Superior scapular location: An overlooked albeit frequent finding in elastofibroma dorsi.

PURPOSE: To explore the frequency of superior scapular elastofibroma dorsi in a large patient series with elastofibroma dorsi. METHODS: 136 chest CTs from January 2016 to July 2022 reporting elastofibroma dorsi were retrospectively analyzed. Three radiologists assessed the number, size, and location of elastofibroma dorsi. Continuous variables underwent two-tailed t-tests with p < 0.05. Inter-observer agreement was assessed by using Cohen's Kappa values. RESULTS: In 136 patients (mean age, 75.9 +/- 9.8 years; 117 female), 330 elastofibroma dorsi were found. Six (4.4 %) patients had single, 87 (64 %) double, 22 (16.2 %) triple and 21 (15.4 %) quadruple lesions. All single and double lesions were in the inferior scapular regions. 43 (31.6 %) patients had superior scapular lesions in addition to inferior scapular elastofibroma dorsi. Inferior scapular elastofibroma dorsi was significantly larger than superior scapular elastofibroma dorsi. The probability of a right superior lesion was significantly higher in patients with a larger right inferior lesion. Inter-observer agreement was very good for experienced radiologist (κ = 94.1) and good for other radiologists (κ = 79.4 and κ = 78). CONCLUSION: In contrast to current belief, superior scapular elastofibroma dorsi accompanying the typical inferior scapular lesions is not uncommon and can even manifest bilaterally. To the best of our knowledge, this is the first case series reporting prevalence of quadruple elastofibroma dorsi.

ADVANCES IN MINIMALLY INVASIVE SURGERY FOR PECTUS EXCAVATUM: ENHANCING OUTCOMES AND PATIENT CARE.

Pectus excavatum, also called sunken chest, is the most common deformation of the sternum (90%). The deformation is caused by the depression of the sternum and costal cartilages, which causes reduction of the chest cavity and dysfunction of cardio-pulmonary systems in it. Sunken chest is more common in males than females, prevalence is 5/1. Most of the cases appear in the first year of life, however severity of the pathology is formed during puberty. Etiopathogenesis, genetic factors, and associated diseases of Pectus Excavatum are various and are still the subject of study. The manifestation of the disease is determined by the degree of chest deformation, which is calculated using the "Haller index". Providing that a high degree of deformation can lead to pathological functioning of the cardiovascular and respiratory systems. The treatment of this condition is an urgent, complex, and developing issue. The main method of treatment for sunken chest is surgical intervention; However, in cases of mild degrees of the mentioned deformation, different approaches are used. Our goal is to discuss contrasting treatment techniques and present our improved repairing technique for sunken chest, which is performed in Georgia.

Mediastinal Rosai-Dorfman Disease with KRAS mutation case report and literature review.

BACKGROUND: Rosai-Dorfman Disease (RDD) is a rare self-limiting histiocytosis, more prevalent in children and young adults. It typically manifests as painless bilateral massive cervical lymphadenopathy but may also extend to extra-nodal sites, with intrathoracic RDD noted in 2% of cases. Distinguishing mediastinal RDD from thymoma on imaging poses challenges, underscoring the reliance on pathological features and immunohistochemical staining for diagnosis. CASE PRESENTATION: Patient, male, 33 years old, underwent lung a CT revealing an enlarged round soft tissue shadow in the anterior superior mediastinum, compared to a year ago. Surgical resection removed the entire mass, thymus, and part of the pericardium, confirming RDD on pathology. Genetic testing using second-generation testing technology identified a KRAS gene point mutation. CONCLUSIONS: No established treatment protocol currently exists for this disease. However, as genetic mutation research progresses, a novel therapeutic avenue is emerging: targeted therapy integrated with surgical interventions.

Dyssynchronous diaphragm contractions impair diaphragm function in mechanically ventilated patients.

BACKGROUND: Pre-clinical studies suggest that dyssynchronous diaphragm contractions during mechanical ventilation may cause acute diaphragm dysfunction. We aimed to describe the variability in diaphragm contractile loading conditions during mechanical ventilation and to establish whether dyssynchronous diaphragm contractions are associated with the development of impaired diaphragm dysfunction. METHODS: In patients receiving invasive mechanical ventilation for pneumonia, septic shock, acute respiratory distress syndrome, or acute brain injury, airway flow and pressure and diaphragm electrical activity (Edi) were recorded hourly around the clock for up to 7 days. Dyssynchronous post-inspiratory diaphragm loading was defined based on the duration of neural inspiration after expiratory cycling of the ventilator. Diaphragm function was assessed on a daily basis by neuromuscular coupling (NMC, the ratio of transdiaphragmatic pressure to diaphragm electrical activity). RESULTS: A total of 4508 hourly recordings were collected in 45 patients. Edi was low or absent (≤ 5 µV) in 51% of study hours (median 71 h per patient, interquartile range 39-101 h). Dyssynchronous post-inspiratory loading was present in 13% of study hours (median 7 h per patient, interquartile range 2-22 h). The probability of dyssynchronous post-inspiratory loading was increased with reverse triggering (odds ratio 15, 95% CI 8-35) and premature cycling (odds ratio 8, 95% CI 6-10). The duration and magnitude of dyssynchronous post-inspiratory loading were associated with a progressive decline in diaphragm NMC (p < 0.01 for interaction with time). CONCLUSIONS: Dyssynchronous diaphragm contractions may impair diaphragm function during mechanical ventilation. TRIAL REGISTRATION: MYOTRAUMA, ClinicalTrials.gov NCT03108118. Registered 04 April 2017 (retrospectively registered).

Posterior mediastinal leiomyosarcoma: Case report and literature review.

BACKGROUND: Posterior mediastinal leiomyosarcoma is an extremely rare malignant mesenchymal tumor with no special clinical symptoms, which is easily confused with some common tumors in the posterior mediastinum, affecting the accuracy of the first diagnosis by clinicians and delaying the treatment of patients. CASE SUMMARY: We report a 59-year-old woman with a space-occupying lesion in the posterior mediastinum. The patient was mistakenly diagnosed with lumbar muscle or vertebral body lesions due to chest and back pain and underwent conservative treatment, but her symptoms did not improve significantly and she gradually developed pain in both lower limbs. Chest computed tomography (CT) scan indicated the left lower lung paraspinal space and underwent standard single-aperture video-assisted thoracoscopic surgery (VATS), which was pathologically confirmed as posterior mediastinal leiomyosarcoma. CONCLUSION: Complete surgical resection of posterior mediastinal leiomyosarcoma can achieve good clinical results.

Morphological comparative study of canine and feline diaphragms: Effect of bodyweight, body condition score, gender, age and breed.

The canine diaphragm is a muscular and tendinous dome-like plate and is largely involved in digestive and respiratory functions. Very few studies compared morphology of the diaphragm between dogs and cats and no studies have investigated the effects of individual factors on this morphology. So the aim of this study was to (1) study the effects of individual factors on the morphology of the diaphragm and (2) to compare its morphology between cats and dogs. Surface measurements of 86 diaphragms were performed. The tendinous centre (TC), the lumbar part of the peripheral muscular (LP) and the sternal and costal parts of the peripheral muscular (SCPM) were measured. Measurement ratios (surface of anatomical part of the diaphragm/total surface of the diaphragm) were used for statistical analysis (TC%S, LP%S, SCPM%S). The SCPM%S are significantly lower, and the LP%S are significantly higher when bodyweight increases in dogs and cats. The TC%S are significantly lower when the body condition score of dogs increases. The SCPM%S are significantly higher, and therefore, the TC%S and LP%S lower in brachycephalic animals as opposed to mesocephalic animals. The TC%S are significantly higher in dogs than in cats and the SCPM%S are significantly higher in cats than in dogs. This study proposed a cartography of the diaphragm morphology in cats and dogs taking into account individual animal factors. Significant differences in the diaphragm morphology between cats and dogs and between mesocephalic and brachycephalic animals were found. Further studies are necessary to confirm these results and to investigate the consequences of these variations.

Network-based analysis identifies potential therapeutic ingredients of Chinese medicines and their mechanisms toward lung cancer.

Lung cancer is one of the most common malignant tumors around the world, which has the highest mortality rate among all cancers. Traditional Chinese medicine (TCM) has attracted increased attention in the field of lung cancer treatment. However, the abundance of ingredients in Chinese medicines presents a challenge in identifying promising ingredient candidates and exploring their mechanisms for lung cancer treatment. In this work, two network-based algorithms were combined to calculate the network relationships between ingredient targets and lung cancer targets in the human interactome. Based on the enrichment analysis of the constructed disease module, key targets of lung cancer were identified. In addition, molecular docking and enrichment analysis of the overlapping targets between lung cancer and ingredients were performed to investigate the potential mechanisms of ingredient candidates against lung cancer. Ten potential ingredients against lung cancer were identified and they may have similar effect on the development of lung cancer. The results obtained from this study offered valuable insights and provided potential avenues for the development of novel drugs aimed at treating lung cancer.

TRAUMATIC BRAIN INJURY AND ITS IMPLICATIONS FOR BEHAVIORAL HEALTH FACTORS.

The constant increase in the level of traumatic brain injuries in recent years, the frequent cases of disability and mortality associated with them require in-depth comprehensive research to study the problem on the ground, its medical, social, and economic aspects, which is very important for improving organizational measures to reduce traumatization among all age groups of the population. Objectives - to determine the presence and nature of structural damage associated with traumatic brain injury. The presence and nature of structural damage associated with traumatic brain injury. The studies included data on the treatment of victims with traumatic brain injuries from 2016 to 2020 on the basis of the Surgical Clinic of the Azerbaijan Medical University. Among the victims, men accounted for 77.9% and women 22.1%. In a prospective comparative study, after signing informed consent, 299 people of different sexes were included, of which 90 were victims with isolated TBI. The inclusion criteria for the study were as follows: victims with a verified diagnosis of TBI; age over 18; patients without concomitant somatic pathology. In a gender-comparative analysis of the revealed data, an injury combined with fractures of the bones of the extremities was recorded in 77 (81.1%) males and 18 of their female opponents, who also received TBI and accounted for 18.9%. Also high, especially in the male half of the examined injured persons, was the frequency of occurrence of TBI combinations with rib fractures and injuries of the chest organs, such injuries were registered in 41 victims, which accounted for 77.4% of all the above combined TBI. Somewhat less in both sex groups was TBI in combination with traumatic injuries of organs and tissues of the abdominal region, as well as with mixed injuries (χ2 criterion is 2.066; Df=4; p=0.724). The lowest level of TBI was observed in people under the age of 20 and older than 70 years, in other groups this figure increased sharply, reaching a maximum at the age of 20-29 and 40-49 years, and stabilized in the age groups over 49 years. The maximum number of cases associated with partial or complete loss of consciousness was recorded in persons aggravated by simultaneous traumatization of the upper or lower extremities and chest, as well as in isolated TBI.

Enhancing medical image segmentation with a multi-transformer U-Net.

Various segmentation networks based on Swin Transformer have shown promise in medical segmentation tasks. Nonetheless, challenges such as lower accuracy and slower training convergence have persisted. To tackle these issues, we introduce a novel approach that combines the Swin Transformer and Deformable Transformer to enhance overall model performance. We leverage the Swin Transformer's window attention mechanism to capture local feature information and employ the Deformable Transformer to adjust sampling positions dynamically, accelerating model convergence and aligning it more closely with object shapes and sizes. By amalgamating both Transformer modules and incorporating additional skip connections to minimize information loss, our proposed model excels at rapidly and accurately segmenting CT or X-ray lung images. Experimental results demonstrate the remarkable, showcasing the significant prowess of our model. It surpasses the performance of the standalone Swin Transformer's Swin Unet and converges more rapidly under identical conditions, yielding accuracy improvements of 0.7% (resulting in 88.18%) and 2.7% (resulting in 98.01%) on the COVID-19 CT scan lesion segmentation dataset and Chest X-ray Masks and Labels dataset, respectively. This advancement has the potential to aid medical practitioners in early diagnosis and treatment decision-making.

Generalizable disease detection using model ensemble on chest X-ray images.

In the realm of healthcare, the demand for swift and precise diagnostic tools has been steadily increasing. This study delves into a comprehensive performance analysis of three pre-trained convolutional neural network (CNN) architectures: ResNet50, DenseNet121, and Inception-ResNet-v2. To ensure the broad applicability of our approach, we curated a large-scale dataset comprising a diverse collection of chest X-ray images, that included both positive and negative cases of COVID-19. The models' performance was evaluated using separate datasets for internal validation (from the same source as the training images) and external validation (from different sources). Our examination uncovered a significant drop in network efficacy, registering a 10.66% reduction for ResNet50, a 36.33% decline for DenseNet121, and a 19.55% decrease for Inception-ResNet-v2 in terms of accuracy. Best results were obtained with DenseNet121 achieving the highest accuracy at 96.71% in internal validation and Inception-ResNet-v2 attaining 76.70% accuracy in external validation. Furthermore, we introduced a model ensemble approach aimed at improving network performance when making inferences on images from diverse sources beyond their training data. The proposed method uses uncertainty-based weighting by calculating the entropy in order to assign appropriate weights to the outputs of each network. Our results showcase the effectiveness of the ensemble method in enhancing accuracy up to 97.38% for internal validation and 81.18% for external validation, while maintaining a balanced ability to detect both positive and negative cases.

[Diaphragmatic dysfunction post-COVID-19 infection: report of two cases].

Following the global outbreak of COVID-19, many patients have suffered from multi-system complications and long-term sequelae caused by the virus. Diaphragm dysfunction is an obscure post-COVID-19 symptom. Although a few cases of diaphragm dysfunction caused by COVID-19 infection have been reported abroad, there are no relevant reports in China. Herein, we present two cases of patients with respiratory distress after COVID-19 infection. On admission, dynamic chest radiographs revealed diaphragm dysfunction in these patients. Further investigations including diaphragm ultrasound, neurophysiological examinations, transdiaphragmatic pressure measurements cranial MRI, and antibody testing for autoimmune diseases, were conducted. The final diagnoses were severe myasthenia gravis induced by COVID-19 infection and diaphragmatic nerve and muscle involvement caused by COVID-19 infection. Both patients showed improvement in symptoms after treatment. Therefore, we summarized our case, with a review of the relevant literature to improve the understanding of the disease and to provide clinical evidence for future diagnosis and treatment.

Feasibility of thoracoscopic monosubsegmentectomy for small ground-glass opacity dominant lung cancer.

BACKGROUND: Monosubsegmentectomy (MSS) involves removal of less lung parenchyma than monosegmentectomy (MS) does. However, the clinical efficacy of MSS in lung cancer treatment remains unclear, with concerns regarding insufficient surgical margins and increased complications. METHODS: Between February 2015 and December 2019, patients who underwent thoracoscopic MSS (n = 126) or MS (n = 678) for small ground-glass opacity (GGO) dominant lung cancer were examined. The primary endpoints were the procedure success rate (defined as resection with a surgical margin ≥2 cm or tumor size) and surgical margin. RESULTS: There were no significant differences in age, sex, smoking history, or comorbidities between the groups. Both groups achieved a success rate of 100%. No significant group differences were observed in the number of lymph nodes removed (p = 0.060), overall complications (p = 0.147), or major complications (p = 0.450). The MSS group had a smaller surgical margin (median, 17 vs. 21mm, p < 0.001) and longer operative time (median, 138 vs. 130 min, p = 0.005) than the MS group did. Propensity score-matched analysis of 122 pairs of patients revealed consistent results. Surgical margins were further compared based on the number of resected subsegments. The 1 subsegment group had the smallest median surgical margin, followed by the 2 and 3 subsegments groups (17, 20, and 23 mm, p < 0.001). CONCLUSIONS: Thoracoscopic MSS is an acceptable option for treating patients with small-sized GGO-dominant lung cancer. However, the close surgical margins and prolonged operative time should be considered.

Explaining and predicting the increased thorax injury in aged females: age and subject-specific thorax geometry coupled with improved bone constitutive models and age-specific material properties evaluated in side impact conditions.

Predicting and understanding thorax injury is fundamental for the assessment and development of safety systems to mitigate injury risk to the increasing and vulnerable aged population. While computational human models have contributed to the understanding of injury biomechanics, contemporary human body models have struggled to predict rib fractures and explain the increased incidence of injury in the aged population. The present study enhanced young and aged human body models (HBMs) by integrating a biofidelic cortical bone constitutive model and population-based bone material properties. The HBMs were evaluated using side impact sled tests assessed using chest compression and number of rib fractures. The increase in thoracic kyphosis and the associated change in rib angle with increasing age, led to increased rib torsional moment increasing the rib shear stress. Coupled with and improved cortical bone constitutive model and aged material properties, the higher resulting shear stress led to an increased number of rib fractures in the aged model. The importance of shear stress resulting from torsional load was further investigated using an isolated rib model. In contrast, HBM chest compression, a common thorax injury-associated metric, was insensitive to the aging factors studied. This study proposes an explanation for the increased incidence of thorax injury with increasing age reported in epidemiological data, and provides an enhanced understanding of human rib mechanics that will benefit assessment and design of future safety systems.

Screening and staging of chronic obstructive pulmonary disease with deep learning based on chest X-ray images and clinical parameters.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is underdiagnosed with the current gold standard measure pulmonary function test (PFT). A more sensitive and simple option for early detection and severity evaluation of COPD could benefit practitioners and patients. METHODS: In this multicenter retrospective study, frontal chest X-ray (CXR) images and related clinical information of 1055 participants were collected and processed. Different deep learning algorithms and transfer learning models were trained to classify COPD based on clinical data and CXR images from 666 subjects, and validated in internal test set based on 284 participants. External test including 105 participants was also performed to verify the generalization ability of the learning algorithms in diagnosing COPD. Meanwhile, the model was further used to evaluate disease severity of COPD by predicting different grads. RESULTS: The Ensemble model showed an AUC of 0.969 in distinguishing COPD by simultaneously extracting fusion features of clinical parameters and CXR images in internal test, better than models that used clinical parameters (AUC = 0.963) or images (AUC = 0.946) only. For the external test set, the AUC slightly declined to 0.934 in predicting COPD based on clinical parameters and CXR images. When applying the Ensemble model to determine disease severity of COPD, the AUC reached 0.894 for three-classification and 0.852 for five-classification respectively. CONCLUSION: The present study used DL algorithms to screen COPD and predict disease severity based on CXR imaging and clinical parameters. The models showed good performance and the approach might be an effective case-finding tool with low radiation dose for COPD diagnosis and staging.

Multi-scale and multi-view network for lung tumor segmentation.

Lung tumor segmentation in medical imaging is a critical step in the diagnosis and treatment planning for lung cancer. Accurate segmentation, however, is challenging due to the variability in tumor size, shape, and contrast against surrounding tissues. In this work, we present MSMV-Net, a novel deep learning architecture that integrates multi-scale multi-view (MSMV) learning modules and multi-scale uncertainty-based deep supervision (MUDS) for enhanced segmentation of lung tumors in computed tomography images. MSMV-Net capitalizes on the strengths of multi-view analysis and multi-scale feature extraction to address the limitations posed by small 3D lung tumors. The results indicate that MSMV-Net achieves state-of-the-art performance in lung tumor segmentation, recording a global Dice score of 55.60% on the LUNA dataset and 59.94% on the MSD dataset. Ablation studies conducted on the MSD dataset further validate that our method enhances segmentation accuracy.

CoGSPro-net:A graph neural network based on protein-protein interaction for classifying lung cancer-relatrd proteins.

This paper proposes a deep learning algorithm named CoGSPro for classifying lung cancer-related proteins. CoGSPro combines graph neural networks and attention mechanisms to extract key features from protein data and accurately classify proteins. It utilizes large-scale protein expression datasets to train and validate the model, enabling it to identify subtle patterns related to lung cancer. CoGSPro integrates protein-protein interaction network information to improve its predictive accuracy. The experimental results indicate that CoGSPro achieves cutting-edge performance, attaining an accuracy of 96.60% in the classification of lung cancer proteins, surpassing other baseline methods. Additionally, CoGSPro has uncovered new biomarkers for lung cancer, offering potential targets for early detection and treatment.