio-temporal image correlation (STIC) technology is able to compensate for the defects of previous traditional two-dimensional (2D) ultrasound and improve the diagnostic accuracy. The aim of the present study was to investigate the clinical application value of STIC technology combined with traditional 2D ultrasound in the diagnosis of fetal cardiac abnormalities. A total of 1,286 fetuses were subjected to sequential echocardiographic examination, during which STIC technology was used to collect heart volume data and carry out image post-processing and off-line analysis. In addition, the prenatal and postnatal echocardiography results were compared with the pathology results following the induced labor of fetuses with cardiac abnormalities. The sensitivity, specificity, misdiagnosis rate and rate of missed diagnosis for the STIC technology in the diagnosis of prenatal fetal cardiac abnormalities were 97.4, 99.6, 0.4 and 2.6%, respectively. The total coincidence rate was 99.2% and the positive and negative predictive values were 97.9 and 99.4%, respectively; the statistics for the consistency check of the STIC technology in the diagnosis of fetal cardiac abnormalities are κ=0.991, P=0.000. STIC technology combined with fetal echocardiography may be used for the definite diagnosis of fetal heart malformations, with high sensitivity and specificity.
Keywords: fetal cardiac abnormality; fetal echocardiography; pathology; spatio-temporal image correlation technology.