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Transient Part-Solid Nodules Detected at Screening Thin-Section CT for Lung Cancer: Comparison with Persistent Part-Solid Nodules
被引:108
|作者:
Lee, Sang Min
[1
,2
]
Park, Chang Min
[1
,2
]
Goo, Jin Mo
[1
,2
]
Lee, Chang Hyun
[1
,2
,3
]
Lee, Hyun Ju
[1
,2
]
Kim, Kwang Gi
[4
]
Kang, Mi-Jin
[5
]
Lee, In Sun
[1
,2
]
机构:
[1] Seoul Natl Univ, Dept Radiol, Coll Med, Seoul 110744, South Korea
[2] Seoul Natl Univ, Med Res Ctr, Inst Radiat Med, Seoul 110744, South Korea
[3] Seoul Natl Univ Hosp, Gangnam Hlth Care Ctr, Seoul 110744, South Korea
[4] Natl Canc Ctr, Dept Biomed Engn, Div Basic & Appl Sci, Gyeonggi Do, South Korea
[5] Inje Univ, Dept Radiol, Sanggye Paik Hosp, Seoul, South Korea
来源:
关键词:
GROUND-GLASS OPACITY;
COMPUTED-TOMOGRAPHY;
GROWTH-RATE;
HISTOLOGY;
SURVIVAL;
SMOKING;
WOMEN;
SIZE;
AREA;
D O I:
10.1148/radiol.09090547
中图分类号:
R8 [特种医学];
R445 [影像诊断学];
学科分类号:
1002 ;
100207 ;
1009 ;
摘要:
Purpose: To retrospectively investigate clinical and computed tomographic (CT) features of transient part-solid nodules (PSNs) initially detected at screening thin-section CT for lung cancer and to determine predictive factors that may differentiate transient PSNs from persistent PSNs. Materials and Methods: This study was approved by the institutional review board. From January 2006 to August 2008, 93 individuals with 126 PSNs were identified from among 16 777 individuals who underwent chest CT. Clinical features and CT characteristics of PSNs were reviewed, and clinical and thin-section CT features were compared between transient and persistent PSNs. To identify predictive factors of transient PSNs and evaluate predictive performance, logistic regression analysis and C statistic analysis were performed. Results: Eighty-eight (69.8%) of 126 PSNs were transient. Between transient and persistent PSNs, there were significant differences (P<.05) in patient age, patient sex, risk of lung cancer, presence of eosinophilia, mode of detection, lesion size, lesion multiplicity, size of solid portion, and lesion border. Multivariate analysis revealed that young patient age, detection of the lesion at follow-up, blood eosinophilia, lesion multiplicity, large solid portion, and ill-defined border were significant (P<.05) independent predictors of transient PSNs. The performance in the discrimination of transient PSNs from persistent PSNs of the logistic regression model that incorporated both clinical and thin-section CT features was significantly higher than the performance of the models that incorporated clinical features or thin-section CT features alone. Conclusion: A substantial proportion of PSNs detected at screening CT were transient. Transient PSNs could be predicted with high accuracy by using the features of young patient age, detection of the PSN at follow-up, blood eosinophilia, lesion multiplicity, large solid portion, and ill-defined lesion border. (C) RSNA, 2010
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页码:242 / 251
页数:10
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