ArticlePloS one2015
Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO).
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Prediction of Ki-67 expression in gastrointestinal stromal tumors using radiomics of plain and multiphase contrast-enhanced CT.European radiology · 2023Article
- CT Radiomics for the Preoperative Prediction of Ki67 Index in Gastrointestinal Stromal Tumors: A Multi-Center Study.Frontiers in oncology · 2021Article
- A nomogram to predict invasiveness in lung adenocarcinoma presenting as ground glass nodule.Translational cancer research · 2020Article
- Spectral CT imaging parameters and Ki-67 labeling index in lung adenocarcinoma.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2020Article
- Article
- [A Retrospective Study of Mean Computed Tomography Value to Predict the Tumor Invasiveness in AAH and Clinical Stage Ia Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2018Article
- Article
- Predictive value of mutant p53 expression index obtained from nonenhanced computed tomography measurements for assessing invasiveness of ground-glass opacity nodules.OncoTargets and therapy · 2016Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to predict Ki-67 labeling index (LI) preoperatively by three-dimensional (3D) CT image parameters for pathologic assessment of GGO nodules. Diameter, total volume (TV), the maximum CT number (MAX), average CT number (AVG) and standard deviation of CT number within the whole GGO nodule (STD) were measured by 3D CT workstation. By detection of immunohistochemistry and Image Software Pro Plus 6.0, different Ki-67 LI were measured and statistically analyzed among preinvasive adenocarcinoma (PIA), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC). Receiver operating characteristic (ROC) curve, Spearman correlation analysis and multiple linear regression analysis with cross-validation were performed to further research a quantitative correlation between Ki-67 labeling index and radiological parameters. Diameter, TV, MAX, AVG and STD increased along with PIA, MIA and IAC significantly and consecutively. In the multiple linear regression model by a stepwise way, we obtained an equation: prediction of Ki-67 LI=0.022*STD+0.001* TV+2.137 (R=0.595, R's square=0.354, p<0.001), which can predict Ki-67 LI as a proliferative marker preoperatively. Diameter, TV, MAX, AVG and STD could discriminate pathologic categories of GGO nodules significantly. Ki-67 LI of early lung adenocarcinoma presenting GGO can be predicted by radiologic parameters based on 3D CT for differential diagnosis.
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