Department of Obstetrics, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, 213004 Jiangsu, China.
Department of Ultrasound, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, 213004 Jiangsu, China.
Comput Math Methods Med. 2022 May 19;2022:7451185. doi: 10.1155/2022/7451185. eCollection 2022.
The empirical wavelet transform (EWT) algorithm was applied in ultrasound to explore the predictive value for fetal growth restriction (FGR) in fetal arteriovenous indexes. 142 pregnant women who received prenatal ultrasonic examination and delivered were selected. They were classified into control group and FGR group. There were 102 patients with normal pregnancy in the control group, and 40 patients with delayed fetal growth in the FGR group. The extended triple collocation (ETC) algorithm was employed to divide the Fourier spectrum of signals adaptively, and the constructed small filter banks were classified into corresponding intervals. The instantaneous frequency was analyzed, and the arterial blood flow indexes of the two groups were compared. The results showed that the time-frequency analysis method under EWT had lower normalization error and higher accuracy. The inner diameter and cross-sectional area of FGR were remarkably smaller than those of the control group, and the differences were statistically significant ( < 0.05). There were no significant differences in mean blood flow and mean blood velocity between the control group and FGR group ( > 0.05). The arterial blood flow parameters of the systolic flow velocity (VS) and the diastolic flow velocity (VD) in the FGR group were notably lower than those in the control group, and the differences were significant ( < 0.05). In conclusion, the frequency principal component extracted by EWT algorithm was less disturbed by noise, which could accurately and effectively evaluate fetal arteriovenous blood flow indexes and predict FGR.
经验模态分解（EWT）算法在超声中应用于探讨胎儿生长受限（FGR）的预测价值，对胎儿动静脉指标进行分析。选择 142 例接受产前超声检查并分娩的孕妇，分为对照组和 FGR 组。对照组 102 例为正常妊娠，FGR 组 40 例为胎儿生长迟缓。采用扩展三重配置（ETC）算法自适应地对信号的傅里叶频谱进行划分，将构建的小滤波器组分类到相应的区间。分析瞬时频率，比较两组的动脉血流指标。结果表明，EWT 下的时频分析方法具有较低的归一化误差和较高的精度。FGR 的内径和截面积显著小于对照组，差异有统计学意义（<0.05）。对照组和 FGR 组的平均血流量和平均血流速度差异无统计学意义（>0.05）。FGR 组的收缩期血流速度（VS）和舒张期血流速度（VD）的动脉血流参数明显低于对照组，差异有统计学意义（<0.05）。结论：EWT 算法提取的频率主成分受噪声干扰较小，能准确有效地评估胎儿动静脉血流指标，预测 FGR。
