Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines.
Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines.
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DOI：
10.1007/s00330-017-4767-2
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发表时间：
2017-10
影响因子：
5.9
通讯作者：
van Ginneken B
中科院分区：
文献类型：
--
作者：
van Riel SJ;Ciompi F;Jacobs C;Winkler Wille MM;Scholten ET;Naqibullah M;Lam S;Prokop M;Schaefer-Prokop C;van Ginneken B
比较PANCAN模型、肺RADS和1.2016全国肿瘤综合网络指南在肺结节基线筛查、CT扫描和直径测量方法对性能的影响。从丹麦肺癌筛查试验数据库中纳入恶性结节CT和良性结节基线CT各549例。使用系统原始直径定义：DLongest-C(PANCAN)、DmeanAxial(NCCN)和Dmean3D(肺-RADS)对系统的性能进行评估。随后，所有直径定义被统一应用于所有系统。用ROC曲线下面积(AUC)评价危险区分度。使用原始的直径规格，PANCAN的性能优于肺RADS和NCCN(AUC 0.874比0.813，p = 0.003；0.874比0.836，p = 0.010)。当联合应用DLongong-C、Dmean3D和DmeanAxial时，PANCAN仍优于肺RADS(p <； 0.001-p = 0.001)和NCCN(p <； 0.001-p = 0.016)。直径定义显著影响NCCN的性能，其中DLongest-C最差(DLongest-C vs.Dmean3D，p = 0.005；DLongest-C vs.Dean Axial，p = 0.016)。在没有后续信息的情况下，PANCAN模型在区分良恶性结节方面明显优于肺RADS和1.2016 NCCN指南。NCCN指南对结节大小的定义最为敏感。·PANCAN模型在识别恶性肺结节方面优于肺RADS和1.2016 NCCN指南。·结节大小定义对肺RADS和PANCAN模型没有显著影响。·1.2016 NCCN指南在使用平均直径与最长直径时显著优于其他指南。·最长直径在所有型号中的性能最低。·从轴位切面和容量测量法得出的平均直径表现相同。
To compare the PanCan model, Lung-RADS and the 1.2016 National Comprehensive Cancer Network (NCCN) guidelines for discriminating malignant from benign pulmonary nodules on baseline screening CT scans and the impact diameter measurement methods have on performances. From the Danish Lung Cancer Screening Trial database, 64 CTs with malignant nodules and 549 baseline CTs with benign nodules were included. Performance of the systems was evaluated applying the system's original diameter definitions: Dlongest-C (PanCan), DmeanAxial (NCCN), both obtained from axial sections, and Dmean3D (Lung-RADS). Subsequently all diameter definitions were applied uniformly to all systems. Areas under the ROC curves (AUC) were used to evaluate risk discrimination. PanCan performed superiorly to Lung-RADS and NCCN (AUC 0.874 vs. 0.813, p = 0.003; 0.874 vs. 0.836, p = 0.010), using the original diameter specifications. When uniformly applying Dlongest-C, Dmean3D and DmeanAxial, PanCan remained superior to Lung-RADS (p < 0.001 – p = 0.001) and NCCN (p < 0.001 – p = 0.016). Diameter definition significantly influenced NCCN’s performance with Dlongest-C being the worst (Dlongest-C vs. Dmean3D, p = 0.005; Dlongest-C vs. DmeanAxial, p = 0.016). Without follow-up information, the PanCan model performs significantly superiorly to Lung-RADS and the 1.2016 NCCN guidelines for discriminating benign from malignant nodules. The NCCN guidelines are most sensitive to nodule size definition. • PanCan model outperforms Lung-RADS and 1.2016 NCCN guidelines in identifying malignant pulmonary nodules. • Nodule size definition had no significant impact on Lung-RADS and PanCan model. • 1.2016 NCCN guidelines were significantly superior when using mean diameter to longest diameter. • Longest diameter achieved lowest performance for all models. • Mean diameter performed equivalently when derived from axial sections and from volumetry.
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影响因子：
4.8
作者：
Lee HJ;Goo JM;Lee CH;Yoo CG;Kim YT;Im JG
通讯作者：
Im JG
影响因子：
19.7
作者：
Pinsky, Paul F.;Gierada, David S.;Amorosa, Judith
通讯作者：
Amorosa, Judith
影响因子：
19.7
作者：
Singh, Satinder;Pinsky, Paul;Nath, P. Hrudaya
通讯作者：
Nath, P. Hrudaya
DOI：
10.1164/rccm.201505-1040oc
发表时间：
2016-03-01
影响因子：
24.7
作者：
Wille, Mathilde M. W.;Dirksen, Asger;Pedersen, Jesper H.
通讯作者：
Pedersen, Jesper H.
影响因子：
158.5
作者：
van Klaveren, Rob J.;Oudkerk, Matthijs;de Koning, Harry J.
通讯作者：
de Koning, Harry J.