Objectives:Reverse Potts shunt is a promising yet high-risk therapy for pediatric pulmonary arterial hypertension. Postoperative hemodynamics is critically influenced by shunt configuration but is difficult to predict. This study aimed to quantify the effects of shunt size and location on hemodynamics to guide surgical planning. Methods:Based on a patient-specific model, four postoperative models with two different shunt locations [left pulmonary artery (LPA)-descending aorta (DAO) and pulmonary artery bifurcation-aortic arch] and three conduit sizes (4, 5, and 6 mm) were created. The direct Potts shunt model was created by a direct side-to-side anastomosis between the LPA and DAO with a 6-mm circular opening. Quantitative parameters including the shunt ratio (SR), which was defined as the percentage of the shunt flow rates to the total pulmonary inflow rate, lower limb oxygen saturation, and pressure were analyzed. Results:Increasing the shunt size from 4 mm to 6 mm elevated the SR from 6.01% to 9.80%, concurrently reducing lower limb oxygen saturation from 89.57% to 86.52%. When taking 11,000 Pa as the threshold, this increased SR resulted in a reduction of the high-pressure area from 17.32% of the total pulmonary artery area to almost zero. Meanwhile, the high-pressure area on the aorta expanded from 8.72% of the total aortic area to 14.94%. These results indicated a reduction in the right ventricular afterload and an increase in the left ventricular afterload. Notably, a 6-mm shunt at the pulmonary artery bifurcation yielded a significantly larger SR than at the LPA (9.80% vs. 2.68%), which is attributed to a higher pressure gradient at the pulmonary artery bifurcation (1,201 Pa vs. 162 Pa). Conclusion:The shunt location had a greater impact on the SR than shunt size within the 4 mm-6 mm range in this specific case. A 6-mm shunt at the pulmonary artery bifurcation yielded a significantly larger SR than at the LPA, which is attributed to the higher preoperative pressure gradient at the bifurcation site. Left heart function is as critical as right heart function in maintaining pressure balance and determining outcomes, as the shunt flow increases the left ventricular afterload.

Organ-on-a-Chip (OOC) platforms are microfluidic systems that recreate key features of human organ physiology in vitro via controlled perfusion. Fluid mechanical stimuli strongly influence cell morphology and function, making this important for cardiovascular OOC applications exposed to pulsatile blood flow. However, many existing OOC devices employ relatively simple chamber geometries and steady inflow assumptions, which may cause non-uniform shear exposure to cells, create stagnant regions with prolonged residence time, and overlook the specific effects of pulsatile perfusion. Here, we used computational fluid dynamics (CFD) to investigate how chamber geometry and inflow conditions shape the near-wall flow environment on a cell culture surface at a matched cycle-averaged volumetric flow rate. Numerical results demonstrated that pillarized chambers markedly reduced relative residence time (RRT) versus the flat chamber, and the small pillar configuration produced the most uniform time-averaged wall shear stress (TAWSS) distribution among the tested designs. Phase-resolved analysis further showed that wall shear stress varies with waveform phase, indicating that steady inflow may not capture features of pulsatile perfusion. These findings provide practical guidance for pillar geometries and perfusion conditions to create more controlled and physiologically relevant microenvironments in OOC platforms, thus improving the reliability of cell experimental readouts.

Background:Currently, vascular hemodynamic analyses are typically conducted using commercial software. This process usually involves reconstructing the three-dimensional (3D) geometry of blood vessels, generating a computational mesh, and performing a computational fluid dynamics (CFD) analysis. It requires skilled medical personnel to manually process medical images, which is time consuming and prone to errors. This study aimed to develop a deep learning-based method to quickly and accurately extract vascular hemodynamic feature data to address these issues. This was accomplished by automating the processes of computed tomography (CT) image segmentation, vessel reconstruction, and CFD prediction. Methods:An improved convolutional neural network (CNN) was developed to automatically segment preprocessed vascular CT images. Additionally, a marching cubes (MC) algorithm was used to reconstruct the segmented images into a 3D model. The geometrical model was then meshed for hemodynamic simulation using OpenFOAM. Results:The proposed Res2Net-ConvFormer-Dilation-UNet (Res2-CD-UNet) model achieved the best results in both the lower-limb and aortic-artery datasets. In the aortic-artery dataset, it achieved an accuracy of 92.76%, which was 1.32% higher than that of the second-best model. In the lower-limb artery dataset, it achieved an accuracy of 94.57%, surpassing the second-best model by 1.12%. The maximum relative geometric error for the lower-limb arteries was only about 2.05%. The overall computational time for the process significantly decreased from several hours to a few minutes, substantially enhancing diagnostic efficiency. Conclusions:The method developed in this study facilitates the automated segmentation, 3D reconstruction, and CFD simulation of arterial regions in CT images. Our proposed method exhibits high accuracy, and enables the rapid and intuitive visualization of hemodynamic changes in the arteries.

The investigation of flow characteristics within the popliteal artery is fundamental to understanding the progression of lower limb arterial disease, given its high susceptibility to atherosclerosis and its frequent manifestation of stenosis. Research on the hemodynamics associated with popliteal artery stenosis remains limited, particularly in cardiovascular diseases. This study comprehensively examines how Newtonian and non-Newtonian fluid models influence the hemodynamic simulations of popliteal artery stenosis. Key hemodynamic parameters, such as velocity, time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT), were systematically examined through numerical simulations to assess their influence and variability in arteries exhibiting different degrees of stenosis compared to healthy arteries. The findings indicate that both models’ velocity and wall shear stress (WSS) distributions are largely comparable during the systolic phase (0.04–0.07 s), characterized by elevated velocities. However, during the countercurrent diastolic phase (0.21–0.40 s), the viscosity of the non-Newtonian fluid model experiences an increase, leading to reduced velocity distributions relative to the Newtonian fluid model. In particular, a 12% disparity in velocities is observed between the two models, indicating that the non-Newtonian model is better suited for comprehensive hemodynamic analysis in simulations involving stenotic popliteal arteries. Furthermore, a distinct flow separation occurs at the stenosis site, with blood flow velocity and WSS exhibiting significant increases as the stenosis severity escalates. For instances where hemodynamic parameters demonstrate minimal variations at stenosis levels below 60%, OSI and RRT are elevated. In contrast, TAWSS remains low, potentially fostering plaque formation. In contrast, when hemodynamic parameters undergo substantial changes at stenosis levels exceeding 60%, TAWSS rises, which may facilitate plaque rupture. This simulation provides a comprehensive analysis of hemodynamic parameter variations across different degrees of stenosis, offering clinicians a valuable instrument for enhancing their understanding of the pathogenic mechanisms associated with popliteal artery atherosclerosis and stenosis.

ABSTRACT:The complex pathogenesis of myocardial ischemia-reperfusion (I/R) injury is a major factor influencing clinical prognosis. It has been confirmed that microRNAs are involved in myocardial I/R injury, and that pyroptosis is closely associated with its underlying mechanisms. However, the specific mechanism by which miR-193b-3p inhibits cell death and alleviates myocardial I/R injury remains unclear. This study aimed to investigate whether miR-193b-3p can inhibit pyroptosis and protect injured myocardium by targeting the Gasdermin-D (GSDMD)/Nucleotide-binding oligomerization domain-like receptor thermal protein domain-associated protein 3 (NLRP3) signaling axis, thereby offering a potential therapeutic strategy for myocardial I/R injury. Through bioinformatics analysis, pyroptosis-related signaling pathways and key genes involved in myocardial I/R injury were identified. A myocardial I/R injury model was established, and pathological changes in myocardial tissue were evaluated using hematoxylin and eosin staining. A dual-luciferase reporter assay was conducted to verify the targeting relationship between miR-193b-3p and GSDMD. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western blotting were employed to detect mRNA and protein expression levels of miR-193b-3p, GSDMD, and NLRP3. The role of miR-193b-3p in myocardial I/R injury was comprehensively evaluated based on cardiac troponin I levels and the rate of myocardial pyroptosis. The findings confirmed that miR-193b-3p inhibited GSDMD expression, attenuated pathological changes in rat myocardium, downregulated NLRP3 and other pyroptosis-related proteins, and reduced both myocardial pyroptosis and serum cardiac troponin I levels.

Congenital heart disease is one of the most common diseases in children worldwide. Single ventricle congenital heart disease poses greater challenges to early diagnosis and accurate assessment due to its complex anatomical structure and unique pathological characteristics. To this end, a cascaded channel attention UNet (CAUNet) network with a channel attention mechanism for automatic segmentation of the left and right ventricles in cardiac CT images is proposed in this study, aiming at the complex anatomical structure and fuzzy boundaries of pediatric heart, to support the diagnosis and prognosis analysis of single ventricle heart disease. Compared with the traditional attention mechanism, the introduction of the channel attention mechanism can more fully capture the relationship between local and global features in the image, effectively improving the accuracy of cardiac CT image segmentation. In terms of model architecture, the designed cascaded CAUNet introduces the channel attention module in the two-stage refinement network by constructing an adaptive cascade segmentation framework; that is, the ventricular region is roughly segmented in the first stage, and the initial segmentation result is optimized in detail in the second stage. Through this two-stage segmentation strategy, the segmentation performance of the network is not only improved, but also shows strong robustness when dealing with single ventricle cases with irregular morphology. In order to verify the effectiveness of the method, an experiments on 4 real clinical data sets is conducted in this study. The experimental results show that under the premise of a small increase in computational complexity, the Dice similarity coefficient of the network proposed in this paper in the segmentation of 7 substructures of the heart, the left and right ventricles, and the pulmonary artery segmentation tasks is improved compared with the mainstream multi-organ segmentation network, proving the potential of channel attention in cardiac image segmentation applications. The obtained precise segmentation results provide accurate quantitative indicators for clinicians to assist in the diagnosis of single ventricle structural abnormalities, which has important application value.

Background Neonates with critical congenital heart disease (CCHD) often require early surgical intervention to survive.This study aimed to evaluate whether specialist pediatric cardiac transfer (SPCT) improves surgical outcomes in neonates with critical congenital heart disease (CCHD). Methods In this retrospective cohort study, we collected clinical data of neonates diagnosed with CCHD who were treated at the cardiac intensive care unit of Shanghai Children’s Medical Center between January 2019 and December 2022. Propensity score matching (PSM) was used to balance the SPCT and non-SPCT groups. The primary outcome was postoperative survival. Results This study included 357 neonates with CCHD. After propensity score matching (PSM), the SPCT group had significantly lower rates of inotropic drug use (57.3% vs. 77.5%, p = 0.004), unplanned emergency operations (29.2% vs. 53.9%, p = 0.001), and preoperative mortality (0% vs. 4.5%, p = 0.043) compared to the non-SPCT group. Additionally, overall survival was higher in the SPCT group (92.6% vs. 82.0%, p = 0.044). Postoperative mortality did not significantly differ between the groups (2.25% in the SPCT group vs. 7.87% in the non-SPCT group, p = 0.065). However, long-distance transport showed significantly lower overall mortality in the L-SPCT group compared to the L-N-SPCT group (2.67% vs. 12.5%, p = 0.049). Multivariate analysis revealed low body weight at surgery (hazard ratio [HR]: 0.444, 95% confidence interval [CI]: 0.273–0.711, p= 0.001), Non-SPCT long distance transport (HR: 4.608, 95% CI: 1.436–4.982, p =0.017)and unplanned emergency operation (HR: 5.227, 95% CI: 2.521–10.834, p < 0.001) as independent risk factors for surgical mortality in neonates with CCHD. Conclusions SPCT reduces the rate of unplanned emergency operations and increases overall survival in neonates with CCHD, particularly in long-distance transfers.

Background Plastic bronchitis (PB) can occur in patients who have undergone congenital heart surgery (CHS). This study aimed to investigate the clinical features of PB in children after CHS.Methods We conducted a retrospective cohort study using the electronic medical record system. The study population consisted of children diagnosed with PB after bronchoscopy in the cardiac intensive care unit after CHS from May 2016 to October 2021.Results A total of 68 children after CHS were finally included in the study (32 in the airway abnormalities group and 36 in the right ventricular dysfunction group). All children were examined and treated with fiberoptic bronchoscopy. Pathogens were detected in the bronchoalveolar lavage fluid of 41 children, including 32 cases in the airway abnormalities group and 9 cases in the right ventricular dysfunction group. All patients were treated with antibiotics, corticosteroids (intravenous or oral), and budesonide inhalation suspension. Children with right ventricular dysfunction underwent pharmacological treatment such as reducing pulmonary arterial pressure. Clinical symptoms improved in 64 children, two of whom were treated with veno-arterial extracorporeal membrane oxygenation (ECMO) due to recurrent PB and disease progression.Conclusions Children with airway abnormalities or right ventricular dysfunction after CHS should be alerted to the development of PB. Pharmacological treatment such as anti-infection, corticosteroids, or improvement of right ventricular function is the basis of PB treatment, while fiberoptic bronchoscopy is an essential tool for the diagnosis and treatment of PB. ECMO assistance is a vital salvage treatment for recurrent critically ill PB patients.

Background: The presence of noise in medical ultrasound images significantly degrades image quality and affects the accuracy of disease diagnosis. The convolutional neural network-denoising autoencoder (CNNDAE) model extracts feature information by stacking regularly sized kernels. This results in the loss of texture detail, the over -smoothing of the image, and a lack of generalizability for speckle noise. Methods: A lightweight attention denoise-convolutional neural network (LAD -CNN) is proposed in the present study. Two different lightweight attention blocks (i.e., the lightweight channel attention (LCA) block and the lightweight large -kernel attention (LLA) block are concatenated into the downsampling stage and the upsampling stage, respectively. A skip connection is included before the upsampling layer to alleviate the problem of gradient vanishing during backpropagation. The effectiveness of our model was evaluated using both subjective visual effects and objective evaluation metrics. Results: With the highest peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) values at all noise levels, the proposed model outperformed the other models. In the test of brachial plexus ultrasound images, the average PSNR of our model was 0.15 higher at low noise levels and 0.33 higher at high noise levels than the suboptimal model. In the test of fetal ultrasound images, the average PSNR of our model was 0.23 higher at low noise levels and 0.20 higher at high noise levels than the suboptimal model. The statistical analysis showed that the p values were less than 0.05, which indicated a statistically significant difference between our model and the other models. Conclusions: The results of this study suggest that the proposed LAD -CNN model is more efficient in denoising and preserving image details than both conventional denoising algorithms and existing deeplearning algorithms.

BACKGROUND:Osteoporosis (OP) is a prevalent disease associated with age, and one of the primary pathologies is the defect of osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs). This study aimed to elucidate whether Nuclear Receptor Binding SET Domain Protein 2 (NSD2) transcriptionally regulates osteogenic differentiation of BMSCs in osteoporosis. METHODS:Identification of human BMSCs (hBMSCs) in vitro was measured by flow cytometry. Osteogenesis of hBMSCs in vitro was measured by Alizarin Red and Alkaline Phosphatase staining. The protein levels of H3K36me1/2/3, NSD2, and Hoxa2 were measured by western blotting. The mRNA levels of NSD2, Runx2, and BSP were measured by qPCR. The role of NSD2 in the osteogenic differentiation of BMSCs was further identified by silencing NSD2 via shRNA or overexpression of NSD2 via lentivirus transfection. The interactions of NSD2, H3K36me2 and Hoxa2 were identified via chromatin immunoprecipitation (ChIP). Luciferase reporting analysis was employed to confirm that NSD2 regulated the transcriptional activity of Hoxa2. Ovariectomized (OVX) was performed on mice to construct osteoporosis (OP) model. Subsequently, the bone mass was assessed by micro computed tomography (micro-CT) scan. RESULTS:During the osteogenesis of OP-derived hBMSCs, the levels of NSD2 and H3K36me2 significantly increased in 14 days of osteogenic induction. Inhibition of NSD2 via shRNA increased the RUNX2 and BSP expression of hBMSCs, while overexpression of NSD2 decreased RUNX2 and BSP expression of hBMSCs. ChIP analysis indicated NSD2-mediated H3K36me2 reduced the osteogenic differentiation of hBMSCs by regulating the osteogenic inhibitor Hoxa2. Accordingly, inhibition of NSD2 in vivo via tail vein injection of LV-shNSD2 lentivirus greatly alleviated OVX-induced osteoporosis in mice. CONCLUSION:We demonstrated that NSD2 inhibited the osteogenic differentiation in hBMSCs by transcriptionally downregulating Hoxa2 via H3K36me2 dimethylation. Inhibition of NSD2 effectively attenuated bone loss in murine osteoporosis and NSD2 is a promising target for clinical treatment of osteoporosis.

Background and objective: Surgical correction of pulmonary artery stenosis (PAS) is essential to the prognosis of patients with tetralogy of Fallot (TOF). The double -patch method of pulmonary arterioplasty is usually applied in case of multiple stenosis in TOF patients' pulmonary artery (PA) and when PAS cannot be relieved by the singlepatch method. The surgical planning for the double -patch design remains challenging. The purpose of this study is to investigate the double -patch design with different angulations between the left pulmonary artery (LPA) and the right pulmonary artery (RPA), and to understand postoperative hemodynamic alterations by the application of computer -aided design (CAD) and computational fluid dynamics (CFD) techniques. Methods: The three-dimensional model of the PA was reconstructed based on preoperative computed tomography imaging data obtained from the patient with TOF. Three postoperative models with different designs of doublepatch were created by "virtual surgery" using the CAD technique. Double -Patch 120 Model was created with double patches implanted in the main pulmonary artery (MPA) and the PA bifurcation and without changing the spatial position of PA. The angulation between the LPA and the RPA was defined as theta, which equaled to 120 degrees in Pre -Operative Model and Double -Patch 120 Model. Based on Double -Patch 120 Model, Double -Patch 110 Model and Double -Patch 130 Model were generated with theta equaled to 110 degrees and 130 degrees, respectively. Combined with CFD, the differences of velocity streamlines, wall shear stress (WSS), flow distribution ratio (FDR), and energy loss (EL) were compared to analyze postoperative pulmonary flow characteristics. Results: The values of velocity and WSS decreased significantly after virtual surgery. Obvious vortices and swirling flows were observed downstream of the stenosis of RPA and LPA in Pre -Operative Model, while fewer vortices developed along the anterior wall of the expanded lumens of RPA, especially in Double -Patch 110 Model. With the relief of PAS, two relatively higher WSS regions were observed at the posterior walls of RPA and LPA. The maximum WSS values in these regions of Double -Patch 110 Model were lower than those in DoublePatch 120 Model and Double -Patch 130 Model. Furthermore, the FDRs were elevated and the ELs were greatly reduced. It was found that Double -Patch 110 Model with the angulation between the LPA and the RPA equaled to 110 degrees showed relatively better properties of hemodynamics than other models. Conclusions: The angulation between the LPA and the RPA is an important factor that should be integrated in the double -patch design for TOF repair. Virtual surgery based on patient -specific vascular model and computational hemodynamics can be used to provide assistance for individualized surgical planning of double -patch arterioplasty.

Systemic to pulmonary arterial shunt including modified central shunt (MCS) and modified Blalock-Taussig shunt (MBTS) are widely applied surgeries to increase pulmonary perfusion. It's crucial to ensure the pulmonary flow was well-controlled within a reasonable range, since both excessive and insufficient pulmonary perfusion leads to poor prognosis. The pulmonary flow could be well-controlled by selecting various shunt designs, e.g. shunt location and size. However, the hemodynamic performance of different designs is less explored under equivalent and reasonable pulmonary flow. Here, the individualized vascular model was reconstructed. To realize appropriate and equivalent pulmonary flow, three virtual surgeries including 4 mm left MBTS, 4 mm MCS, and 5 mm right MBTS were implemented using computer-aided design (CAD). The postoperative hemodynamic parameters were calculated by computational fluid dynamics (CFD). The results showed the postoperative models had equivalent pulmonary flow. The left MBTS had a better performance in balancing the pulmonary flow distribution. The right MBTS had a lower wall shear stress (WSS) and time-averaged WSS region in the shunt. The flow vortex and shear stress fluctuations were hardly avoidable in pulmonary arteries. In conclusion, the appropriate and equivalent pulmonary flow could be well realized by a larger-sized shunt when changing the shunt location of MBTS to the third aortic branch, compared with the MCS. The pulmonary flow distribution is greatly affected by the shunt location and vascular anatomy. The assessment and monitoring of thrombosis risk is requisite during perioperative management and postoperative follow-up no matter what shunt design is applied.

Venoarterial extracorporeal membrane oxygenation (VA-ECMO) has been extensively demonstrated as an effective means of bridge-to-destination in the treatment of patients with severe ventricular failure or cardiopulmonary failure. However, appropriate selection of candidates and management of patients during Extracorporeal membrane oxygenation (ECMO) support remain challenging in clinical practice, due partly to insufficient understanding of the complex influences of extracorporeal membrane oxygenation support on the native cardiovascular system. In addition, questions remain as to how central and peripheral venoarterial extracorporeal membrane oxygenation modalities differ with respect to their hemodynamic impact and effectiveness of compensatory oxygen supply to end-organs. In this work, we developed a computational model to quantitatively address the hemodynamic interaction between the extracorporeal membrane oxygenation and cardiovascular systems and associated gas transport. Model-based numerical simulations were performed for cardiovascular systems with severe cardiac or cardiopulmonary failure and supported by central or peripheral venoarterial extracorporeal membrane oxygenation. Obtained results revealed that: 1) central and peripheral venoarterial extracorporeal membrane oxygenation modalities had a comparable capacity for elevating arterial blood pressure and delivering oxygenated blood to important organs/tissues, but induced differential changes of blood flow waveforms in some arteries; 2) increasing the rotation speed of extracorporeal membrane oxygenation pump (ω) could effectively improve arterial blood oxygenation, with the efficiency being especially high when ω was low and cardiopulmonary failure was severe; 3) blood oxygen indices (i.e., oxygen saturation and partial pressure) monitored at the right radial artery could be taken as surrogates for diagnosing potential hypoxemia in other arteries irrespective of the modality of extracorporeal membrane oxygenation; and 4) Left ventricular (LV) overloading could occur when ω was high, but the threshold of ω for inducing clinically significant left ventricular overloading depended strongly on the residual cardiac function. In summary, the study demonstrated the differential hemodynamic influences while comparable oxygen delivery performance of the central and peripheral venoarterial extracorporeal membrane oxygenation modalities in the management of patients with severe cardiac or cardiopulmonary failure and elucidated how the status of arterial blood oxygenation and severity of left ventricular overloading change in response to variations in ω. These model-based findings may serve as theoretical references for guiding the application of venoarterial extracorporeal membrane oxygenation or interpreting in vivo measurements in clinical practice.

The accurate segmentation of the right and left ventricles with limited labeled data is a challenging task in echocardiographic data analysis. To fully leverage the easily accessible unlabeled data, we propose a label-decoupling teacher-student framework (LDTSF) based on semi-supervised learning. Specifically, the decoupled deep network within LDTSF jointly predicts pixel-wise segmentation maps, level set-based edge regression maps, target skeleton maps and target detail maps to focus on edge pixels. Several micro-task-transformable layers are used to map multi-task representations to a unified space in order to supervise the consistency among multiple tasks using massive unlabeled data. In addition, we first train a teacher model based on semi-supervised learning strategy, and then use the pseudo-labels generated by the teacher model together with the original labels to train a student model. Experiments on our self-collected 3D echocardiographic dataset and a publicly available MRI dataset show that our method outperforms state-of-the-art semi-supervised learning methods. The code will be available at: https://github.com/SwanKnightZJP/LDTSF.

The emergence of the medicine-engineering interdisciplinary technology research center can promote the transformation and application of engineering technology in clinical medicine. Focusing on the construction of virtual reality engineering technology research center for structural heart disease in Shanghai, this paper discussed the operation experience of the medicine-engineering interdisciplinary technology research center from the aspects of resource integration, research development, achievement transformation and talent cultivation, and put forward some suggestions such as in-depth integration of disciplines, improvement of achievement transformation mechanism, establishment of scientific research incentive mechanism and ethical guidelines, in order to create "production-study-research-medicine-teaching" five-in-one medicine-engineering interdisciplinary technology research center.

Segmentation of left and right ventricles from 3-D echocardiographic images is premised and key for the quantitative analysis of cardiac function, which is important for pediatric cardiac diagnosis. Compared with 2-D echocardiography, 3-D echocardiography can fully represent a ventricular structure without geometric inference. However, it usually takes experts several hours to obtain a 3-D segmentation mask of the left and right ventricles. Therefore, a fast and automatic segmentation method is highly desired. Unfortunately, 3-D echocardiography suffers from low contrast, unclear left and right ventricles borders, and blind zone. Existing segmentation methods usually have poor performance at ventricular boundaries. To deal with these problems, we propose a novel dual-branch TransV-Net (DBTV). DBTV comprises two parallel, interleaved, and relatively independent V-shaped encoder–decoder branches. The main branch acts on the original data to extract image features, and the auxiliary branch acts on edge maps to extract the additional edge features. To suppress noise and enhance the edge information, extra concatenations are added to bridge the features from the main and auxiliary branches. To reduce object missing caused by blind zone, a 3-D transformer-based module is proposed in the bottom layer of the dual-branch structure to extract the global contexts. We do experiments on a self-collected dataset with 120 3-D echocardiographic images from 60 cardiac sequences, and the dice scores of 0.913 and 0.880 are obtained in the left and right ventricle segments, respectively. Each inference takes about two-thirds of a second for a single 3-D frame.

In order to enhance the reconstruction of Tetralogy of Fallot (TOF) cardiovascular models and facilitate the development of individualized treatment strategies for clinical practitioners, this study employed the modeling outcomes from Materialise ® -Mimics as a reference point to investigate the modeling effectiveness of the existing automatic segmentation algorithm based on the U-Net model. We selected a single case and performed three-dimensional modeling using both the automatic segmentation algorithm and Mimics. Subsequently, we utilized Mimics to measure morphological parameters, including pulmonary artery diameter and angles, from the models generated by the two aforementioned methods, as well as from the two-dimensional images. The parameters acquired from the two-dimensional plane served as the standard reference. Discrepancies and relative errors between the parameters obtained from the two models and the reference values were calculated, while smaller discrepancies and parameter errors indicated greater model accuracy. Although the models generated through both methods exhibited substantial morphological similarity, the algorithmic models excluded image information at the juncture of the right ventricle and pulmonary artery. Furthermore, the data revealed that the discrepancies and relative errors in the algorithmic model's measurements were higher than those observed in the Mimics-generated models compared to the reference values. Consequently, it is inferred that the modeling efficacy of the automatic segmentation algorithm based on the U-Net model is promising, yet further model training is required to enhance modeling precision.

Background and objectives: A large proportion of infants with vallecular cyst (VC) have coexisting laryn-gomalacia (LM). Feeding difficulties, regurgitation, occasional cough, and sleep-disordered breathing are the common symptoms in moderate to severe cases. The surgical management of these cases is more challenging and remains controversial. The purpose of this study is to help surgeons select the effective surgical strategies by computer-aided design (CAD) and computational fluid dynamics (CFD) simulations of the upper airway flow characteristics.Methods: The three dimensional (3D) geometric model of the upper airway was reconstructed based on two dimensional (2D) medical images of the patient with VC accompanied with LM. Virtual surgeries were carried out preoperatively to simulate three possible post-operative states in silico. The different outcomes of virtual surgical strategies were predicted based on computational evaluations of airway fluid dynamics including pressure, resistance, velocity, and wall shear stress (WSS).Results: The CFD results of this study suggested the importance of the angle between the rim of epiglottis and arytenoid epiglottic (AE) fold. There was a small impact on the upper airway flow field while the VC was removed and the angle of epiglottis was unchanged. The partial lifting of epiglottis can further improve the flow field. With performing supraglottoplasty (SGP) and the marsupialization of VC, epiglottis was completely recovered, and the flow field was significantly improved. The clinical symptoms of this patient improved greatly after surgeries and no recurrence or growth retardation were noted during 1-year follow-up. The clinical prognosis was consistent with the prediction of the CFD results.Conclusions: The state of epiglottis needs to be carefully checked to evaluate the necessity of perform-ing further SGP in the patients with VC accompanied with LM. CFD and CAD could be developed as a new approach to help surgeons predict the post-operative outcomes through quantification of the air-flow dynamics, and make the optimal and individualized surgical approaches for patients with airway obstruction.(c) 2023 Elsevier B.V. All rights reserved.

Tetralogy of Fallot (TOF) is one of the commonest cyanotic congenital heart diseases, characterized by the highly variable anatomy of pulmonary artery (PA), location and degree of obstruction. Subtle alterations in the geometry of PAs would cause changes of pulmonary hemodynamics, which are closely associated with the outcome of TOF patients. Hence, it is critical to understand the geometric characteristics of PA in TOF patients. This study was conducted to explored the differences of tortuosity of PAs between TOF patients and children with normal PAs. And there were twenty TOF patients and ten individuals with normal PA. The three-dimensional geometries of PAs were constructed based on preoperative computed tomography data. The tortuosity of pulmonary arteries were quantitatively measured and statistically analyzed. It was found that there were no obvious differences in the tortuosity of right pulmonary artery (RPA) between TOF and control groups (1.07 ± 0.044 vs. 1.07 ± 0.029, P = 0.977). Nevertheless, the tortuosity of main pulmonary artery (MPA) (1.07 ± 0.012 vs. 1.11 ± 0.038, P < 0.0001) and the tortuosity of left pulmonary artery (LPA) (1.10±0.022 vs. 1.18±0.070, P = 0.001) were relatively higher in the TOF group compared with the control group. The positive correlation was found between the tortuosity of MPA and the tortuosity of LPA (r=0.618, P < 0.0001). The area under the curve (AUC) of the MPA tortuosity and the LPA tortuosity was 0.945 and 0.935, respectively. They exhibit both high sensitivity and specificity in the diagnosis of TOF. The cutoff value of the MPA tortuosity was 1.092, and that of the LPA tortuosity was 1.117. It revealed that increased tortuosity of MPA and LPA in TOF patients compared with those of normal subjects, which might provide guidance for the diagnostic evaluation and prognostic prediction of TOF patients.

Abstract Objective: To explore whether specialist pediatric cardiac transfer could improve the prognosis of neonates with critical congenital heart disease (CCHD). Methods: This cohort study retrospectively collected the clinical data of neonates diagnosed with CCHD who underwent treatment at the cardiac intensive care unit of Shanghai Children’s Medical Center between January 2018 and December 2021. The neonates were classified into the specialist pediatric cardiac transfer (SPCT) and non-SPCT groups. Propensity score matching (PSM) was used to match the two groups. The surgical outcome was the postoperative survival of the neonates. Results: During the study period, 357 neonates with CCHD were treated and included, of which 16 died before surgery, all in the non-SPCT group. After PSM, compared with the non-SPCT group, the SPCT group showed a lower rate of inotropic drug use (57.3% vs. 77.5%, P=0.004), a lower rate of unplanned emergent operation (29.2% vs. 53.9%, p=0.001), a higher total survival rate (92.1% vs. 82.0%, p =0.044), and a lower preoperative mortality rate (0% vs. 4.5%, p =0.043). The multivariable analysis showed that body weight at surgery (HR=0.444, 95%CI: 0.273-0.711, p=0.001) and unplanned emergent surgery (HR=5.227, 95%CI: 2.521-10.834, p<0.001) were independently associated with mortality in neonates with CCHD. Conclusion:Low body weight and unplanned emergency surgery are independent risk factors for the death of neonates with CCHD. Although SPCT is unrelated to the surgery mortality rate of newborns with CCHD, it can reduce the incidence of unplanned emergency surgery and increase the total survival rate.