目的探讨剪切波弹性成像定量分析乳腺病灶周边硬度对判断病灶良、恶性的诊断价值。方法回顾性分析2018年12月至2020年5月经中国科学技术大学附属第一医院(安徽省立医院)南区诊断为乳腺癌的60例患者临床资料,共60个病灶,其中良性病灶31个...目的探讨剪切波弹性成像定量分析乳腺病灶周边硬度对判断病灶良、恶性的诊断价值。方法回顾性分析2018年12月至2020年5月经中国科学技术大学附属第一医院(安徽省立医院)南区诊断为乳腺癌的60例患者临床资料,共60个病灶,其中良性病灶31个,恶性病灶29个。测量并记录每个病灶弹性模量值[最大值(E_(max))、最小值(E_(min))、平均值(E_(mean))、标准差(E_(sd))]和病灶周围区域(Shell 1.0、2.0、3.0 mm)的弹性模量值,同时比较“硬环征”的表现情况。比较良、恶性病灶及周围组织弹性模量值之间的差异。以病理诊断为金标准,绘制受试者工作特性曲线(ROC),比较各弹性模量的曲线下面积(AUC),获得诊断价值最大的弹性模量。最后比较BI-RADS分类、弹性成像及两者联合的诊断价值。结果良性组患者年龄小于恶性组,差异有统计学意义(P<0.05)。良、恶性组病灶最大径的差异无统计学意义(P>0.05)。恶性组“硬环征”发生率高于良性组,差异有统计学意义(P<0.05)。良、恶性组病灶内部及周围的弹性模量E_(min)比较,差异无统计学意义(P>0.05);恶性组E_(mean)、E_(max)、E_(sd)均高于良性组,差异有统计学意义(P<0.05)。各组弹性模量(E_(mean)、E_(max)、E_(sd))的ROC显示,Shell 2.0 mm E_(max)的AUC为所有弹性模量中最大,为0.843,截断值为97.06,敏感度82.76%,特异度74.19%。BIRADS分类、Shell 2.0 mm E_(max)两者联合获得的ROC曲线,AUC值为0.965,敏感度93.1%,特异度93.5%。结论常规超声BI-RADS分类、剪切波超声弹性成像技术相联合,能明显提高乳腺癌患者良、恶性病灶诊断准确率。展开更多
Technological trends in the automotive industry toward a software-defined and autonomous vehicle require a reassessment of today’s vehicle development process.The validation process soaringly shapes after starting wi...Technological trends in the automotive industry toward a software-defined and autonomous vehicle require a reassessment of today’s vehicle development process.The validation process soaringly shapes after starting with hardware-in-the-loop testing of control units and reproducing real-world maneuvers and physical interaction chains.Here,the road-to-rig approach offers a vast potential to reduce validation time and costs significantly.The present research study investigates the maneuver reproduction of drivability phenomena at a powertrain test bed.Although drivability phenomena occur in the frequency range of most up to 30∙Hz,the design and characteristics substantially impact the test setup’s validity.By utilization of modal analysis,the influence of the test bed on the mechanical characteristic is shown.Furthermore,the sensitivity of the natural modes of each component,from either specimen or test bed site,is determined.In contrast,the uncertainty of the deployed measurement equipment also affects the validity.Instead of an accuracy class indication,we apply the ISO/IEC Guide 98 to the measurement equipment and the test bed setup to increase the fidelity of the validation task.In conclusion,the present paper contributes to a traceable validity determination of the road-to-rig approach by providing objective metrics and methods.展开更多
文摘目的探讨剪切波弹性成像定量分析乳腺病灶周边硬度对判断病灶良、恶性的诊断价值。方法回顾性分析2018年12月至2020年5月经中国科学技术大学附属第一医院(安徽省立医院)南区诊断为乳腺癌的60例患者临床资料,共60个病灶,其中良性病灶31个,恶性病灶29个。测量并记录每个病灶弹性模量值[最大值(E_(max))、最小值(E_(min))、平均值(E_(mean))、标准差(E_(sd))]和病灶周围区域(Shell 1.0、2.0、3.0 mm)的弹性模量值,同时比较“硬环征”的表现情况。比较良、恶性病灶及周围组织弹性模量值之间的差异。以病理诊断为金标准,绘制受试者工作特性曲线(ROC),比较各弹性模量的曲线下面积(AUC),获得诊断价值最大的弹性模量。最后比较BI-RADS分类、弹性成像及两者联合的诊断价值。结果良性组患者年龄小于恶性组,差异有统计学意义(P<0.05)。良、恶性组病灶最大径的差异无统计学意义(P>0.05)。恶性组“硬环征”发生率高于良性组,差异有统计学意义(P<0.05)。良、恶性组病灶内部及周围的弹性模量E_(min)比较,差异无统计学意义(P>0.05);恶性组E_(mean)、E_(max)、E_(sd)均高于良性组,差异有统计学意义(P<0.05)。各组弹性模量(E_(mean)、E_(max)、E_(sd))的ROC显示,Shell 2.0 mm E_(max)的AUC为所有弹性模量中最大,为0.843,截断值为97.06,敏感度82.76%,特异度74.19%。BIRADS分类、Shell 2.0 mm E_(max)两者联合获得的ROC曲线,AUC值为0.965,敏感度93.1%,特异度93.5%。结论常规超声BI-RADS分类、剪切波超声弹性成像技术相联合,能明显提高乳腺癌患者良、恶性病灶诊断准确率。
文摘Technological trends in the automotive industry toward a software-defined and autonomous vehicle require a reassessment of today’s vehicle development process.The validation process soaringly shapes after starting with hardware-in-the-loop testing of control units and reproducing real-world maneuvers and physical interaction chains.Here,the road-to-rig approach offers a vast potential to reduce validation time and costs significantly.The present research study investigates the maneuver reproduction of drivability phenomena at a powertrain test bed.Although drivability phenomena occur in the frequency range of most up to 30∙Hz,the design and characteristics substantially impact the test setup’s validity.By utilization of modal analysis,the influence of the test bed on the mechanical characteristic is shown.Furthermore,the sensitivity of the natural modes of each component,from either specimen or test bed site,is determined.In contrast,the uncertainty of the deployed measurement equipment also affects the validity.Instead of an accuracy class indication,we apply the ISO/IEC Guide 98 to the measurement equipment and the test bed setup to increase the fidelity of the validation task.In conclusion,the present paper contributes to a traceable validity determination of the road-to-rig approach by providing objective metrics and methods.
