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多结节疾病:薄层CT的解剖定位——一种简单算法的多阅片者评估

Multinodular disease: anatomic localization at thin-section CT--multireader evaluation of a simple algorithm.

作者信息

Gruden J F, Webb W R, Naidich D P, McGuinness G

机构信息

Department of Radiology, New York University Hospitals System, NY, USA.

出版信息

Radiology. 1999 Mar;210(3):711-20. doi: 10.1148/radiology.210.3.r99mr21711.

Abstract

PURPOSE

To evaluate the interobserver variability and accuracy of an algorithm for anatomic localization of small nodules evident on thin-section computed tomographic (CT) images of the lungs.

MATERIALS AND METHODS

Four experienced chest radiologists independently evaluated thin-section CT images in 58 patients by using an algorithm and a standard score sheet. Nodules were placed into four possible anatomic locations or categories: perilymphatic, random, associated with small airways disease, or centrilobular. Algorithm accuracy was assessed by comparing the localization by the observers to that expected for each specific disease in the study group on the basis of reports in the literature. Interobserver variability was assessed by placing cases into one of three groups: (a) complete concordance, (b) triple concordance, and (c) discordant.

RESULTS

All observers agreed in 79% (46 of 58) of the cases with regard to nodule localization; three of the four concurred in an additional 17% (10 of 58). The observers were correct in 218 (94%) of 232 localizations in the 58 cases. There were no apparent differences in the number of either discordant or incorrect localizations between the observers. The most noteworthy source of error and of disagreement between observers was the confusion of perilymphatic and small airways disease-associated nodules in a small number of cases.

CONCLUSION

The proposed algorithm is reproducible and accurate in the majority of cases and facilitates nodule localization at thin-section CT.

摘要

目的

评估一种用于在肺部薄层计算机断层扫描(CT)图像上对小肺结节进行解剖定位的算法的观察者间变异性和准确性。

材料与方法

四位经验丰富的胸部放射科医生使用一种算法和标准评分表,对58例患者的薄层CT图像进行独立评估。结节被分为四个可能的解剖位置或类别:淋巴管周围型、随机型、与小气道疾病相关型或小叶中心型。通过将观察者的定位与基于文献报道的研究组中每种特定疾病预期的定位进行比较,评估算法的准确性。通过将病例分为以下三组之一来评估观察者间变异性:(a)完全一致,(b)三者一致,(c)不一致。

结果

所有观察者在79%(58例中的46例)的病例中就结节定位达成一致;四位观察者中的三位在另外17%(58例中的10例)的病例中意见一致。在这58例病例的232次定位中,观察者有218次(94%)定位正确。观察者之间在不一致或错误定位的数量上没有明显差异。观察者之间最值得注意的错误和分歧来源是在少数病例中淋巴管周围型结节与小气道疾病相关型结节的混淆。

结论

所提出的算法在大多数情况下具有可重复性和准确性,有助于在薄层CT上进行结节定位。

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