[Pulmonary PET /CT image instance segmentation based on dense interactive feature fusion Mask RCNN].

There are some problems in positron emission tomography/ computed tomography (PET/CT) lung images, such as little information of feature pixels in lesion regions, complex and diverse shapes, and blurred boundaries between lesions and surrounding tissues, which lead to inadequate extraction of tumor lesion features by the model. To solve the above problems, this paper proposes a dense interactive feature fusion Mask RCNN (DIF-Mask RCNN) model. Firstly, a feature extraction network with cross-scale backbone and auxiliary structures was designed to extract the features of lesions at different scales. Then, a dense interactive feature enhancement network was designed to enhance the lesion detail information in the deep feature map by interactively fusing the shallowest lesion features with neighboring features and current features in the form of dense connections. Finally, a dense interactive feature fusion feature pyramid network (FPN) network was constructed, and the shallow information was added to the deep features one by one in the bottom-up path with dense connections to further enhance the model's perception of weak features in the lesion region. The ablation and comparison experiments were conducted on the clinical PET/CT lung image dataset. The results showed that the APdet, APseg, APdet_s and APseg_s indexes of the proposed model were 67.16%, 68.12%, 34.97% and 37.68%, respectively. Compared with Mask RCNN (ResNet50), APdet and APseg indexes increased by 7.11% and 5.14%, respectively. DIF-Mask RCNN model can effectively detect and segment tumor lesions. It provides important reference value and evaluation basis for computer-aided diagnosis of lung cancer.

Global research progress of endothelial cells and ALI/ARDS: a bibliometric analysis.

Background: Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are severe respiratory conditions with complex pathogenesis, in which endothelial cells (ECs) play a key role. Despite numerous studies on ALI/ARDS and ECs, a bibliometric analysis focusing on the field is lacking. This study aims to fill this gap by employing bibliometric techniques, offering an overarching perspective on the current research landscape, major contributors, and emerging trends within the field of ALI/ARDS and ECs. Methods: Leveraging the Web of Science Core Collection (WoSCC) database, we conducted a comprehensive search for literature relevant to ALI/ARDS and ECs. Utilizing Python, VOSviewer, and CiteSpace, we performed a bibliometric analysis on the corpus of publications within this field. Results: This study analyzed 972 articles from 978 research institutions across 40 countries or regions, with a total of 5,277 authors contributing. These papers have been published in 323 different journals, spanning 62 distinct research areas. The first articles in this field were published in 2011, and there has been a general upward trend in annual publications since. The United States, Germany, and China are the principal contributors, with Joe G. N. Garcia from the University of Arizona identified as the leading authority in this field. American Journal of Physiology-Lung Cellular and Molecular Physiology has the highest publication count, while Frontiers in Immunology has been increasingly focusing on this field in recent years. "Cell Biology" stands as the most prolific research area within the field. Finally, this study identifies endothelial glycocalyx, oxidative stress, pyroptosis, TLRs, NF-κB, and NLRP3 as key terms representing research hotspots and emerging frontiers in this field. Conclusion: This bibliometric analysis provides a comprehensive overview of the research landscape surrounding ALI/ARDS and ECs. It reveals an increasing academic focus on ALI/ARDS and ECs, particularly in the United States, Germany, and China. Our analysis also identifies several emerging trends and research hotspots, such as endothelial glycocalyx, oxidative stress, and pyroptosis, indicating directions for future research. The findings can guide scholars, clinicians, and policymakers in targeting research gaps and setting priorities to advance the field.

Anti-synthase syndrome associated with SARS-Cov-2 infection.

BACKGROUND: Anti-synthetase syndrome (AS) is a rare autoimmune idiopathic inflammatory myopathy (IIM) with diverse manifestations, including arthritis, interstitial lung disease (ILD), Raynaud's phenomenon, unexplained persistent fever, and mechanic's hands. CASE PRESENTATION: We present the case of a 72-year-old woman, previously healthy, who was admitted to our hospital for treatment of cough and rapid breathing. The patient had elevated white blood cells and C-reactive protein, and tested negative for severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). She was initially diagnosed with community-acquired pneumonia and received tamoxifen for anti-infection treatment, but her dystonia worsened. She eventually required non-invasive ventilator support, tested positive for SARS-Cov-2 again, and started antiviral therapy, corticosteroids to reduce alveolar effusion, anticoagulation, and other treatments. However, her condition continued to deteriorate, with the lowest oxygenation index reaching only 80mmHg. Ultimately, she underwent tracheal intubation and mechanical ventilation. Chest CT revealed rapid progressive interstitial changes in her lungs, and her hands showed noticeable fraternization changes. At this point, we suspected that the novel coronavirus infection might be associated with autoimmune diseases. The patient's autoimmune antibody spectrum showed positive results for anti-recombinant RO-52 antibody and myositis-specific antibody anti-alanyl tRNA synthetase (anti-PL-12). The patient was treated with dexamethasone sodium phosphate for anti-inflammatory and anti-fibrotic effects. After successful extubation, the patient was discharged with only oral prednisone tablets at a dose of 30 mg. CONCLUSIONS: This case presents an early diagnosis and successful treatment of anti-synthetase syndrome combined with SARS-Cov-2 infection, emphasizing the importance of comprehensive physical examination. Additionally, it highlights the rapid progression of interstitial lung disease under SARS-Cov-2 infection, which is often difficult to distinguish on imaging. In cases where treatment for SARS-Cov-2 infection is ineffective, early screening for autoimmune diseases is recommended. As there is currently no standardized method for treating AS-ILD, the successful treatment of this case provides a reference for clinical research on anti-synthetase syndrome in the later stage.

A Dual-Branch Framework With Prior Knowledge for Precise Segmentation of Lung Nodules in Challenging CT Scans.

Lung cancer is one of the deadliest cancers globally, and early diagnosis is crucial for patient survival. Pulmonary nodules are the main manifestation of early lung cancer, usually assessed using CT scans. Nowadays, computer-aided diagnostic systems are widely used to assist physicians in disease diagnosis. The accurate segmentation of pulmonary nodules is affected by internal heterogeneity and external data factors. In order to overcome the segmentation challenges of subtle, mixed, adhesion-type, benign, and uncertain categories of nodules, a new mixed manual feature network that enhances sensitivity and accuracy is proposed. This method integrates feature information through a dual-branch network framework and multi-dimensional fusion module. By training and validating with multiple data sources and different data qualities, our method demonstrates leading performance on the LUNA16, Multi-thickness Slice Image dataset, LIDC, and UniToChest, with Dice similarity coefficients reaching 86.89%, 75.72%, 84.12%, and 80.74% respectively, surpassing most current methods for pulmonary nodule segmentation. Our method further improved the accuracy, reliability, and stability of lung nodule segmentation tasks even on challenging CT scans.

Impact of bronchoscopic thermal vapor ablation on lung volume reduction in patients with emphysema: a meta-analysis.

BACKGROUND: Bronchoscopic lung volume reduction (LVR) could significantly improve pulmonary function and quality of life in patients with emphysema. We aimed to assess the efficacy and safety of bronchoscopic thermal vapor ablation (BTVA) on LVR in patients with emphysema at different stage. METHODS: A systematic search of database including PubMed, Embase and Cochrane library was conducted to determine all the studies about bronchoscopic thermal vapor ablation published through Dec 1, 2022. Related searching terms were "lung volume reduction", "bronchoscopic thermal vapor ablation", "bronchial thermal vapor ablation" "BTVA" and "emphysema", "efficacy" and"safety". We used standardized mean difference (SMD) to analyze the summary estimates for BTVA therapy. RESULTS: We retrieved 30 records through database search, and 4 trials were selected for meta-analysis, including 112 patients with emphysema. Meta-analysis of the pooled effect showed that levels of forced expiratory volume in 1 s (FEV1), residual volume (RV), total lung capacity (TLC), 6-min walk distance (6MWD) and St George's Respiratory Questionnaire (SGRQ) were significantly improved in patients with emphysema following BTVA treatment between 6 months vs. baseline. Additionally, no significant changes in FEV1, RV, TLC and SGRQ occurred from 3 to 6 months of follow-up except for 6MWD. The magnitude of benefit was higher at 3 months compared to 6 months. The most common complications at 6 months were treatment-related chronic obstructive pulmonary disease (COPD) exacerbations (RR: 12.49; 95% CI: 3.06 to 50.99; p < 0.001) and pneumonia (RR: 9.49; 95% CI: 2.27 to 39.69; p < 0.001). CONCLUSIONS: Our meta-analysis provided clinically relevant information about the impact and safety of BTVA on predominantly upper lobe emphysema. Particularly, short-term significant improvement of lung function and quality of life occurred especially within the initial 3 months. Further large-scale, well-designed long-term interventional investigations are needed to clarify this issue.

Deep neural network pulmonary nodule segmentation methods for CT images: Literature review and experimental comparisons.

Automatic and accurate segmentation of pulmonary nodules in CT images can help physicians perform more accurate quantitative analysis, diagnose diseases, and improve patient survival. In recent years, with the development of deep learning technology, pulmonary nodule segmentation methods based on deep neural networks have gradually replaced traditional segmentation methods. This paper reviews the recent pulmonary nodule segmentation algorithms based on deep neural networks. First, the heterogeneity of pulmonary nodules, the interpretability of segmentation results, and external environmental factors are discussed, and then the open-source 2D and 3D models in medical segmentation tasks in recent years are applied to the Lung Image Database Consortium and Image Database Resource Initiative (LIDC) and Lung Nodule Analysis 16 (Luna16) datasets for comparison, and the visual diagnostic features marked by radiologists are evaluated one by one. According to the analysis of the experimental data, the following conclusions are drawn: (1) In the pulmonary nodule segmentation task, the performance of the 2D segmentation models DSC is generally better than that of the 3D segmentation models. (2) 'Subtlety', 'Sphericity', 'Margin', 'Texture', and 'Size' have more influence on pulmonary nodule segmentation, while 'Lobulation', 'Spiculation', and 'Benign and Malignant' features have less influence on pulmonary nodule segmentation. (3) Higher accuracy in pulmonary nodule segmentation can be achieved based on better-quality CT images. (4) Good contextual information acquisition and attention mechanism design positively affect pulmonary nodule segmentation.

Fusu mixture alleviates inflammatory reactions in lipopolysaccharide-induced acute respiratory distress syndrome mice via regulation of surfactant-associated protein C, aquaporin 5, and Notch1.

Background: Acute respiratory distress syndrome (ARDS) is a common life-threatening critical illness with high mortality. Fusu mixture (FSM) can improve the mechanical ventilation in ARDS patients. However, the detailed pharmacological mechanisms and active substances of FSM are still unclear. This study aimed to explore the potential pharmacological mechanisms of FSM for treating ARDS and its chemical compositions. Methods: A lipopolysaccharide (LPS)-induced ARDS mouse model was established, and the mice subsequently received FSM (50 mg/kg) orally for 5 days. Then, the blood samples and lung tissues were collected. Enzyme-linked immunosorbent assay (ELISA) was used to determine the levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in serum, and histopathology examinations were applied to analyze the inflammatory response of lung tissues in ARDS mice. In addition, protein expressions of aquaporin 5 (AQP-5), surfactant-associated protein C (SP-C), and Notch1 were detected by western blot assays and immunohistochemical (IHC) examination. In addition, the chemical compositions of FSM were analyzed by high performance liquid chromatography (HPLC), using standard reference agents. Results: After LPS induction, the serum levels of IL-6 and TNF-α in ARDS mice were significantly increased (P<0.01, vs. Control), and FSM significantly reduced these 2 pro-inflammatory cytokines (IL-6 and TNF-α) compared to the model mice (P<0.01). Histopathology examinations showed FSM significantly attenuated the inflammatory responses in lung tissues. Furthermore, after FSM treatment, the SP-C and AQP-5 were significantly increased, compared to the Model mice (P<0.01), and FSM also up-regulated the Notch1 expressions in lung tissues of ARDS mice (P<0.001, vs. Model). Conclusions: Collectively, it is suggested that FSM alleviates inflammatory reactions and promotes the proliferation of alveolar epithelial cells in LPS-induced ARDS mice via regulation of SP-C, AQP-5, and Notch1 in lung tissues.

Severe varicella-zoster virus meningoencephalomyelitis coexisting with visceral disseminated varicella-zoster virus infection in a patient with lupus nephritis: A case report.

RATIONALE: Meningoencephalomyelitis and visceral dissemination infection are rare but life-threatening complications of either the primary infection or reactivation of varicella-zoster virus (VZV) in immunocompromised patients. To date, few studies have reported the co-existence of VZV meningoencephalomyelitis and the visceral dissemination of VZV infection. PATIENT CONCERNS: A 23-year-old male was diagnosed with lupus nephritis class III and was being treated with oral prednisone and tacrolimus. The patient exhibited herpes zoster 21-day after the initiation of therapy and experienced unbearable abdominal pain and generalized seizures 11 days after the onset of a zoster rash. Magnetic resonance imaging showed progressive lesions in the cerebrum, brainstem, and cerebellum, as well as meningeal thickening and thoracic myelitis. Computed tomography showed pulmonary interstitial infiltration, partial intestinal dilatation, and effusion. Metagenomic next-generation sequencing revealed 198,269 and 152,222 VZV-specific reads in the cerebrospinal fluid and bronchoalveolar lavage fluid, respectively. DIAGNOSES: Based on the clinical and genetic findings, this patient was finally diagnosed with VZV meningoencephalomyelitis and visceral disseminated VZV infection. INTERVENTIONS: The patient received intravenous acyclovir (0.5 g every 8 hours) combined with plasma exchange and intravenous immunoglobulin. Treatment against secondary bacterial and fungal infections, organ support therapy and rehabilitation training were given simultaneously. OUTCOME: The patient's peripheral muscle strength did not improve and repeated metagenomic next-generation sequencing showed the persistence of VZV-specific reads in the cerebrospinal fluid. The patient finally abandoned therapy due to financial constraints at the 1-month follow-up. LESSONS: Patients with autoimmune diseases receiving immunosuppressive therapy should be warned about the possibility of developing serious neurological infections and visceral disseminated VZV infections as side effects. Early diagnosis and the early initiation of intravenous acyclovir therapy are important for such cases.

Nested multi-scale transform fusion model: The response evaluation of chemoradiotherapy for patients with lung tumors.

BACKGROUND AND OBJECTIVE: The response evaluation of chemoradiotherapy is an important method of precision treatment for patients with malignant lung tumors. In view of the existing evaluation criteria for chemoradiotherapy, it is difficult to synthesize the geometric and shape characteristics of lung tumors. In the present, the response evaluation of chemoradiotherapy is limited. Therefore, this paper constructs a response evaluation system of chemoradiotherapy based on PET/CT images. METHODS: There are two parts in the system: a nested multi-scale fusion model and an attribute sets for the Response evaluation of chemoradiotherapy (AS-REC). In the first part, a new nested multi-scale transform method, i.e., latent low-rank representation (LATLRR) and non-subsampled contourlet transform (NSCT), is proposed. Then, the average gradient self-adaptive weighting is used for the low-frequency fusion rule, and the regional energy fusion rule is used for the high-frequency fusion rule. Further, the low-rank part fusion image is obtained by the inverse NSCT, and the fusion image is generated by adding the low-rank part fusion image and the significant part fusion image. In the second part, AS-REC is constructed to evaluate the growth direction of the tumor, the degree of tumor metabolic activity, and the tumor growth state. RESULTS: the numerical results clearly show that the performance of our proposed method outperforms in comparison with several existing methods, among them, the value of Qabf increased by up to 69%. CONCLUSIONS: Through the experiment of three reexamination patients, the effectiveness of the evaluation system of radiotherapy and chemotherapy are proved.

Yang-xin-xue keli exerts therapeutic effects via regulating mitochondrial homeostasis and function in doxorubicin-induced rat heart failure.

Background: Heart failure, especially chronic heart failure, is generally induced by the accumulation of reactive oxygen species (ROS), as well as the subsequent loss of mitochondrial permeability transition pore (mPTP) openings and pathological mitochondrial dysfunction. Herein, we explored the therapeutic effects of the Chinese medicine Yangxin Keli (YXXKL) on chronic heart failure and its underlying working mechanism. Methods: To mimic oxidative stress-induced chronic heart failure, a rat heart failure model was induced by the administration of DOX. Transthoracic echocardiography was performed to confirm the successful establishment of the heart failure model by observing significantly decreased cardiac function in the rats. Mitochondrial membrane potential, function, and ATP synthesis activity were measured after YXXKL was employed. Results The administration of YXXKL not only significantly improved cardiac function but also reversed the myocardium loss and fibrosis induced via DOX. Moreover, the administration of YXXKL also increased ATP synthesis and mitochondrial DNA mass in left ventricular tissues, which indicated that mitochondria may be a key target of YXXKL. Thus, we employed rat cardiomyocyte H9c2 and primary rat cardiac myocytes (RCMs) to induce oxidative stress-induced myocardial injury via DOX treatment. YXXKL-medicated serum promoted cell proliferation, which was inhibited by the addition of IC30 DOX, and the serum also inhibited cell apoptosis, which was promoted by the addition of IC50 DOX. YXKL-medicated serum was able to scavenge ROS and maintain the mitochondrial membrane potential as well as promote mitochondrial function, including the promotion of ATP synthesis, mitochondrial DNA mass, and transcriptional activity. Furthermore, we also observed that YXXKL-medicated serum inhibited DOX-induced autophagy/mitophagy by scavenging ROS. Conclusion: Taken together, we conclude that YXXKLI may exert therapeutic effects on oxidative stress-related heart failure via the regulation of mitochondria.

Diagnostic value of rapid on-site evaluation in interventional pulmonology: A protocol for systematic review and meta analysis.

BACKGROUND: Rapid on-site evaluation (ROSE) is a kind of rapid evaluation of specimen satisfaction, preliminary diagnosis and priority strategy, the diagnostic accuracy of ROSE in the field of pulmonary intervention shows wide variation. The aim of the study was to further clarify the accuracy and diagnostic efficacy of ROSE in interventional pulmonology. METHODS: This review summarizes and meta-analyzes studies of ROSE in interventional pulmonology, the ROSE diagnoses would be compared with the final pathologic diagnoses. The following electronic databases have been searched: PubMed, Cochrane Library, Embase, Web of science, CNKI, and WANFANG DATA. The methodologic quality of studies has been assessed using the Quality of Diagnostic Studies (QUADAS-2) instrument. This review is conducted using standard methods for systematic reviews of diagnostic accuracy studies. STATA SE 12.0 is used for data synthesis and analysis. RESULTS: This review evaluates the accuracy and diagnostic efficacy of ROSE in interventional pulmonology, and the process factors that may influence the ROSE diagnosis are analyzed, such as Smear method, profession of smear technician, staining method, Profession of stain technician, Profession of reading slides, invasive procedure, Anesthesia method and etc. CONCLUSION:: This review will stimulate proper evaluation of ROSE and provide assistance for clinical practice.

Medical Image Retrieval Using Empirical Mode Decomposition with Deep Convolutional Neural Network.

Content-based medical image retrieval (CBMIR) systems attempt to search medical image database to narrow the semantic gap in medical image analysis. The efficacy of high-level medical information representation using features is a major challenge in CBMIR systems. Features play a vital role in the accuracy and speed of the search process. In this paper, we propose a deep convolutional neural network- (CNN-) based framework to learn concise feature vector for medical image retrieval. The medical images are decomposed into five components using empirical mode decomposition (EMD). The deep CNN is trained in a supervised way with multicomponent input, and the learned features are used to retrieve medical images. The IRMA dataset, containing 11,000 X-ray images, 116 classes, is used to validate the proposed method. We achieve a total IRMA error of 43.21 and a mean average precision of 0.86 for retrieval task and IRMA error of 68.48 and F1 measure of 0.66 on classification task, which is the best result compared with existing literature for this dataset.

[Third investigation and analysis of quality control situation of intensive care unit in traditional Chinese medicine hospitals in Sichuan Province].

OBJECTIVE: To evaluate the present development and status of quality control for intensive care unit (ICU) in Sichuan Provincial traditional Chinese medicine (TCM) hospitals including integrated traditional Chinese and western medicine hospitals and ethnic hospitals, and to provide practical references for improving the service quality of ICU. METHODS: Supervisory Group of Sichuan Provincial Critical Care Medicine Quality Control Center of TCM was established in September 2018. From September 8th to 17th, 2018, according to the Scoring Criteria of Quality Control and Supervision Project of TCM for Critical Care Medicine, a 10-day quality control professional guidance was hand out to TCM hospitals with independent ICU in Sichuan Province. The service level of different aspects of hospital quality control was evaluated and ranked from equipment and resource support, medical team, service capacity and level, ward quality, completion of critical care core indicators, completion of quality control of TCM, development of new technologies, diagnosis and treatment schemes for dominant diseases. RESULTS: There were 52 TCM hospitals across the province that had an ICU. Thirty-three hospitals were third-class (63.5%), while the rest 19 hospitals were second-class (36.5%). Province-level, city-level and county-level hospitals were accounted for 9.6% (5/52), 38.5% (20/52), and 51.9% (27/52), respectively. Average bed ratio of ICU was 1.8%. Doctor-bed and guard-bed ratios were 0.71:1 and 2.0:1, respectively. The average annual admission rate of patients and the average daily admission rate of beds were higher, which were basically 1%. Ward quality was high; the incidence of nosocomial infection was controlled below 10%. Compliance rate of septic shock bundle treatment was high. The incidences of ventilator-associated pneumonia (VAP), catheter-related bloodstream infection (CRBSI) and catheter-associated urinary tract infection (CAUTI) were 0.45%, 0.22%, and 0.30%, respectively. Participation rate of TCM was about 83.4%. Average number of new technologies was about 4.4. Average number of disease schemes was about 2.62. CONCLUSIONS: ICU of Sichuan Provincial TCM hospitals reaches the standard level in service capacity and level, ward quality, critical medicine quality control, and participation rate of TCM treatment. Improvements are required for other prospects, including department scale, medical personnel allocation, new technical development, diagnosis and treatment schemes of dominant diseases.