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首页> 外文期刊>Journal of medical systems >Inter-observer Variability Analysis of Automatic Lung Delineation in Normal and Disease Patients
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Inter-observer Variability Analysis of Automatic Lung Delineation in Normal and Disease Patients

机译:正常和疾病患者的肺自动划定观察者之间的变异性分析

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Human interaction has become almost mandatory for an automated medical system wishing to be accepted by clinical regulatory agencies such as Food and Drug Administration. Since this interaction causes variability in the gathered data, the inter-observer and intra-observer variability must be analyzed in order to validate the accuracy of the system. This study focuses on the variability from different observers that interact with an automated lung delineation system that relies on human interaction in the form of delineation of the lung borders. The database consists of High Resolution Computed Tomography (HRCT): 15 normal and 81 diseased patients' images taken retrospectively at five levels per patient. Three observers manually delineated the lungs borders independently and using software called ImgTracer T (AtheroPoint T, Roseville, CA, USA) to delineate the lung boundaries in all five levels of 3-D lung volume. The three observers consisted of Observer-1: lesser experienced novice tracer who is a resident in radiology under the guidance of radiologist, whereas Observer-2 and Observer-3 are lung image scientists trained by lung radiologist and biomedical imaging scientist and experts. The inter-observer variability can be shown by comparing each observer's tracings to the automated delineation and also by comparing each manual tracing of the observers with one another. The normality of the tracings was tested using D'Agostino-Pearson test and all observers tracings showed a normal P-value higher than 0.05. The analysis of variance (ANOVA) test between three observers and automated showed a P-value higher than 0.89 and 0.81 for the right lung (RL) and left lung (LL), respectively. The performance of the automated system was evaluated using Dice Similarity Coefficient (DSC), Jaccard Index (JI) and Hausdorff (HD) Distance measures. Although, Observer-1 has lesser experience compared to Obsever-2 and Obsever-3, the Observer Deterioration Factor (ODF) shows that Observer-1 has less than 10 % difference compared to the other two, which is under acceptable range as per our analysis. To compare between observers, this study used regression plots, Bland-Altman plots, two tailed T-test, Mann-Whiney, Chi-Squared tests which showed the following P-values for RL and LL: (i) Observer-1 and Observer-3 were: 0.55, 0.48, 0.29 for RL and 0.55, 0.59, 0.29 for LL; (ii) Observer-1 and Observer-2 were: 0.57, 0.50, 0.29 for RL and 0.54, 0.59, 0.29 for LL; (iii) Observer-2 and Observer-3 were: 0.98, 0.99, 0.29 for RL and 0.99, 0.99, 0.29 for LL. Further, CC and R-squared coefficients were computed between observers which came out to be 0.9 for RL and LL. All three observers however manage to show the feature that diseased lungs are smaller than normal lungs in terms of area.
机译:对于希望被食品和药物管理局等临床监管机构接受的自动化医疗系统,人机交互已几乎成为强制性的。由于这种相互作用导致所收集数据的可变性,因此必须分析观察者之间和观察者内部的变异性,以验证系统的准确性。这项研究的重点是不同观察者的变异性,这些变异性与依靠肺部边界描绘形式的人为交互作用的自动肺部描绘系统相互作用。该数据库由高分辨率计算机断层扫描(HRCT)组成:每位患者五个级别的15例正常患者和81例患病患者的图像。三名观察员独立地手动划定了肺部边界,并使用称为ImgTracer T(AtheroPoint T,美国加利福尼亚州罗斯维尔的AtheroPoint T)的软件在所有三个水平的3-D肺部容积中划定了肺部边界。这三名观察员由观察者1组成:经验较少的新手示踪剂,他们是放射科医生指导下的放射学常驻者,观察者2和观察者3是由肺放射学家和生物医学成像科学家和专家培训的肺图像科学家。观察者之间的可变性可以通过将每个观察者的描迹与自动描绘进行比较,也可以通过将观察者的每个手动描迹进行比较来显示。使用D'Agostino-Pearson检验测试了追踪的正态性,所有观察者的追踪均显示出正常的P值高于0.05。三个观察者之间的方差分析(ANOVA)测试自动进行,结果显示右肺(RL)和左肺(LL)的P值分别高于0.89和0.81。使用骰子相似系数(DSC),Jaccard指数(JI)和Hausdorff(HD)距离度量来评估自动化系统的性能。尽管与Obsever-2和Obsever-3相比,Observer-1的经验要少,但是观察者恶化因素(ODF)显示,与其他两个观察者相比,Observer-1的差异小于10%,根据我们的说法,该差异在可接受的范围内分析。为了比较观察者之间的差异,本研究使用了回归图,Bland-Altman图,两个尾部T检验,Mann-Whiney和Chi-Squared检验,这些检验显示了RL和LL的以下P值:(i)Observer-1和Observer -3是:对于RL为0.55、0.48、0.29,对于LL为0.55、0.59、0.29; (ii)观察员1和观察员2分别为:​​RL为0.57、0.50、0.29,LL为0.54、0.59、0.29; (iii)Observer-2和Observer-3分别为:RL为0.98、0.99、0.29,LL为0.99、0.99、0.29。此外,在观察者之间计算了CC和R平方系数,得出RL和LL为0.9。然而,所有三个观察者设法显示出患病的肺部面积小于正常肺部的特征。

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