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首页> 外文期刊>Japanese journal of radiology >Diagnostic performance and inter-operator variability of apparent diffusion coefficient analysis for differentiating pleomorphic adenoma and carcinoma ex pleomorphic adenoma: comparing one-point measurement and whole-tumor measurement including radiomics approach
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Diagnostic performance and inter-operator variability of apparent diffusion coefficient analysis for differentiating pleomorphic adenoma and carcinoma ex pleomorphic adenoma: comparing one-point measurement and whole-tumor measurement including radiomics approach

机译:诊断性能与算术间显式扩散系数分析的变化分析,用于区分性腺瘤和癌癌患者腺瘤:比较单点测量和全肿瘤测量,包括辐射瘤方法

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Background and purpose The purpose of this study was to compare the diagnostic performance between apparent diffusion coefficient (ADC) analysis of one-point measurement and whole-tumor measurement, including radiomics for differentiating pleomorphic adenoma (PA) from carcinoma ex pleomorphic adenoma (CXPA), and to evaluate the impact of inter-operator segmentation variability. Materials and methods One hundred and fifteen patients with PA and 22 with CXPA were included. Four radiologists with different experience independently placed one-point and whole-tumor ROIs and a radiomics-predictive model was constructed from the extracted imaging features. We calculated the area under the receiver-operator characteristic curve (AUC) for the diagnostic performance of imaging features and the radiomics-predictive model. Results AUCs of the imaging features from whole-tumor varied between readers (0.50-0.89). The most experienced radiologist (Reader 1) produced significantly high AUCs than less experienced radiologists (Reader 3 and 4; P = 0.01 and 0.009). AUCs were higher for the radiomics-predictive model (0.82-0.87) than for one-point (0.66-0.79) in all readers. Conclusion Some imaging features of whole-tumor and radiomics-predictive model had higher diagnostic performance than one-point. The diagnostic performance of imaging features from whole-tumor alone varied depending on operator experience. Operator experience appears less likely to affect diagnostic performance in the radiomics-predictive model.
机译:背景和目的本研究的目的是将表观扩散系数(ADC)分析的诊断性能进行了分析的单点测量和全肿瘤测量,包括用于区分Pleomorphic Adenoma(PA)的含有癌腺瘤(CXPA)的辐射症,并评估操作频道间分割变异性的影响。包括含有CXPA的1百万例PA和22患者的材料和方法。从提取的成像特征构建了四个不同经验的四个具有不同经验的放射科医生,并从提取的成像特征构建了射出量预测模型。我们计算了接收器操作员特征曲线(AUC)下的区域,用于成像特征的诊断性能和辐射族预测模型。结果读者之间的全肿瘤成像特征的AUC(0.50-0.89)。最经验丰富的放射科医生(读者1)产生明显高的AUC,而不是经验丰富的放射科学家(读者3和4; P = 0.01和0.009)。辐射瘤预测模型(0.82-0.87)比所有读者中的单点(0.66-0.79)更高。结论全肿瘤和辐射瘤预测模型的一些成像特征具有比单点更高的诊断性能。单独从整个肿瘤的成像特征的诊断性能取决于操作员体验。操作员经验似乎不太可能影响辐射瘤预测模型中的诊断性能。

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