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The Lung Image Database Consortium (LIDC): a comparison of different size metrics for pulmonary nodule measurements.

机译:肺图像数据库协会(LIDC):肺结节测量的不同大小指标的比较。

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RATIONALE AND OBJECTIVES: The goal was to investigate the effects of choosing between different metrics in estimating the size of pulmonary nodules as a factor both of nodule characterization and of performance of computer aided detection systems, because the latter are always qualified with respect to a given size range of nodules. MATERIALS AND METHODS: This study used 265 whole-lung CT scans documented by the Lung Image Database Consortium (LIDC) using their protocol for nodule evaluation. Each inspected lesion was reviewed independently by four experienced radiologists who provided boundary markings for nodules larger than 3 mm. Four size metrics, based on the boundary markings, were considered: a unidimensional and two bidimensional measures on a single image slice and a volumetric measurement based on all the image slices. The radiologist boundaries were processed and those with four markings were analyzed to characterize the interradiologist variation, while those with at least one marking were used to examine the difference between the metrics. RESULTS: The processing of the annotations found 127 nodules marked by all of the four radiologists and an extended set of 518 nodules each having at least one observation with three-dimensional sizes ranging from 2.03 to 29.4 mm (average 7.05 mm, median 5.71 mm). A very high interobserver variation was observed for all these metrics: 95% of estimated standard deviations were in the following ranges for the three-dimensional, unidimensional, and two bidimensional size metrics, respectively (in mm): 0.49-1.25, 0.67-2.55, 0.78-2.11, and 0.96-2.69. Also, a very large difference among the metrics was observed: 0.95 probability-coverage region widths for the volume estimation conditional on unidimensional, and the two bidimensional size measurements of 10 mm were 7.32, 7.72, and 6.29 mm, respectively. CONCLUSIONS: The selection of data subsets for performance evaluation is highly impacted by the size metric choice. The LIDC plans to include a single size measure for each nodule in its database. This metric is not intended as a gold standard for nodule size; rather, it is intended to facilitate the selection of unique repeatable size limited nodule subsets.
机译:理由和目标:目的是研究在评估肺结节大小(作为结节表征和计算机辅助检测系统的性能)的因素的不同度量之间进行选择的影响,因为后者始终相对于给定条件合格结节的大小范围。材料与方法:本研究使用了由肺图像数据库协会(LIDC)记录的265例全肺CT扫描,用于其结节评估方案。每位受检查的病变均由四位经验丰富的放射科医生进行独立审查,他们为3 mm以上的结节提供了边界标记。考虑了基于边界标记的四个尺寸度量:在单个图像切片上的一维和二维测量,以及基于所有图像切片的体积测量。处理放射线医师的边界,分析带有四个标记的边界以表征放射线医师的差异,同时使用具有至少一个标记的边界来检查指标之间的差异。结果:对注释的处理发现了由四位放射科医生共同标记的127个结节和一组518个结节的扩展集,每个结节至少具有一个观察到的三维尺寸,范围从2.03至29.4 mm(平均7.05 mm,中位值5.71 mm) 。对于所有这些指标,观察者之间的变化都非常大:对于三维,一维和两个二维尺寸指标,估计的标准偏差的95%分别在以下范围内(以mm为单位):0.49-1.25、0.67-2.55 ,0.78-2.11和0.96-2.69。此外,还发现指标之间存在非常大的差异:以一维为条件进行体积估计的概率覆盖区域宽度为0.95,两个二维尺寸为10 mm的尺寸分别为7.32、7.72和6.29 mm。结论:用于性能评估的数据子集的选择受到大小度量选择的极大影响。 LIDC计划为其数据库中的每个结节包括一个单一大小的度量。此度量标准不打算作为结核大小的金标准;相反,其旨在促进对唯一的可重复大小限制的结节子集的选择。

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