Differential diagnosis of fetal large ventricular septal defect and tetralogy of Fallot based on big data analysis.

BACKGROUND AND OBJECTIVES: To analyze echocardiographic parameters of fetal large ventricular septal defect (VSD) and tetralogy of Fallot (TOF) in the context of multicenter data and big data analysis because these two diseases are often misdiagnosed in fetuses, and to find the key parameters for the differential diagnosis of these two diseases. METHODS: A total of 305 cases of large VSD and 192 cases of TOF diagnosed by fetal echocardiography from August 2010 to July 2016 from the database of Beijing Key Laboratory of Fetal Heart Defects were analyzed. Quantile regression of the 48 echocardiographic parameters of the 6272 normal fetuses from seven Chinese medical institutions was performed to determine the Q-score. The forward selection method and the naive Bayesian classification method were used to analyze the core differential diagnostic variables of fetal TOF and VSD. RESULTS: The Q-score of the internal diameter of the aorta (AO Q-score), the ratio of the diameter of the pulmonary artery to the internal diameter of the aorta (PA/AO), and the Q-score of the ratio of the diameter of the pulmonary artery to the internal diameter of the aorta (PA/AO Q-score) were key parameters for the differential diagnosis of fetal large VSD and TOF. PA/AO was the primary parameter, with an area under the receiver operating characteristic curve of 0.951. CONCLUSIONS: These findings provide a new method for the prenatal diagnosis of large VSD and TOF and a theoretical basis for the intelligent diagnosis of large VSD and TOF.