In the extraction of fetal electrocardiogram (ECG) signal, due to the unicity of the scale of the U-Net same-level convolution encoder, the size and shape difference of the ECG characteristic wave between mother and fetus are ignored, and the time information of ECG signals is not used in the threshold learning process of the encoder’s residual shrinkage module. In this paper, a method of extracting fetal ECG signal based on multi-scale residual shrinkage U-Net model is proposed. First, the Inception and time domain attention were introduced into the residual shrinkage module to enhance the multi-scale feature extraction ability of the same level convolution encoder and the utilization of the time domain information of fetal ECG signal. In order to maintain more local details of ECG waveform, the maximum pooling in U-Net was replaced by Softpool. Finally, the decoder composed of the residual module and up-sampling gradually generated fetal ECG signals. In this paper, clinical ECG signals were used for experiments. The final results showed that compared with other fetal ECG extraction algorithms, the method proposed in this paper could extract clearer fetal ECG signals. The sensitivity, positive predictive value, and F1 scores in the 2013 competition data set reached 93.33%, 99.36%, and 96.09%, respectively, indicating that this method can effectively extract fetal ECG signals and has certain application values for perinatal fetal health monitoring.
OBJECTIVE To evaluate the clinical results of repair of bone defect by embryonic bone transplantation. METHODS From January 1994 to June 1999, 148 cases of bone defect were repaired by embryonic bone transplantation following alcohol treatment, there were 63 cases with bone cyst, 42 cases with fibrous dysplasia of bone, 26 cases with giant cell tumor of bone, and 17 cases with enchondroma among them. The maximal bone defect was 3.5 cm x 10.0 cm, while the minimal defect was 0.5 cm x 1.0 cm. RESULTS All of those bone defect with benign tumor were bone union used by embryonic bone transplantation after 3 months to 1 year of operation, the average healing course was 6.2 months, followed up 1 to 6 years, averaged 14 months, no tumor recurrence and no obvious local or system response were observed. CONCLUSION Embryonic bone can be used as a good repairing material of postoperative bone defect of benign tumors, the clinical results are satisfactory.
This review provides an overview of prenatal interventional treatments for fetal congenital heart disease (CHD), with a particular focus on the latest advancements in fetal aortic valvuloplasty (FAV) and fetal pulmonary valvuloplasty (FPV). FAV aims to improve left heart hemodynamics, prevent hypoplastic left heart syndrome (HLHS), and promote biventricular circulation. FPV seeks to improve the natural history of pulmonary atresia with intact ventricular septum (PA/IVS) and critical pulmonary stenosis with intact ventricular septum (CPS/IVS), alleviate right ventricular outflow tract obstruction, and promote biventricular circulation. This article discusses patient selection, technical details, risk assessment, and clinical outcomes for these procedures, highlighting the challenges in current research, including the lack of standardized patient selection criteria and long-term prognostic studies. Additionally, it emphasizes the opportunities and challenges of fetal cardiac intervention (FCI) development in China and proposes recommendations for future improvements and research directions.
Objective To search and review the best clinical evidence to direct the use of ultrasound. Methods After developing clinical questions, we searched the following databases for evidence: PROQUEST (1984 to 2004), SUMSEARCH (1980 to 2004) and The Cochrane Library (Issue 4, 2004). The key words were “repeated ultrasound exposure and children development (outcome)”. Results We found 3 systematic reviews, 3 randomized controlled trials, 1 cohort study and 1 case-control study. Most of the trials concluded that the effects of ultrasound to fetus were to be identified, some of the trials showed that ultrasound exposure could have an effect on fetus growth and language ability after delivery. Conclusions The pregnant women should avoid ultrasound as much as possible.
Objective To define an evidence-based conclusion concerning ultrasound screening for fetal genital system malformations during pregnancy. Methods In order to assess whether or not ultrasound screening for fetal genital system malformations is effective and feasible, we searched The Cochrane Library (Issue 3, 2009), MEDLINE (1981 to 2009), ACP Journal Club (1991 to 2008), and BMJ Clinical Evidence (1999 to 2008) for systematic reviews, randomized controlled trials (RCTs), cohort studies, and controlled clinical trials. Results Five cohort studies and three crosssectional studies were retrieved. The results showed ultrasound screening detected fetal sex determination by the contour of the rump and the angle of the genital tubercle to a horizontal line through the lumbosacral skin surface in the first trimester. Scrotal size and penile length increases with gestational age for male fetuses, and by 32 weeks, bilateral testicular descent was observed in most cases. Ultrasonographic scans, fetal genetic studies, and hormonal assays of amniotic fluid can diagnosis certain diseases, fetal sex differentiation disorders, fetal endocrinal disorders, and chromosome abnormality. Conclusion The findings of this study should reassure physicians and parents alike that ultrasound screening is an reliable option for the prenatal diagnosis of fetal genital system malformations, but more randomized controlled trials are needed to further supply relevant evidence.
Fetal electrocardiogram signal extraction is of great significance for perinatal fetal monitoring. In order to improve the prediction accuracy of fetal electrocardiogram signal, this paper proposes a fetal electrocardiogram signal extraction method (GA-LSTM) based on genetic algorithm (GA) optimization with long and short term memory (LSTM) network. Firstly, according to the characteristics of the mixed electrocardiogram signal of the maternal abdominal wall, the global search ability of the GA is used to optimize the number of hidden layer neurons, learning rate and training times of the LSTM network, and the optimal combination of parameters is calculated to make the network topology and the mother body match the characteristics of the mixed signals of the abdominal wall. Then, the LSTM network model is constructed using the optimal network parameters obtained by the GA, and the nonlinear transformation of the maternal chest electrocardiogram signals to the abdominal wall is estimated by the GA-LSTM network. Finally, using the non-linear transformation obtained from the maternal chest electrocardiogram signal and the GA-LSTM network model, the maternal electrocardiogram signal contained in the abdominal wall signal is estimated, and the estimated maternal electrocardiogram signal is subtracted from the mixed abdominal wall signal to obtain a pure fetal electrocardiogram signal. This article uses clinical electrocardiogram signals from two databases for experimental analysis. The final results show that compared with the traditional normalized minimum mean square error (NLMS), genetic algorithm-support vector machine method (GA-SVM) and LSTM network methods, the method proposed in this paper can extract a clearer fetal electrocardiogram signal, and its accuracy, sensitivity, accuracy and overall probability have been better improved. Therefore, the method could extract relatively pure fetal electrocardiogram signals, which has certain application value for perinatal fetal health monitoring.
OBJECTIVE: To explore the expression of basic fibroblast growth factor(bFGF) during the wound healing of human fetal and adult skin and its significance. METHODS: We established the animal model of fetal scarless healing by transplanting full-thickness skin grafts from human fetus to a subcutaneous location on the athymic mouse recipient, and then making the linear incisions. The expression of bFGF was observed in the normal adult skin, normal fetal skin and during wound healing by immunohistochemical method. The positive staining cells were counted under selected high-power focus randomly. RESULTS: bFGF staining was not observed in the normal fetal skin and the wounded one. However, bly positive staining was shown around the vessels in normal adult skin. Moreover, the positive straining became ber in the wounded skin, especially in dermal fibroblasts and endotheliocytes. The number of positive staining cell was 2.1 +/- 0.1 in normal fetal skin, and 2.2 +/- 0.1, 2.1 +/- 0.3, 2.1 +/- 0.3 and 2.0 +/- 0.1 in the fetal skins after 12 hours, 1 day, 3 days and 7 days of wound respectively. The number of positive staining cell were 23.2 +/- 4.2 in normal adult skin and 40.5 +/- 3.6 in the wound adult skin. There was significant difference between the fetal skin and adult skin (P lt; 0.01). CONCLUSION: The negative expression of bFGF in the fetal skin may be one of the important reasons for fetal scarless healing.
Fetal electrocardiogram (ECG) signals provide important clinical information for early diagnosis and intervention of fetal abnormalities. In this paper, we propose a new method for fetal ECG signal extraction and analysis. Firstly, an improved fast independent component analysis method and singular value decomposition algorithm are combined to extract high-quality fetal ECG signals and solve the waveform missing problem. Secondly, a novel convolutional neural network model is applied to identify the QRS complex waves of fetal ECG signals and effectively solve the waveform overlap problem. Finally, high quality extraction of fetal ECG signals and intelligent recognition of fetal QRS complex waves are achieved. The method proposed in this paper was validated with the data from the PhysioNet computing in cardiology challenge 2013 database of the Complex Physiological Signals Research Resource Network. The results show that the average sensitivity and positive prediction values of the extraction algorithm are 98.21% and 99.52%, respectively, and the average sensitivity and positive prediction values of the QRS complex waves recognition algorithm are 94.14% and 95.80%, respectively, which are better than those of other research results. In conclusion, the algorithm and model proposed in this paper have some practical significance and may provide a theoretical basis for clinical medical decision making in the future.