Detection of small pulmonary nodules is the goal of lung cancer screening. Computer-aided detection (CAD) systems are recommended to use in lung cancer computed tomography (CT) screening to increase the accuracy of no...Detection of small pulmonary nodules is the goal of lung cancer screening. Computer-aided detection (CAD) systems are recommended to use in lung cancer computed tomography (CT) screening to increase the accuracy of nodule detection. Size and density of lung nodules are primary factors in determining the risk of malignancy. Therefore, purpose of this study is to apply computer-simulated virtual nodules based on the point spread function (PSF) measured in same scanner (maintaining spatial resolution condition) to assess the CAD system performance dependence on nodule size and density. Virtual nodules with density differences between lung background and nodule density (ΔCT) values (200, 300 and 400 HU) and different sizes (4 to 8 mm) were generated and fused on clinical images. CAD detection was performed and free-response receiver operating characteristic (FROC) curves were obtained. Results show that both density and size of virtual nodules can affect detection efficiency. Detailed results are possible to use for quantitative analysis of a CAD system performance. This study suggests that PSF-based virtual nodules could be effectively used to assess the lung cancer CT screening CAD system performance dependence on nodule size and density.展开更多
文摘Detection of small pulmonary nodules is the goal of lung cancer screening. Computer-aided detection (CAD) systems are recommended to use in lung cancer computed tomography (CT) screening to increase the accuracy of nodule detection. Size and density of lung nodules are primary factors in determining the risk of malignancy. Therefore, purpose of this study is to apply computer-simulated virtual nodules based on the point spread function (PSF) measured in same scanner (maintaining spatial resolution condition) to assess the CAD system performance dependence on nodule size and density. Virtual nodules with density differences between lung background and nodule density (ΔCT) values (200, 300 and 400 HU) and different sizes (4 to 8 mm) were generated and fused on clinical images. CAD detection was performed and free-response receiver operating characteristic (FROC) curves were obtained. Results show that both density and size of virtual nodules can affect detection efficiency. Detailed results are possible to use for quantitative analysis of a CAD system performance. This study suggests that PSF-based virtual nodules could be effectively used to assess the lung cancer CT screening CAD system performance dependence on nodule size and density.
文摘目的探讨可溶性E-钙黏蛋白(soluble E-cadherin,SE-CAD)、胸苷激酶-1(thymidine kinase 1,TK-1)在非小细胞肺癌(NSCLC)患者血清中的水平,并分析其与附睾蛋白4(HE4)、癌胚抗原(CEA)、细胞角蛋白19片段(CYFRA21-1)联合检测在NSCLC诊断中的临床应用价值。方法收集本院2016年1月至2018年1月期间初诊NSCLC患者86例、小细胞肺癌患者45例、同期良性疾病患者42例、同期初诊其他恶性肿瘤(除肺癌外)患者30例、健康受试者的血清标本40例,应用液态芯片技术对受试者血清标本进行CEA、CYFRA21-1水平检测,ELISA方法检测SE-CAD、TK-1、HE4。结果①非小细胞肺癌患者血清中SE-CAD水平明显高于良性对照组、正常对照组( P <0.05),差异具有统计学意义,但与小细胞肺癌组及其他恶性肿瘤组比较差异无统计学意义( P >0.05);②非小细胞肺癌组患者血清 TK1 与CYFRA21-1水平明显高于良性对照组、小细胞肺癌组、其他恶性肿瘤组和健康对照组,差异均有统计学意义(均 P <0.05)。③单项检测时,CYFRA21-1对非小细胞肺癌的诊断灵敏度最高,为87.2%,TK-1的诊断特异性最高。5种肿瘤标志物联合检测,灵敏度高达93.2%,特异性有所降低为85.7%。结论 SE-CAD、TK1 与CYFRA21-1均可作为鉴别良恶性肿瘤的检验指标,联合HE4、CEA、CYFRA21-1等指标对非小细胞肺癌诊断的灵敏度远高于单项检测。
