Objective: To analysis the clinical characteristics of 400 fetuses with heart defects and the impactors of pregnancy decision making, and explore the influence of a multi-disciplinary team (MDT) cooperation approach on it. Methods: Clinical data of 400 fetuses with abnormal cardiac structure diagnosed at Peking University First Hospital from January 2012 to June 2021 were collected, which were divided into 4 groups according to the characteristics of fetal heart defects and the presence of extracardiac abnormalities or not: single cardiac defects without extracardiac abnormalities (122 cases), multiple cardiac defects without extracardiac abnormalities (100 cases), single cardiac defects with extracardiac abnormalities (115 cases), and multiple cardiac defects with extracardiac abnormalities (63 cases). The types of fetal cardiac structural abnormalities and genetic test results, and the detection rate of pathogenic genetic abnormalities, MDT consultation and management situation, and pregnancy decision of fetuses in each group were retrospectively analyzed. A logistics regression was used to analyze the influencing factors of fetal heart defects pregnancy decision. Results: (1) Among the 400 fetal heart defects, the four most common major types were ventricular septal defect 96 (24.0%, 96/400), tetralogy of Fallot 52 (13.0%, 52/400), coarctation of the aorta 34 (8.5%, 34/400), and atrioventricular septal defect 26 (6.5%, 26/400). (2) Among the 204 fetuses undergoing genetic examination, 44 (21.6%, 44/204) pathogenic genetic abnormalities were detected. (3) Detection rate of pathogenic genetic abnormalities (39.3%, 24/61) and pregnancy termination rate (86.1%, 99/115) in the single cardiac defects with extracardiac abnormalities group were significantly higher than those in the single cardiac defects without extracardiac abnormalities group [15.1% (8/53), 44.3% (54/122), respectively] and the multiple cardiac defects without extracardiac abnormalities group [6.1% (3/49), 70.0% (70/100), respectively, both P<0.05], and the pregnancy termination rate in the multiple cardiac defects without extracardiac abnormalities group and the multiple cardiac defects with extracardiac abnormalities group (82.5%,52/63) were significantly higher than that of the single cardiac abnormalities without extracardiac abnormalities group (both P<0.05). (4) After adjusting for age, gravity, parity and performed prenatal diagnosis, maternal age, the diagnosis of gestational age, prognosis grades, co-existence of extracardiac abnormalities, presence of pathogenic genetic abnormalities, and receiving MDT consultation and management were still independent influencing factors of termination of pregnancy of fetuses with cardiac defects (all P<0.05). A total of 29 (7.2%, 29/400) fetal cardiac defects received MDT consultation and management, and compared with those without MDT management, the pregnancy termination rate in the multiple cardiac defects without extracardiac abnormalities group [74.2%(66/89) vs 4/11] and the multiple cardiac defects with extracardiac abnormalities group [87.9%(51/58) vs 1/5] were lower, the differences were statistically significant respectively (all P<0.05). Conclusions: Maternal age, diagnosed gestational age, severity of cardiac defects, extracardiac abnormalities, pathogenic genetic abnormalities and MDT counseling and management are the influencing factors of fetal heart defects pregnancy decision. MDT cooperation approach influences pregnancy decision-making and should be recommended for the management of fetal cardiac defect to reduce unnecessary termination of pregnancy and improve pregnancy outcomes.
Pregnancy ; Female ; Humans ; Retrospective Studies ; Fetal Diseases/diagnosis* ; Heart Defects, Congenital/therapy* ; Fetus ; Decision Making ; Ultrasonography, Prenatal/methods*

Objective: To investigate the representability and etiological diagnostic value of myocardium samples obtained from patients with hypertrophic cardiomyopathy (HCM) by transthoracic echocardiography-guided percutaneous intramyocardial septal biopsy (myocardial biopsy of Liwen procedure). Methods: This study was a retrospective case-series analysis. Patients with HCM, who underwent myocardial biopsy of Liwen procedure and radiofrequency ablation in Xijing Hospital, Air Force Military Medical University from July to December 2019, were included. Demographic data (age, sex), echocardiographic data and complications were collected through electronic medical record system. The histological and echocardiographic features, pathological characteristics of the biopsied myocardium of the patients were analyzed. Results: A total of 21 patients (aged (51.2±14.5) years and 13 males (61.9%)) were enrolled. The thickness of ventricular septum was (23.3±4.5)mm and the left ventricular outflow tract gradient was (78.8±42.6)mmHg (1 mmHg=0.133 kPa). Eight patients (38.1%) were complicated with hypertension, 1 patient (4.8%) had diabetes, and 2 patients (9.5%) had atrial fibrillation. Hematoxylin-eosin staining of myocardial samples of HCM patients before radiofrequency ablation evidenced myocytes hypertrophy, myocytes disarray, nuclear hyperchromatism, hypertrophy, atypia, coronary microvessel abnormalities, adipocyte infiltration, inflammatory cell infiltration, cytoplasmic vacuoles, lipofuscin deposition. Interstitial fibrosis and replacement fibrosis were detected in Masson stained biopsy samples. Hematoxylin-eosin staining of myocardial samples of HCM patients after radiofrequency ablation showed significantly reduced myocytes, cracked nuclear in myocytes, coagulative necrosis, border disappearance and nuclear fragmentation. Quantitative analysis of myocardial specimens of HCM patients before radiofrequency ablation showed that there were 9 cases (42.9%) with mild myocardial hypertrophy and 12 cases (57.1%) with severe myocardial hypertrophy. Mild, moderate and severe fibrosis were 5 (23.8%), 9 (42.9%) and 7 (33.3%), respectively. Six cases (28.6%) had myocytes disarray. There were 11 cases (52.4%) of coronary microvessel abnormalities, 4 cases (19.0%) of adipocyte infiltration, 2 cases (9.5%) of inflammatory cell infiltration,6 cases (28.5%) of cytoplasmic vacuole, 16 cases (76.2%) of lipofuscin deposition. The diameter of cardiac myocytes was (25.2±2.8)μm, and the percentage of collagen fiber area was 5.2%(3.0%, 14.6%). One patient had severe replacement fibrosis in the myocardium, with a fibrotic area of 67.0%. The rest of the patients had interstitial fibrosis. The myocardial specimens of 13 patients were examined by transmission electron microscopy. All showed increased myofibrils, and 9 cases had disorder of myofibrils. All patients had irregular shape of myocardial nucleus, partial depression, mild mitochondrial swelling, fracture and reduction of mitochondrial crest, and local aggregation of myofibrillary interfascicles. One patient had hypertrophy of cardiomyocytes, but the arrangement of muscle fibers was roughly normal. There were vacuoles in the cytoplasm, and Periodic acid-Schiff staining was positive. Transmission electron microscopy showed large range of glycogen deposition in the cytoplasm, with occasional double membrane surround, which was highly indicative of glycogen storage disease. No deposition of glycolipid substance in lysozyme was observed under transmission electron microscope in all myocardial specimens, which could basically eliminate Fabry disease. No apple green substance was found under polarized light after Congo red staining, which could basically exclude cardiac amyloidosis. Conclusion: Myocardium biopsied samples obtained by Liwen procedure of HCM patients are representative and helpful for the etiological diagnosis of HCM.
Biopsy/adverse effects* ; Cardiomegaly/pathology* ; Cardiomyopathy, Hypertrophic/diagnosis* ; Eosine Yellowish-(YS) ; Fibrosis ; Heart Defects, Congenital ; Hematoxylin ; Humans ; Lipofuscin ; Male ; Myocardium/pathology* ; Retrospective Studies

Heart sound analysis is significant for early diagnosis of congenital heart disease. A novel method of heart sound classification was proposed in this paper, in which the traditional mel frequency cepstral coefficient (MFCC) method was improved by using the Fisher discriminant half raised-sine function (F-HRSF) and an integrated decision network was used as classifier. It does not rely on segmentation of the cardiac cycle. Firstly, the heart sound signals were framed and windowed. Then, the features of heart sounds were extracted by using improved MFCC, in which the F-HRSF was used to weight sub-band components of MFCC according to the Fisher discriminant ratio of each sub-band component and the raised half sine function. Three classification networks, convolutional neural network (CNN), long and short-term memory network (LSTM), and gated recurrent unit (GRU) were combined as integrated decision network. Finally, the two-category classification results were obtained through the majority voting algorithm. An accuracy of 92.15%, sensitivity of 91.43%, specificity of 92.83%, corrected accuracy of 92.01%, and F score of 92.13% were achieved using the novel signal processing techniques. It shows that the algorithm has great potential in early diagnosis of congenital heart disease.
Humans ; Heart Sounds ; Algorithms ; Neural Networks, Computer ; Heart Defects, Congenital/diagnosis* ; Signal Processing, Computer-Assisted

Automatic classification of heart sounds plays an important role in the early diagnosis of congenital heart disease. A kind of heart sound classification algorithms based on sub-band envelope feature and convolution neural network was proposed in this paper, which did not need to segment the heart sounds according to cardiac cycle accurately. Firstly, the heart sound signal was divided into some frames. Then, the frame level heart sound signal was filtered with Gammatone filter bank to obtain the sub-band signals. Next, the sub-band envelope was extracted by Hilbert transform. After that, the sub-band envelope was stacked into a feature map. Finally, type Ⅰ and type Ⅱ convolution neural network were selected as classifier. The result shown that the sub-band envelope feature was better in type Ⅰ than type Ⅱ. The algorithm is tested with 1 000 heart sound samples. The test results show that the overall performance of the algorithm proposed in this paper is significantly improved compared with other similar algorithms, which provides a new method for automatic classification of congenital heart disease, and speeds up the process of automatic classification of heart sounds applied to the actual screening.
Algorithms ; Heart ; Heart Defects, Congenital/diagnosis* ; Heart Sounds ; Humans ; Neural Networks, Computer ; Signal Processing, Computer-Assisted

OBJECTIVES: To explore the method and significance of prenatal counseling in cardiac surgery for fetal congenital heart disease (CHD). METHODS: The prenatal counseling should be provided by experienced CHD experts. The preliminary clinical diagnosis based on relevant data was carried out, the prognosis risk for fetal CHD was graded, and the pathophysiological process and potential hazards of the disease were analyzed. The current condition of CHD in the treatment plan, the long-term quality of life, and the special requirements of parturition in place, period and mode were described. A reliable follow-up system of the fetuses was established, the diagnosis after delivery was verified, and surgical treatment was carried out timely. RESULTS: From January 2016 to December 2018, 225 parents with fetal CHD received prenatal counseling, including 60 fetuses (26.7%) with simple CHD and 165 (73.3%) with complex CHD, among which 59 cases (98.3%) and 93 cases (56.4%) decided to continue the pregnancy, respectively. During the follow-up, 118 fetuses were born, of which 66 infants received surgical treatment within 6 months after birth, 63 infants (95.5%) recovered and 3 infants (4.5%) died. The rest 52 infants continued to be followed up. CONCLUSIONS The prenatal counseling for fetal CHD can provide the parents a comprehensive medical information about CHD, which is beneficial to making appropriate pregnancy decisions, and can turn the fetuses from unreasonable birth and passive treatment to selective birth and active treatment in CHD.
Cardiac Surgical Procedures ; Counseling ; Female ; Fetus ; Heart Defects, Congenital ; surgery ; Humans ; Pregnancy ; Prenatal Diagnosis ; Quality of Life ; Ultrasonography, Prenatal

diagnosis, treatment planning, and post-therapeutic monitoring of patients with congenital heart disease. More interactive and realistic medical experiences take advantage of advanced visualization techniques like augmented, mixed, and virtual reality. Further, 3D printing is now used in medicine. All these technologies improve the understanding of the complex morphologies of congenital heart disease. In this review article, we describe the technical advantages and disadvantages of various advanced visualization techniques and their medical applications in the field of congenital heart disease. In addition, unresolved issues and future perspectives of these evolving techniques are described.]]>
Diagnosis ; Heart Defects, Congenital ; Humans ; Image Processing, Computer-Assisted ; Imaging, Three-Dimensional ; Printing, Three-Dimensional

Heart Defects, Congenital/diagnosis* ; Humans ; Hypertension ; MicroRNAs/genetics* ; Pulmonary Arterial Hypertension ; Pulmonary Artery/diagnostic imaging*

The electronic stethoscope combined with artificial intelligence (AI) technology has realized the digital acquisition of heart sounds and intelligent identification of congenital heart disease, which provides objective basis for heart sound auscultation and improves the accuracy of congenital heart disease diagnosis. At the present stage, the AI based cardiac auscultation technique mainly focuses on the research of AI algorithms, and the researchers have designed and summarized a variety of effective algorithms based on the characteristics of cardiac audio data, among which the mel-frequency cepstral coefficients (MFCC) is the most effective one, and widely used in the cardiac auscultation. However, the current cardiac sound analysis techniques are based on specific data sets, and have not been validated in clinic, so the performance of algorithms need to be further verified. The lack of heart sound data, especially the high-quality, standardized, publicly available heart sound database with disease labeling, further restricts the development of heart sound diagnostic analysis and its application in screening. Therefore, expert consensus is necessary in establishing an authoritative heart sound database and standardizing the heart sound auscultation screening process for congenital heart disease. This paper provides an overview of the research and application status of auscultation algorithm and hardware equipment based on AI in auscultation screening of congenital heart disease, and puts forward the problems to be solved in clinical application of AI auscultation screening technology.
Algorithms ; Artificial Intelligence ; Heart Auscultation/trends* ; Heart Defects, Congenital/diagnosis* ; Humans ; Mass Screening/methods*

Cardiac auscultation is the basic way for primary diagnosis and screening of congenital heart disease(CHD). A new classification algorithm of CHD based on convolution neural network was proposed for analysis and classification of CHD heart sounds in this work. The algorithm was based on the clinically collected diagnosed CHD heart sound signal. Firstly the heart sound signal preprocessing algorithm was used to extract and organize the Mel Cepstral Coefficient (MFSC) of the heart sound signal in the one-dimensional time domain and turn it into a two-dimensional feature sample. Secondly, 1 000 feature samples were used to train and optimize the convolutional neural network, and the training results with the accuracy of 0.896 and the loss value of 0.25 were obtained by using the Adam optimizer. Finally, 200 samples were tested with convolution neural network, and the results showed that the accuracy was up to 0.895, the sensitivity was 0.910, and the specificity was 0.880. Compared with other algorithms, the proposed algorithm has improved accuracy and specificity. It proves that the proposed method effectively improves the robustness and accuracy of heart sound classification and is expected to be applied to machine-assisted auscultation.
Algorithms ; Heart Defects, Congenital ; diagnosis ; Heart Sounds ; Humans ; Neural Networks (Computer) ; Sensitivity and Specificity

Shone complex is a rare congenital disorder that involves 4 obstructive lesions of the left heart, as follows: parachute mitral valve, supravalvular mitral ring, subaortic stenosis, and coarctation of the aorta. Incomplete forms with 2 or 3 of these lesions in adult patients have been rarely reported in the literature, meaning that insufficient general data exist concerning the surgical strategy and clinical follow-up. Herein, we report the case of a 31-year-old woman with a diagnosis of incomplete form of Shone complex with parachute mitral valve and coarctation of the aorta who underwent successful single-stage surgical repair.
Adult ; Aortic Coarctation ; Congenital, Hereditary, and Neonatal Diseases and Abnormalities ; Constriction, Pathologic ; Diagnosis ; Female ; Follow-Up Studies ; Heart ; Heart Defects, Congenital ; Humans ; Mitral Valve