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Investigation and Application of High Megavoltage X-Ray Imaging Mode in Radiotherapy
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作者 Quanshi Zhang Xiwen Wang +5 位作者 qiyin sun Yuehui Jin Yun Li Ziyu Li Tao sun Liang Wang 《International Journal of Medical Physics, Clinical Engineering and Radiation Oncology》 2016年第1期42-50,共9页
After drawbacks and shortages of using conventional kV or MV imaging mode were analyzed, this study proposes a new position verification mode with using the energy larger than 15 MeV or nominal accelerating potential ... After drawbacks and shortages of using conventional kV or MV imaging mode were analyzed, this study proposes a new position verification mode with using the energy larger than 15 MeV or nominal accelerating potential greater than 25 MV X-Ray. The new position verification mode is named HMV imaging mode. Along with the comparison of theoretical analyses, phantom experiments and clinical results to the original imaging modes, this report is going to demonstrate the HMV imaging mode is superior to traditional kV and MV imaging modes. This report first theoretically analyzed three main effects of X-ray interacting with medium by numerous equations and compared their mass attenuation coefficient with different types of tissue. X-ray irradiated on a “Catphan 500” cylinder phantom with different energies to verify these theoretical results. Furthermore, based on phantom experiments’ results, we have done numerous clinical trials and comparisons with patient’s clinical results. The theoretical and experimental results illustrate that the scanned images from HMV mode have a good quality and have ability to identify different tissue components clearly. HMV imaging mode overcomes drawbacks of position verification from both kV and MV level imaging mode as well as keeping advantages of kV and MV imaging mode. The result indicates that HMV is a good position verification mode in radiotherapy. 展开更多
关键词 High Energy X-Ray X-Ray Imaging Mode Position Verification Reaction Cross-Section
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急性心肌梗死患者预后不良的影响因素分析及其风险预测列线图模型构建
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作者 李国栋 许海斌 孙启银 《中国基层医药》 CAS 2023年第10期1483-1488,共6页
目的探究急性心肌梗死(AMI)患者预后不良的影响因素,并构建其风险预测列线图模型。方法研究对象为湖州市第一人民医院2018年6月至2021年6月接诊的AMI患者173例,根据发生心肌梗死6个月后随访结果将其分为预后良好组(n=130)和预后不良组(n... 目的探究急性心肌梗死(AMI)患者预后不良的影响因素,并构建其风险预测列线图模型。方法研究对象为湖州市第一人民医院2018年6月至2021年6月接诊的AMI患者173例,根据发生心肌梗死6个月后随访结果将其分为预后良好组(n=130)和预后不良组(n=43)。采用回顾性分析研究方法,比较两组患者临床资料的差异;通过LASSO回归分析初步筛选潜在影响因素;通过logistic回归分析方法探究AMI患者预后不良的影响因素;列线图模型运用R 4.2.6语言“rms”包构建,并通过绘制受试者工作特征曲线(ROC曲线)、校准曲线、决策曲线评价模型的区分度、校准度及有效性,模型验证采用Bootstrap法进行内部验证(重复抽样1000次)。结果两组患者罪犯血管、Killip分级、血管开通时间、肌钙蛋白(cTnI)、高血压史、N末端B型脑钠肽前体(NT-proBNP)、糖尿病史、肌酐、高脂血症史、左室射血分数(LVEF)、吸烟史、肌酸激酶同工酶(CK-MB)比较,差异均有统计学意义(均P<0.05)。采用LASSO回归模型筛选出7个潜在的影响因素,分别为糖尿病史、梗死血管-前降支、KillipⅣ级、血管开通时间、cTnI、NT-proBNP、LVEF。logistic回归分析显示,血管开通时间(OR=0.171,95%CI:0.053~0.548,P=0.003)、cTnI(OR=0.201,95%CI:0.079~0.510,P=0.001)、LVEF(OR=1.469,95%CI:1.167~1.847,P=0.001)、NT-proBNP(OR=0.996,95%CI:0.993~1.00,P=0.025)是AMI患者预后不良的独立影响因素(均P<0.05),线性回归分析提示模型无明显共线性(VIF<10)。基于logistic回归分析提示的4个影响因素构建AMI患者预后不良风险预测的列线图模型,ROC曲线显示该模型的曲线下面积为0.979[95%CI(0.959,0.999)],一致性指数为0.934;模型的校准曲线与理想曲线接近;决策曲线分析提示,当该模型预测的概率阈值为0.61~0.99时,模型预测价值较优越。结论AMI患者预后不良的影响因素有血管开通时间、cTnI、NT-proBNP、LVEF等,构建的列线图模型对 展开更多
关键词 急性心肌梗死 预后不良 影响因素 LASSO回归 LOGISTIC回归 列线图模型 ROC曲线 决策曲线
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