Extracorporeal membrane oxygenation (ECMO), as an extracorporeal life support technology, can provide respiratory support and hemodynamic support according to different modes. The significant advantages of ECMO in the treatment of acute respiratory distress syndrome and the development of its oxygenator, pump, and heparin-coated circuits have promoted its application and exploration in thoracic surgery. ECMO can be used during the perioperative period of lung transplantation and can be applied for patients who cannot maintain one-lung ventilation, or have a high risk of anesthesia, or undergo complex thoracic surgery involving trachea, carina, mediastinum and esophagus. This article will review the application and progress of ECMO in general thoracic surgery.

Remarkable results have been realized by the U-Net network in the task of medical image segmentation. In recent years, many scholars have been researching the network and expanding its structure, such as improvement of encoder and decoder and improvement of skip connection. Based on the optimization of U-Net structure and its medical image segmentation techniques, this paper elucidates in the following: First, the paper elaborates on the application of U-Net in the field of medical image segmentation; Then, the paper summarizes the seven improvement mechanism of U-Net: dense connection mechanism, residual connection mechanism, multi-scale mechanism, ensemble mechanism, dilated mechanism, attention mechanism, and transformer mechanism; Finally, the paper states the ideas and methods on the U-Net structure improvement in a bid to provide a reference for later researches, which plays a significant part in advancing U-Net.
Image Processing, Computer-Assisted/methods*

Lung cancer is the leading cause of cancer-related deaths worldwide, especially non-small cell lung cancer (NSCLC). With the popularization of low-dose CT and the improvement of people’s awareness of physical examinations, the number of detected pulmonary nodules is gradually increasing, and there is a greater demand for standardized diagnostic and treatment guidelines. On April 23, 2024, the National Comprehensive Cancer Network updated its clinical practice guidelines for NSCLC to the version 5. Compared with the version 5 in 2023, the version 5 in 2024 updates focus on diagnostic evaluation, perioperative systemic therapy, treatment of advanced NSCLC, and molecular marker testing, which will be interpreted in this article with the aim of providing the latest guidance and reference for the diagnosis and treatment of lung cancer in China.

Objective     To analyze the etiologies, surgical treatment and outcomes of retrograde type A aortic dissection (RTAD) after thoracic endovascular aortic repair (TEVAR) for Stanford type B aortic dissection. Methods     The clinical data of patients with RTAD after TEVAR for Stanford type B aortic dissection receiving operations in Changhai Hospital from March 2014 to August 2018 were analyzed. All patients were followed-up by clinic interview or telephone. Results     A total of 16 patients were enrolled, including 13 males and 3 females with a mean age of 49.1±12.2 years. The main symptoms of RTAD were chest pain in 12 patients, headache in 1 patient, conscious disturbance in 1 patient, and asymptomatic in 2 patients. All the 16 patients received total arch replacement with the frozen elephant trunk technique. Bentall procedure was used in 2 patients, aortic root plasticity in 10 patients and aortic valve replacement in 1 patient. The primary tear in 10 patients was located in the area which were anchored by bare mental stent, and in the other 6 patients it was located in the anterior part of ascending aorta. The mean cardiopulmonary bypass time was 152.2±29.4 min, aortic cross-clamping time was 93.6±27.8 min and selective cerebral perfusion time was 29.8±8.3 min. There was no death in hospital or within postoperative 30 days. The follow-up period was 32-85 (57.4±18.3) months. No death occurred during the follow-up period. One patient underwent TEVAR again 3 years after this operation and had an uneventful survival. Conclusion     Total arch replacement with the frozen elephant trunk technique is a suitable strategy for the management of RTAD after TEVAR for Stanford type B aortic dissection.

At present, fatigue state monitoring of upper limb movement generally relies solely on surface electromyographic signal (sEMG) to identify and classify fatigue, resulting in unstable results and certain limitations. This paper introduces the sEMG signal recognition and motion capture technology into the fatigue state monitoring process and proposes a fatigue analysis method combining an improved EMG fatigue threshold algorithm and biomechanical analysis. In this study, the right upper limb load elbow flexion test was used to simultaneously collect the biceps brachii sEMG signal and upper limb motion capture data, and at the same time the Borg Fatigue Subjective and Self-awareness Scale were used to record the fatigue feelings of the subjects. Then, the fatigue analysis method combining the EMG fatigue threshold algorithm and the biomechanical analysis was combined with four single types: mean power frequency (MPF), spectral moments ratio (SMR), fuzzy approximate entropy (fApEn) and Lempel-Ziv complexity (LZC). The test results of the evaluation index fatigue evaluation method were compared. The test results show that the method in this paper has a recognition rate of 98.6% for the overall fatigue state and 97%, 100%, and 99% for the three states of ease, transition and fatigue, which are more advantageous than other methods. The research results of this paper prove that the method in this paper can effectively prevent secondary injury caused by overtraining during upper limb exercises, and is of great significance for fatigue monitoring.
Electromyography/methods* ; Fatigue ; Humans ; Muscle Fatigue ; Muscle, Skeletal ; Upper Extremity

To solve the problems of small one-time ablation range and easy charring of the tissue around the electrode associated with the tumor radiofrequency ablation needle, based on the multiphysical field coupling analysis software COMSOL, the effects of needle material, the number of sub needles and the bending angle of sub needles on the ablation effect of radiofrequency ablation electrode needle were studied. The results show that compared with titanium alloy and stainless steel, nickel titanium alloy has better radiofrequency energy transmission efficiency and it is the best material for electrode needle. The number of sub needles has a great influence on the average necrosis depth and the maximum necrosis diameter. Under the same conditions, the more the number of sub needles, the larger the volume of coagulation necrosis area. The bending angle of the needle has a great effect on the maximum diameter of the coagulated necrotic area, but has little effect on the average necrotic depth. Under the same other conditions, the coagulation necrosis area formed by ablation increased with the increase of the bending angle of the sub needle. For the three needles with bending angles of 60 °, 90 ° and 120 ° analyzed in this paper, the one with bending angle of 120 ° can obtain the largest coagulation necrosis area. In general, the design of nickel titanium alloy with 120 ° bending 8-pin is the optimal. The average depth of radiofrequency ablation necrosis area is 32.40 mm, and the maximum necrosis diameter is 52.65 mm. The above optimized design parameters can provide guidance for the structure and material design of tumor radiofrequency ablation needle.
Humans ; Needles ; Temperature ; Catheter Ablation/methods* ; Necrosis ; Neoplasms/surgery* ; Alloys

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. Neuroimaging based on magnetic resonance imaging (MRI) is one of the most intuitive and reliable methods to perform AD screening and diagnosis. Clinical head MRI detection generates multimodal image data, and to solve the problem of multimodal MRI processing and information fusion, this paper proposes a structural and functional MRI feature extraction and fusion method based on generalized convolutional neural networks (gCNN). The method includes a three-dimensional residual U-shaped network based on hybrid attention mechanism (3D HA-ResUNet) for feature representation and classification for structural MRI, and a U-shaped graph convolutional neural network (U-GCN) for node feature representation and classification of brain functional networks for functional MRI. Based on the fusion of the two types of image features, the optimal feature subset is selected based on discrete binary particle swarm optimization, and the prediction results are output by a machine learning classifier. The validation results of multimodal dataset from the AD Neuroimaging Initiative (ADNI) open-source database show that the proposed models have superior performance in their respective data domains. The gCNN framework combines the advantages of these two models and further improves the performance of the methods using single-modal MRI, improving the classification accuracy and sensitivity by 5.56% and 11.11%, respectively. In conclusion, the gCNN-based multimodal MRI classification method proposed in this paper can provide a technical basis for the auxiliary diagnosis of Alzheimer's disease.
Humans ; Alzheimer Disease/diagnostic imaging* ; Neurodegenerative Diseases ; Magnetic Resonance Imaging/methods* ; Neural Networks, Computer ; Neuroimaging/methods* ; Cognitive Dysfunction/diagnosis*

Committee of Minimally Invasive Cardiovascular Surgery (CMICS) annually investigates the minimally invasive cardiovascular surgery performed by departments of cardiovascular surgery of all hospitals in China of last year, and makes classification and summary according to the operation amount of minimally invasive surgery, regional and hospital distribution, and publishes it on the theme report of China Minimally Invasive Cardiovascular Surgery Conference (CMC). In 2021, CMICS published the 2018-2019 annual data of Chinese cardiovascular surgery in the form of a white paper for the first time in the Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, which attracted great attention from peers. In this statistical report, CMICS will focus on the volume of minimally invasive cardiovascular surgery, regional and hospital distribution in China (excluding Hong Kong Special Administrative Region, Macao Special Administrative Region, and Taiwan Province) in the 2020—2021 for your reference.

The Monte Carlo N-Particle (MCNP) is often used to calculate the radiation dose during computed tomography (CT) scans. However, the physical calculation process of the model is complicated, the input file structure of the program is complex, and the three-dimensional (3D) display of the geometric model is not supported, so that the researchers cannot establish an accurate CT radiation system model, which affects the accuracy of the dose calculation results. Aiming at these two problems, this study designed a software that visualized CT modeling and automatically generated input files. In terms of model calculation, the theoretical basis was based on the integration of CT modeling improvement schemes of major researchers. For 3D model visualization, LabVIEW was used as the new development platform, constructive solid geometry (CSG) was used as the algorithm principle, and the introduction of editing of MCNP input files was used to visualize CT geometry modeling. Compared with a CT model established by a recent study, the root mean square error between the results simulated by this visual CT modeling software and the actual measurement was smaller. In conclusion, the proposed CT visualization modeling software can not only help researchers to obtain an accurate CT radiation system model, but also provide a new research idea for the geometric modeling visualization method of MCNP.
Radiation Dosage ; Software Design ; Tomography, X-Ray Computed/methods* ; Software ; Algorithms ; Phantoms, Imaging ; Monte Carlo Method

In recent years, photon-counting computed tomography (PCD-CT) based on photon-counting detectors (PCDs) has become increasingly utilized in clinical practice. Compared with conventional CT, PCD-CT has the potential to achieve micron-level spatial resolution, lower radiation dose, negligible electronic noise, multi-energy imaging, and material identification, etc. This advancement facilitates the promotion of ultra-low dose scans in clinical scenarios, potentially detecting minimal and hidden lesions, thus significantly improving image quality. However, the current state of the art is limited and issues such as charge sharing, pulse pileup, K-escape and count rate drift remain unresolved. These issues could lead to a decrease in image resolution and energy resolution, while an increasing in image noise and ring artifact and so on. This article systematically reviewed the physical principles of PCD-CT, and outlined the structural differences between PCDs and energy integration detectors (EIDs), and the current challenges in the development of PCD-CT. In addition, the advantages and disadvantages of three detector materials were analysed. Then, the clinical benefits of PCD-CT were presented through the clinical application of PCD-CT in the three diseases with the highest mortality rate in China (cardiovascular disease, tumour and respiratory disease). The overall aim of the article is to comprehensively assist medical professionals in understanding the technological innovations and current technical limitations of PCD-CT, while highlighting the urgent problems that PCD-CT needs to address in the coming years.
Tomography, X-Ray Computed/methods* ; Photons ; Noise ; China ; Phantoms, Imaging