Usefulness of computerized method for lung nodule detection on digital chest radiographs using similar subtraction images from different patients
Usefulness of computerized method for lung nodule detection on digital chest radiographs using similar subtraction images from different patients
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DOI：
10.1016/j.ejrad.2011.02.010
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发表时间：
2012-05-01
影响因子：
3.3
通讯作者：
Korogi, Yukunori
中科院分区：
文献类型：
--
作者：
Aoki, Takatoshi;Oda, Nobuhiro;Korogi, Yukunori
目的：评价一种新的计算机化方法在无胸部X线片的患者中自动选择相似胸片进行图像减影的有效性，并通过呈现不同患者的“相似减影图像”来辅助放射科医生的解释。材料和方法：获得机构审查委员会的批准，免除了对患者知情同意的要求。一个大约15,000张正常胸片的大型数据库被用来搜索不同患者的相似图像。根据两个临床参数和目标图像中肺野的相似性选择100幅候选图像。我们利用100幅图像中胸部区域的相关值来搜索最相似的图像。通过减去从目标图像中选择的相似图像来获得相似减影图像。对30例肺结节患者和30例非肺结节患者进行观察者操作测试。4名主诊放射科医生和4名放射科住院医师参加了这项观察者表现测试。结果：所有放射科医生的AUC值从0.925显著增加到0.974(P=.004)。当有计算机输出的图像时，居民的平均AUC(0.960比0.890)比主治医师的(0.987比0.960)更好。结论：利用不同患者的相似减影图像进行肺结节计算机检测的新方法将有助于在数字胸片上检测肺结节，特别是对于经验较少的读者。(C)2011爱思唯尔爱尔兰有限公司。保留所有权利。
Purpose: The purpose of this study is to evaluate the usefulness of a novel computerized method to select automatically the similar chest radiograph for image subtraction in the patients who have no previous chest radiographs and to assist the radiologists' interpretation by presenting the "similar subtraction image" from different patients.Materials and methods: Institutional review board approval was obtained, and the requirement for informed patient consent was waived. A large database of approximately 15,000 normal chest radiographs was used for searching similar images of different patients. One hundred images of candidates were selected according to two clinical parameters and similarity of the lung field in the target image. We used the correlation value of chest region in the 100 images for searching the most similar image. The similar subtraction images were obtained by subtracting the similar image selected from the target image. Thirty cases with lung nodules and 30 cases without lung nodules were used for an observer performance test. Four attending radiologists and four radiology residents participated in this observer performance test.Results: The AUC for all radiologists increased significantly from 0.925 to 0.974 with the CAD (P = .004). When the computer output images were available, the average AUC for the residents was more improved (0.960 vs. 0.890) than for the attending radiologists (0.987 vs. 0.960).Conclusion: The novel computerized method for lung nodule detection using similar subtraction images from different patients would be useful to detect lung nodules on digital chest radiographs, especially for less experienced readers. (C) 2011 Elsevier Ireland Ltd. All rights reserved.