Objective:Non-diagnostic thyroid nodules(Bethesda I)account for 5%-20%of all thyroid nodules.Accurate differentiation of benign and malignant nodules can reduce unnecessary surgeries and repeat biopsies.Herein we eval...Objective:Non-diagnostic thyroid nodules(Bethesda I)account for 5%-20%of all thyroid nodules.Accurate differentiation of benign and malignant nodules can reduce unnecessary surgeries and repeat biopsies.Herein we evaluated the diagnostic efficacy of multigene testing in non-diagnostic thyroid nodules and developed a predictive model integrating molecular and clinical data.Methods:In this prospective cohort study,1,175 patients with thyroid nodules were evaluated for inclusion,of which 218 patients with Bethesda I nodules met our inclusion criteria.The primary outcome was diagnostic accuracy of molecular testing,and the secondary outcome was the performance of a predictive model integrating molecular and clinical data.Results:Final histopathology identified 165 benign and 53 malignant nodules.Molecular testing detected 10distinct point mutations and seven gene fusions.Among benign nodules,147 tested negative and 18 tested positive,whereas 44 malignant nodules tested positive and nine tested negative.In nodules with ultrasound grades 4-5 and fine-needle aspiration cytology(FNAC)results categorized as non-diagnostic,molecular testing achieved sensitivity of 83.00%,specificity of 89.00%,positive predictive value(PPV)of 71.00%,negative predictive value(NPV)of94.20%,and overall accuracy of 87.60%.The predictive model incorporated 18 clinical and 19 molecular features.Eleven non-zero predictors were selected via least absolute shrinkage and selection operator(LASSO),and the model achieved area under curve(AUC)of 0.95 in the training set and 0.96 in the testing set.Decision curve analysis indicated greater net benefit compared with conventional diagnostic approaches.Conclusions:Molecular testing significantly improved diagnostic accuracy for Bethesda I thyroid nodules.Integrating molecular and clinical data enabled the development of a robust predictive model,facilitating precise,individualized patient management and reducing the need for repeat FNAC and unnecessary surgeries.展开更多
虚拟场景中的人体结构建模采用层次建模法,将人体模型看作由段和连接段的节点组成。并利用Multigen工具集中的degree of Freedom技术,构建人体模型,定义人体关节信息。通过对节点的属性赋值,设置关节点的位移和旋转角度等特征,实现虚拟...虚拟场景中的人体结构建模采用层次建模法,将人体模型看作由段和连接段的节点组成。并利用Multigen工具集中的degree of Freedom技术,构建人体模型,定义人体关节信息。通过对节点的属性赋值,设置关节点的位移和旋转角度等特征,实现虚拟场景中的人体运动仿真,丰富了虚拟场景的真实感和交互性。展开更多
基金supported by Military Key Clinical Speciality(No.51561Z23612)Chongqing Talents Project(No.cstc2022ycjh-bgzxm0091)。
文摘Objective:Non-diagnostic thyroid nodules(Bethesda I)account for 5%-20%of all thyroid nodules.Accurate differentiation of benign and malignant nodules can reduce unnecessary surgeries and repeat biopsies.Herein we evaluated the diagnostic efficacy of multigene testing in non-diagnostic thyroid nodules and developed a predictive model integrating molecular and clinical data.Methods:In this prospective cohort study,1,175 patients with thyroid nodules were evaluated for inclusion,of which 218 patients with Bethesda I nodules met our inclusion criteria.The primary outcome was diagnostic accuracy of molecular testing,and the secondary outcome was the performance of a predictive model integrating molecular and clinical data.Results:Final histopathology identified 165 benign and 53 malignant nodules.Molecular testing detected 10distinct point mutations and seven gene fusions.Among benign nodules,147 tested negative and 18 tested positive,whereas 44 malignant nodules tested positive and nine tested negative.In nodules with ultrasound grades 4-5 and fine-needle aspiration cytology(FNAC)results categorized as non-diagnostic,molecular testing achieved sensitivity of 83.00%,specificity of 89.00%,positive predictive value(PPV)of 71.00%,negative predictive value(NPV)of94.20%,and overall accuracy of 87.60%.The predictive model incorporated 18 clinical and 19 molecular features.Eleven non-zero predictors were selected via least absolute shrinkage and selection operator(LASSO),and the model achieved area under curve(AUC)of 0.95 in the training set and 0.96 in the testing set.Decision curve analysis indicated greater net benefit compared with conventional diagnostic approaches.Conclusions:Molecular testing significantly improved diagnostic accuracy for Bethesda I thyroid nodules.Integrating molecular and clinical data enabled the development of a robust predictive model,facilitating precise,individualized patient management and reducing the need for repeat FNAC and unnecessary surgeries.
文摘虚拟场景中的人体结构建模采用层次建模法,将人体模型看作由段和连接段的节点组成。并利用Multigen工具集中的degree of Freedom技术,构建人体模型,定义人体关节信息。通过对节点的属性赋值,设置关节点的位移和旋转角度等特征,实现虚拟场景中的人体运动仿真,丰富了虚拟场景的真实感和交互性。
