Accessory mitral valve（AMV）refers to the additional valvular structural components connected to the normal mitral valve. It is a rare congenital cardiovascular malformation with an incidence of approximately 1/26 000. Most patients have no obvious symptoms and are often accidentally detected during echocardiography due to the presence of other associated cardiac malformations. The combination of AMV with left ventricular outflow tract（LVOT）vegetations is extremely rare and may be related to infective endocarditis. In this case，a 48-year-old male patient was discovered to have a "cardiac mass" during treatment for a cerebral infarction at an external hospital and was admitted to China-Japan Union Hospital of Jilin University for further diagnosis and treatment. Over the past 3 months，the patient experienced intermittent fever，accompanied by chest tightness and pain during physical exertion. The patient had a history of gout and diabetes. Transthoracic echocardiography（TTE）and transesophageal echocardiography revealed left ventricular outflow tract obstruction，accessory mitral valve（membranous fixed type），and a space-occupying lesion on the ventricular septal side within the left ventricular outflow tract. The final diagnosis of vegetation in the left ventricular outflow tract and accessory mitral valve was confirmed through surgical resection and postoperative pathology. Postoperative TTE showed a significant reduction in the flow velocity and pressure gradient within the left ventricular outflow tract. Echocardiography，with its advantages of simplicity，non-invasiveness，and repeatability，allows for the direct observation of accessory mitral valve and other cardiac abnormalities，evaluation of valve function and hemodynamic changes，and assessment of the left ventricular outflow tract obstruction condition. It facilitates preoperative diagnosis and postoperative follow-up，serving as the gold standard for diagnosing accessory mitral valve.

Objective:To assess the predictive performance of a nomogram model integrating endoscopic ultrasound（EUS）radiomic features with clinical variables for distinguishing early esophageal squamous cell carcinoma（ESCC）from non-cancerous lesions.Methods:Clinical and imaging data from 454 patients who underwent EUS for suspected esophageal malignancies were retrospectively collected in the First Affiliated Hospital of Nanjing Medical University（training cohort， n = 323）and Dongyang People's Hospital（external validation cohort， n = 131）from January 2020 to November 2023. Independent clinical predictors of early ESCC were identified using univariable and multivariable Logistic regression analyses to establish a clinical model. Pearson correlation and Least Absolute Shrinkage and Selection Operator（LASSO）algorithms were used to construct a radiomics model. A combined model integrating radiomics scores and clinical predictors was developed and visualized as a nomogram. The predictive performance of each model was assessed using the area under the ROC curve（AUC），and calibration curves were used to evaluate the model's fitting capability. Results:The training set and validation set indicated that there were statistically significant differences in age，smoking history and lesion location between the early ESCC group and the non-cancerous lesion change group（all P < 0.05）. According to univariate and multivariate Logistic regression analysis，age（ OR = 1.039，95% CI = 1.003–1.077， P = 0.036）and smoking（ OR = 2.358，95% CI = 1.270 - 4.376， P = 0.007）were identified as independent predictors and used to develop the clinical model，with AUCs of 0.608 and 0.694 in the training and validation cohorts，respectively. Fourteen optimal radiomic features were selected to construct the radiomics model，with AUCs of 0.881 and 0.807 in the training and validation cohorts，respectively. The combined nomogram model demonstrated superior predictive performance with AUCs of 0.893 and 0.830，sensitivities of 82.5% and 79.1%，and specificities of 82.2% and 81.3% in the training and validation cohorts，respectively. Conclusions:The EUS-based nomogram model demonstrates optimal predictive performance and can serve as a non-invasive tool to assist endoscopists in distinguishing early ESCC from non-cancerous lesions.

Objective:To analyze the relationship between the growth and development of pump twin and the changes of blood flow parameters and the natural pregnancy outcome of pump twin after pontaneous cessation of blood flow in the umbilical artery of the acardiac twin with reverse arterial perfusion sequence（TRAPs）detected by prenatal ultrasound.Methods:From January 2001 to August 2023，a total of 23 cases of TRAPs diagnosed in Hubei Maternal and Child Health Hospital were retrospectively collected and detected by ultrasound follow-up. According to the pregnancy outcome of the pump twin，23 patients were divided into the poor pregnancy outcome group（6 cases）and the good pregnancy outcome group（17 cases）. The changes of ultrasound growth indexes and blood flow parameters of the pump twin and acardia twin were compared between the two groups. The hemodynamic parameters with statistically significant differences between the two groups were selected，and the diagnostic efficacy for TRAPs pregnancy outcomes was analyzed using ROC analysis.Results:There were no statistically significant differences in the structural development of acardiac fetus between the two groups，including skin edema，hemicardia，skull structure，trunk structure，upper and lower limbs，cardiothoracic ratio，amniotic fluid，sex and amniotic nature of twins（all P > 0.05）. The lower limbs of acardia twin was significantly higher in the poor pregnancy outcome group（6/6）than in the good pregnancy outcome group（7/17），and the difference was statistically significant（ P < 0.05）. The relevant parameters of ultrasound blood flow were shown in both groups，there were no significant differences in middle cerebral artery pulsation index（PI）and umbilical artery PI between the two groups before natural occlusion of fetal blood flow with TRAPs（all P > 0.05）. In the good pregnancy outcome group，the ratio of umbilical cord diameter between pump twin and acardia twin was higher than that in the poor pregnancy outcome group，the difference was statistically significant（ P < 0.05）. The scatter plot of the ratio of umbilical diameter between the two groups was drawn，and the cut-off value was 2.125 through ROC curve analysis，the area under the curve（AUC）was 0.961，the sensitivity was 94.10%，the specificity was 100%，and the Yoden index was 0.94. Conclusions:The ratio of umbilical cord diameter between pump twin and acardia twin in TRAPs is significant for predicting the pregnancy outcome of pump twin.

Although thyroid nodules are less common in children than in adults，some benign nodules enlarge with age，causing symptoms or aesthetic concerns. Preserving thyroid function is crucial due to its role in children's growth and development. Thermal ablation，a safe and minimally invasive technique，offers a new option for treating benign thyroid nodules in children. This article reviewed the indications，methods，outcomes，and complication management of thermal ablation，in order to provide a reference for clinical practice.

Fetal sacrococcygeal teratoma（SCT）is a rare condition，but the prognosis of fetuses diagnosed with SCT prenatally is generally poor，with a mortality rate of 13% to 50%. The primary causes of death include fetal hydrops and high?output heart failure，while other causes include tumor rupture，hemorrhage，preterm labor，dystocia，or malignant teratoma invasion of surrounding tissues. For large tumors，especially those with rich blood supply or rapid growth，intrauterine treatment should be considered to prevent arteriovenous shunting，reduce tumor size，and reverse fetal heart failure and hydrops. This approach aims to allow the fetus to grow safely to a viable gestational age，after which the tumor can be completely removed by secondary surgery following cesarean delivery or natural childbirth. Currently，there are five main intrauterine treatment strategies：①Ultrasound?guided cystic teratoma aspiration：single or multiple aspirations，intrauterine continuous drainage，or prenatal aspiration；②Ultrasound?guided alcohol sclerotherapy；③Open fetal surgery；④Laser ablation：fetoscopic?guided ablation of feeding vessels of the teratoma，or ultrasound?guided laser ablation；⑤ Ultrasound?guided radiofrequency ablation（RFA）.According to the literature，the latter two minimally invasive intrauterine treatment methods show better outcomes for teratomas containing solid components and are gradually becoming the mainstream treatment options.

Objective:To develop an artificial intelligence system using fully convolutional neural networks（FCN）to assist echocardiographers in the quantitative assessment of mitral regurgitation（MR）severity.Methods:From August 2021 to June 2024，echocardiographic images of 441 patients with MR were prospectively collected from Renmin Hospital of Wuhan University and the Central Hospital of Wuhan. After screening，a total of 269 patients（4 917 frames）were included in the study. Of these，3 644 frames（128 patients）of apical four-chamber color Doppler MR flow convergence images from Renmin Hospital of Wuhan University were selected as the training/validation set，while images from 121 patients（813 frames）were used as the internal test set. Additionally，images from 20 patients（460 frames）from the Central Hospital of Wuhan were selected as the external test set. The FCN algorithm was employed to capture features and segment the MR color region on the left atrial side，simultaneously outputting the regurgitant radius（r）for the calculation of the effective regurgitant orifice area and regurgitant volume. The severity of MR was then classified according to the 2017 guidelines of the American Society of Echocardiography. The segmentation and classification performance of the model was evaluated，and the measurement results of the AI system was compared with that of both senior and junior physicians.Results:In the internal test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.48，0.81，0.86，and 0.87，respectively. In the external test set，the accuracy of r identification for cases classified as Grade Ⅰ to Ⅳ was 0.60，0.77，0.64，and 0.77，respectively. The average accuracy of MR classification in the internal and external test sets was 0.91 and 0.88，respectively.Conclusions:The FCN model is capable of segmenting the left atrial side regurgitant areas in apical four-chamber heart color Doppler images，aiding physicians in obtaining quantitative assessment parameters for MR，and assisting junior physicians in accurately assessing the severity of MR.

Omental torsion represents a rare cause of acute abdomen，current literatures predominantly limited to case reports focusing on greater omentum torsion，by contrast，lesser omentum torsion is exceedingly uncommon. One case of male patient aged 8 years and 7 months with epigastric pain was admitted to the Children's Hospital of Zhejiang University School of Medicine. Initial abdominal ultrasound suggested omental pathology. To confirm the diagnosis，repeat ultrasonography and contrast-enhanced CT were performed，leading to a preliminary suspicion of greater omentum torsion. Following multidisciplinary collaborative consultation，surgical intervention was recommended. The patient underwent laparoscopic omentectomy with adhesiolysis，which intraoperatively confirmed lesser omentum torsion. Histopathological examination provided definitive diagnostic confirmation.Postoperative abdominal ultrasound revealed no significant abnormalities. This case underscored the critical value of dynamic multimodal imaging evaluation and multidisciplinary decision-making in the preoperative diagnosis and therapeutic management of lesser omentum torsion，aiming to establish ultrasonographic diagnostic references for lesser omentum torsion while simultaneously heightening clinical vigilance toward rare diseases.

Object:To explore the feasibility of using artificial intelligence for quality control of echocardiographic images.Methods:Retrospectively，5 000 two-dimensional echocardiographic video images within the period from 2021 to 2023 were randomly retrieved from the echocardiography database of Nanjing Drum Tower Hospital，Affiliated Hospital of Medical School，Nanjing University. Among these selected images，1 559 of them were apical views. The physician team formulated the scoring rules，which specifically included four scoring criteria：gain，scaling ratio，cardiac axis angle，and structure. Subsequently，the data were labeled with view classification and image quality scores. The labeled data were further partitioned into the training set（ n = 643），the validation set（ n = 276），and the test set（ n = 640）. The training and validation sets were utilized for constructing the models for view classification and quality assessment，while the test set was employed to verify the models' effectiveness. The view classification module was implemented using the SlowFast model，and the quality assessment module involved algorithms such as ResNet，Video Swin Transformer，SSD，and U-Net. Results:The average accuracy，precision，recall rate and F1 score of the classification model in identifying each apical view were 0.987 1，0.983 0，0.987 1 and 0.984 9 respectively，and the inference time was（333.4 ± 105.4）ms. The average accuracies of the quality assessment module in terms of gain，scaling ratio，cardiac axis angle and display of main structures were 0.915 1，0.928 2，0.938 7 and 0.965 6 respectively，and the overall scoring accuracy was 0.912 7.Conclusions:The echocardiogram quality control system developed in this research can effectively classify and evaluate the quality of two-dimensional images of the apical views in echocardiograms. Moreover，it guarantees the objectivity，timeliness and high-efficiency of quality control，which has reference value for the establishment of the echocardiogram quality control system.

Objective:To evaluate the lung ultrasound characteristics of mycoplasma pneumoniae pneumonia in children and to investigate the value of lung ultrasound monitoring in clinical diagnosis and treatment.Methods:A retrospective analysis of 62 children with mycoplasma pneumoniae pneumonia admitted to Xi'an Chest Hospital from 7 November to 30 November 2023 was performed，and the characteristic parameters of bedside lung ultrasound and their related clinical data were collected. Pathological lung ultrasound features such as interrupted pleural line，well-spaced B-lines，coalescent B-lines，small subpleural patchy pulmonary consolidation，large pulmonary consolidation and pleural effusion in 12 scan areas of both lungs were observed. The maximum upper and lower diameters，right and left diameters，and anterior and posterior diameters of the large pulmonary consolidations were measured，and the changes in the above signs before and after treatment were measured and compared.Results:In sixty-two children with mycoplasma pneumoniae pneumonia，including 32 males and 30 females，with a mean age of（8.18 ± 2.05）years old and a mean hospital stay of（8.79 ± 2.93）days，lung ultrasound showed interrupted pleural line，well-spaced B-lines，coalescent B-lines，small subpleural patchy pulmonary consolidation，large pulmonary consolidation and pleural effusion，with the incidence of 93.5%（58 /62），33.9%（21/62），32.3%（20/62），59.7%（37/62），66.1%（41/62）and 17.7%（11/62），respectively，in which the large pulmonary consolidations presented rich blood supply were more common in the L6 and L4 areas，while the pleural effusions were more common in the L6 area.The signs of interrupted pleural line，coalescent B-lines，large pulmonary consolidation and pleural effusion were significantly improved after treatment compared with before treatment（all P<0.05）. The upper and lower diameters，left and right diameters，and anterior and posterior diameters of large pulmonary consolidations were significantly reduced after treatment compared with before treatment［（4.19 ± 2.42）cm vs.（2.84 ± 2.31）cm， t=2.613， P=0.011；（2.80 ± 1.82）cm vs.（1.96 ± 1.62）cm， t=2.226， P=0.029；（3.41 ± 2.11）cm vs.（2.12 ± 1.82）cm， t=2.972， P=0.004］.With the process of treatment，the dynamic observation of lung ultrasound showed that the well-spaced B-lines/coalescent B-lines gradually decreased until they completely disappeared or a small number of B-lines remained，and the area of the large pulmonary consolidation showed a dynamic downward trend（all P<0.001），and the area of large pulmonary consolidations gradually decreased until they completely disappeared or only small subpleural patchy pulmonary consolidations and well-spaced/coalescent B-lines remained，and at the same time，the pleural effusion gradually absorbed until it disappeared. Conclusions:Lung ultrasound can detect the distribution area of lung lesions，morphology and blood supply characteristics of children with mycoplasma pneumoniae pneumonia，as well as the dynamic changes after treatment，and lung ultrasound can dynamically monitor and evaluate the progression and regression of the disease in real time，providing a reliable imaging evidence for clinical practice.

Objective:To assess the value of artificial intelligence（AI）assisted system in the diagnosis of malignancy in follicular thyroid tumours，and to compare with the diagnostic results of doctors with different levels of experience.Methods:A total of 101 nodules were retrospectively collected from 86 patients with follicular thyroid tumours who underwent surgical treatment at Peking Union Medical College Hospital，Chinese Academy of Medical Sciences，Peking Union Medical College from May 2016 to January 2018.The nodules were classified into risk group（29 patients，34 nodules，including 15 follicular carcinomas and 19 follicular tumours of indeterminable malignant potential）and benign group（59 atients，67 nodules，including 15 follicular adenomas and 52 nodular goitre adenomatoid hyperplasia）. The sensitivities，specificities and accuracies of the AI system，two doctors of different seniorities（one junior A and one senior B），and guidelines of thyroid ultrasound malignancy risk stratification［including the 2015 American Thyroid Guidelines（ATA），the 2017 American College of Radiology Thyroid Imaging Reporting and Data System（ACR TI-RADS），the 2020 Chinese Society of Ultrasound，Thyroid Imaging Reporting and Data System（C-TIRADS）］（classified by a senior doctor C）for diagnosing follicular tumours in the risk group and follicular carcinomas were calculated and compared.Results:The AI system showed a sensitivity of 46.7%，specificity of 89.6% and accuracy of 81.7% for diagnosing follicular carcinoma；and a sensitivity of 32.4%，specificity of 89.6% and accuracy of 70.3% for diagnosing follicular neoplasms（risk group）. Compared with junior doctor A，the specificity of AI system in diagnosing follicular cancer and follicular neoplasms（risk group）was higher（89.6% vs. 83.6%， P=0.020；89.6% vs. 73.1%， P=0.020），and the differences of sensitivity were not significant（46.7% vs. 32.4%， P=0.181；32.4% vs. 11.8%， P=0.073）. The difference of sensitivity and specificity were not statistically significant between the AI system and senior doctor B（all P＞0.05）.The differences in area under the curve for diagnosis of follicular carcinoma and follicular tumour（risk group）were not statistically significant between the AI system compared to junior doctor A，senior doctor B，the C-TIRADS，ATA guideline，and ACR TI-RADS（all P＞0.05）. Conclusions:Ultrasound-based AI-assisted diagnostic system is similarly efficient in diagnosing follicular thyroid tumours as experienced doctors，and the AI system diagnostic specificity is superior to that of junior doctors.