Appropriate management of penetrating trauma to the thorax requires knowledge of vulnating agents, as well as the principles of ballistic injury. The importance of the approach’s choice for surgical exploration of th...Appropriate management of penetrating trauma to the thorax requires knowledge of vulnating agents, as well as the principles of ballistic injury. The importance of the approach’s choice for surgical exploration of these injuries, and parietal damage, is an essential factor in decision making in the management and definition of the therapeutic strategy for these injuries. The authors report a clinical case of a penetrating traumatic ballistic wound of the thorax managed in a context of difficult diagnosis in the surgical Unit of the CHUPB.展开更多
Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were col...Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were collected(segmented dataset),and chest CT data of 984 patients were screened from the COVID 19-CT dataset(10 cases were randomly selected as whole test dataset,the remaining 974 cases were selected as layer selection dataset).T7—T8 layer was classified based on convolutional neural network(CNN)derived networks,including ResNet,ResNeXt,MobileNet,ShuffleNet,DenseNet,EfficientNet and ConvNeXt,then the accuracy,precision,recall and specificity were used to evaluate the performance of layer selection dataset.The skeletal muscle(SM),subcutaneous adipose tissue(SAT),intermuscular adipose tissue(IMAT)and visceral adipose tissue(VAT)were segmented using classical fully CNN(FCN)derived network,including FCN,SegNet,UNet,Attention UNet,UNET++,nnUNet,UNeXt and CMUNeXt,then Dice similarity coefficient(DSC),intersection over union(IoU)and 95 Hausdorff distance(HD)were used to evaluate the performance of segmented dataset.The automatic body composition analysis system was constructed based on optimal layer selection network and segmentation network,the mean absolute error(MAE),root mean squared error(RMSE)and standard deviation(SD)of MAE were used to evaluate the performance of automatic system for testing the whole test dataset.Results The accuracy,precision,recall and specificity of DenseNet network for automatically classifying T7—T8 layer from chest CT images was 95.06%,84.83%,92.27%and 95.78%,respectively,which were all higher than those of the other layer selection networks.In segmentation of SM,SAT,IMAT and overall,DSC and IoU of UNet++network were all higher,while 95HD of UNet++network were all lower than those of the other segmentation networks.Using DenseNet as the layer selection network and UNet++as the segmentation network,MAE of the automatic body composition analysis system for predicting SM,SAT,IMAT,VAT and MAE was 27.09,6.95,6.65 and 3.35 cm 2,respectively.Conclusion The body composition analysis system based on chest CT could be used to assess content of chest muscle and adipose.Among them,the UNet++network had better segmentation performance in adipose tissue than SM.展开更多
为研究真实工况下人员在爆炸冲击波作用下的动态响应特性,开展某型云爆弹静爆作用下工事内仿人形装置(Anthropomorphic Test Device,ATD)和绵羊的毁伤试验研究。采用爆炸测试装置和简易假人作为研究对象,通过6发爆炸试验分析爆炸冲击波...为研究真实工况下人员在爆炸冲击波作用下的动态响应特性,开展某型云爆弹静爆作用下工事内仿人形装置(Anthropomorphic Test Device,ATD)和绵羊的毁伤试验研究。采用爆炸测试装置和简易假人作为研究对象,通过6发爆炸试验分析爆炸冲击波在ATD表面传播规律,开展2种人员损伤预测模型的对比分析。研究结果表明:在本试验工况下,冲击波和崩落的混凝土碎块是主要的毁伤元;爆炸冲击波在ATD表面首先发生反射,随后绕射至其他部位,压力曲线表现出非典型冲击波特征,反射叠加效应明显;在典型冲击波特征正压作用时间区间内,由于Axelsson损伤模型线性阻尼项的影响,求解的胸壁运动速度呈现出先增大至峰值后降低的现象;Axelsson损伤模型与UFC 3-340-02规范相比,在人员损伤预测方面相对保守。所得研究结果可为工程应用及毁伤评估提供参考。展开更多
<strong>Objective:</strong> To explore the characteristics and mechanisms of serious injuries of chest caused by road traffic accidents. <strong>Methods:</strong> Totally 112 autopsy cases with...<strong>Objective:</strong> To explore the characteristics and mechanisms of serious injuries of chest caused by road traffic accidents. <strong>Methods:</strong> Totally 112 autopsy cases with chest injuries in the urban of Jingzhou road traffic accidents were collected. Systematic review and analysis of the general information, postmortem examinations and assessments of chest injury had carried out from Feb. 2016 to Mar. 2018. <strong>Results:</strong> Average age of the victims was 52.2 years and the ratio of male to female deaths was 2.39:1. The proportion of motor-cyclists and pedestrians increased significantly. The overwhelming majority of accident vehicles were motorcycles and bicycles. Fractures of ribs and pulmonary contusion were the most common injuries. Craniocerebral and abdominal injuries were the most common associated injuries. <strong>Conclusion:</strong> Fractures of ribs and pulmonary contusion were the most common features of fatal road traffic injuries, often associated with vitreoretinal damage and serious multiple damages. These features reflect the characteristics of great violence in traffic accidents, which provides the evidence of identification of violent injuries.展开更多
A simplified finite element model of a human thorax had been developed for probing into the mechani- cal response in simple and complex blast environments. The human thorax model was first created by CT images with bl...A simplified finite element model of a human thorax had been developed for probing into the mechani- cal response in simple and complex blast environments. The human thorax model was first created by CT images with blast loading applied via a coupled arbitrary Lagrangian- Eulerian method, allowing for a variety of loads to be considered. The goal is to analyze the maximum stress distri- butions of lung tissue and peak inward thorax wall velocity and to know the possible regions and levels of lung injury. In parallel, a mathematical model has been modified from the Lobdell model to investigate the detailed percentage of lung injury at each level. The blast loadings around the human tho- rax were obtained from the finite element model, and were then applied in the mathematical model as the boundary con- ditions to predict the normalized work of the human thorax lung. The present results are found in agreement with the modified Bowen curves and the results predicted by Axels- son＇s model.展开更多
BACKGROUND The coronavirus disease 2019(COVID-19)pandemic is continuing.The disease most commonly affects the lungs.Since the beginning of the pandemic thorax computed tomography(CT)has been an indispensable imaging m...BACKGROUND The coronavirus disease 2019(COVID-19)pandemic is continuing.The disease most commonly affects the lungs.Since the beginning of the pandemic thorax computed tomography(CT)has been an indispensable imaging method for diagnosis and follow-up.The disease is tried to be controlled with vaccines.Vaccination reduces the possibility of a severe course of the disease.AIM The aim of this study is to investigate whether the vaccination status of patients hospitalized due to COVID-19 has an effect on the CT severity score(CT-SS)and CORADS score obtained during hospitalization.METHODS The files of patients hospitalized between April 1,2021 and April 1,2022 due to COVID-19 were retrospectively reviewed.A total of 224 patients who were older than 18 years of age,whose vaccination status was accessible,whose severe acute respiratory syndrome coronavirus 2 polymerase chain reaction result was positive,and who had a Thorax CT scan during hospitalization were included in the study.RESULTS Among the patients included in the study,52.2%were female and the mean age was 61.85 years.The patients applied to the hospital on the average 7th day of their complaints.While 63 patients were unvaccinated(Group 1),20 were vaccinated with a single dose of CoronaVac(Group 2),24 with a single dose of BioNTech(Group 3),38 with 2 doses of CoronaVac(Group 4),40 with 2 doses of BioNTech(Group 5),and 39 with 3 doses of vaccine(2 doses of CoronaVac followed by a single dose of BioNTech,Group 6).CT-SS ranged from 5 to 23,with a mean of 12.17.RESULTS CT-SS mean of the groups were determined as 14.17,13.35,11.58,10.87,11.28,10.85,respectively.Accordingly,as a result of the comparisons between the groups,the CT-SS levels of the unvaccinated patients found to be significantly higher than the other groups.As the vaccination rates increased,the rate of typical COVID-19 findings on CT was found to be significantly lower.CONCLUSION Increased vaccination rates in COVID-19 patients reduce the probability of typical COVID-19 symptoms in the lungs.It also reduces the risk of severe disease and decreases CT Severity Scores.This may lead to a loss of importance of Thorax CT in the diagnosis of COVID-19 pneumonia as the end of the pandemic approaches.展开更多
文摘Appropriate management of penetrating trauma to the thorax requires knowledge of vulnating agents, as well as the principles of ballistic injury. The importance of the approach’s choice for surgical exploration of these injuries, and parietal damage, is an essential factor in decision making in the management and definition of the therapeutic strategy for these injuries. The authors report a clinical case of a penetrating traumatic ballistic wound of the thorax managed in a context of difficult diagnosis in the surgical Unit of the CHUPB.
文摘Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were collected(segmented dataset),and chest CT data of 984 patients were screened from the COVID 19-CT dataset(10 cases were randomly selected as whole test dataset,the remaining 974 cases were selected as layer selection dataset).T7—T8 layer was classified based on convolutional neural network(CNN)derived networks,including ResNet,ResNeXt,MobileNet,ShuffleNet,DenseNet,EfficientNet and ConvNeXt,then the accuracy,precision,recall and specificity were used to evaluate the performance of layer selection dataset.The skeletal muscle(SM),subcutaneous adipose tissue(SAT),intermuscular adipose tissue(IMAT)and visceral adipose tissue(VAT)were segmented using classical fully CNN(FCN)derived network,including FCN,SegNet,UNet,Attention UNet,UNET++,nnUNet,UNeXt and CMUNeXt,then Dice similarity coefficient(DSC),intersection over union(IoU)and 95 Hausdorff distance(HD)were used to evaluate the performance of segmented dataset.The automatic body composition analysis system was constructed based on optimal layer selection network and segmentation network,the mean absolute error(MAE),root mean squared error(RMSE)and standard deviation(SD)of MAE were used to evaluate the performance of automatic system for testing the whole test dataset.Results The accuracy,precision,recall and specificity of DenseNet network for automatically classifying T7—T8 layer from chest CT images was 95.06%,84.83%,92.27%and 95.78%,respectively,which were all higher than those of the other layer selection networks.In segmentation of SM,SAT,IMAT and overall,DSC and IoU of UNet++network were all higher,while 95HD of UNet++network were all lower than those of the other segmentation networks.Using DenseNet as the layer selection network and UNet++as the segmentation network,MAE of the automatic body composition analysis system for predicting SM,SAT,IMAT,VAT and MAE was 27.09,6.95,6.65 and 3.35 cm 2,respectively.Conclusion The body composition analysis system based on chest CT could be used to assess content of chest muscle and adipose.Among them,the UNet++network had better segmentation performance in adipose tissue than SM.
文摘为研究真实工况下人员在爆炸冲击波作用下的动态响应特性,开展某型云爆弹静爆作用下工事内仿人形装置(Anthropomorphic Test Device,ATD)和绵羊的毁伤试验研究。采用爆炸测试装置和简易假人作为研究对象,通过6发爆炸试验分析爆炸冲击波在ATD表面传播规律,开展2种人员损伤预测模型的对比分析。研究结果表明:在本试验工况下,冲击波和崩落的混凝土碎块是主要的毁伤元;爆炸冲击波在ATD表面首先发生反射,随后绕射至其他部位,压力曲线表现出非典型冲击波特征,反射叠加效应明显;在典型冲击波特征正压作用时间区间内,由于Axelsson损伤模型线性阻尼项的影响,求解的胸壁运动速度呈现出先增大至峰值后降低的现象;Axelsson损伤模型与UFC 3-340-02规范相比,在人员损伤预测方面相对保守。所得研究结果可为工程应用及毁伤评估提供参考。
文摘<strong>Objective:</strong> To explore the characteristics and mechanisms of serious injuries of chest caused by road traffic accidents. <strong>Methods:</strong> Totally 112 autopsy cases with chest injuries in the urban of Jingzhou road traffic accidents were collected. Systematic review and analysis of the general information, postmortem examinations and assessments of chest injury had carried out from Feb. 2016 to Mar. 2018. <strong>Results:</strong> Average age of the victims was 52.2 years and the ratio of male to female deaths was 2.39:1. The proportion of motor-cyclists and pedestrians increased significantly. The overwhelming majority of accident vehicles were motorcycles and bicycles. Fractures of ribs and pulmonary contusion were the most common injuries. Craniocerebral and abdominal injuries were the most common associated injuries. <strong>Conclusion:</strong> Fractures of ribs and pulmonary contusion were the most common features of fatal road traffic injuries, often associated with vitreoretinal damage and serious multiple damages. These features reflect the characteristics of great violence in traffic accidents, which provides the evidence of identification of violent injuries.
文摘A simplified finite element model of a human thorax had been developed for probing into the mechani- cal response in simple and complex blast environments. The human thorax model was first created by CT images with blast loading applied via a coupled arbitrary Lagrangian- Eulerian method, allowing for a variety of loads to be considered. The goal is to analyze the maximum stress distri- butions of lung tissue and peak inward thorax wall velocity and to know the possible regions and levels of lung injury. In parallel, a mathematical model has been modified from the Lobdell model to investigate the detailed percentage of lung injury at each level. The blast loadings around the human tho- rax were obtained from the finite element model, and were then applied in the mathematical model as the boundary con- ditions to predict the normalized work of the human thorax lung. The present results are found in agreement with the modified Bowen curves and the results predicted by Axels- son＇s model.
文摘BACKGROUND The coronavirus disease 2019(COVID-19)pandemic is continuing.The disease most commonly affects the lungs.Since the beginning of the pandemic thorax computed tomography(CT)has been an indispensable imaging method for diagnosis and follow-up.The disease is tried to be controlled with vaccines.Vaccination reduces the possibility of a severe course of the disease.AIM The aim of this study is to investigate whether the vaccination status of patients hospitalized due to COVID-19 has an effect on the CT severity score(CT-SS)and CORADS score obtained during hospitalization.METHODS The files of patients hospitalized between April 1,2021 and April 1,2022 due to COVID-19 were retrospectively reviewed.A total of 224 patients who were older than 18 years of age,whose vaccination status was accessible,whose severe acute respiratory syndrome coronavirus 2 polymerase chain reaction result was positive,and who had a Thorax CT scan during hospitalization were included in the study.RESULTS Among the patients included in the study,52.2%were female and the mean age was 61.85 years.The patients applied to the hospital on the average 7th day of their complaints.While 63 patients were unvaccinated(Group 1),20 were vaccinated with a single dose of CoronaVac(Group 2),24 with a single dose of BioNTech(Group 3),38 with 2 doses of CoronaVac(Group 4),40 with 2 doses of BioNTech(Group 5),and 39 with 3 doses of vaccine(2 doses of CoronaVac followed by a single dose of BioNTech,Group 6).CT-SS ranged from 5 to 23,with a mean of 12.17.RESULTS CT-SS mean of the groups were determined as 14.17,13.35,11.58,10.87,11.28,10.85,respectively.Accordingly,as a result of the comparisons between the groups,the CT-SS levels of the unvaccinated patients found to be significantly higher than the other groups.As the vaccination rates increased,the rate of typical COVID-19 findings on CT was found to be significantly lower.CONCLUSION Increased vaccination rates in COVID-19 patients reduce the probability of typical COVID-19 symptoms in the lungs.It also reduces the risk of severe disease and decreases CT Severity Scores.This may lead to a loss of importance of Thorax CT in the diagnosis of COVID-19 pneumonia as the end of the pandemic approaches.
