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Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)

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...

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Autores principales: Peng, Mingzheng, Peng, Fei, Zhang, Chengzhong, Wang, Qingguo, Li, Zhao, Hu, Haiyang, Liu, Sida, Xu, Binbin, Zhu, Wenzhuo, Han, Yudong, Lin, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4465676/
https://www.ncbi.nlm.nih.gov/pubmed/26061252
http://dx.doi.org/10.1371/journal.pone.0129206
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author Peng, Mingzheng
Peng, Fei
Zhang, Chengzhong
Wang, Qingguo
Li, Zhao
Hu, Haiyang
Liu, Sida
Xu, Binbin
Zhu, Wenzhuo
Han, Yudong
Lin, Qiang
author_facet Peng, Mingzheng
Peng, Fei
Zhang, Chengzhong
Wang, Qingguo
Li, Zhao
Hu, Haiyang
Liu, Sida
Xu, Binbin
Zhu, Wenzhuo
Han, Yudong
Lin, Qiang
author_sort Peng, Mingzheng
collection PubMed
description 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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spelling pubmed-44656762015-06-25 Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO) Peng, Mingzheng Peng, Fei Zhang, Chengzhong Wang, Qingguo Li, Zhao Hu, Haiyang Liu, Sida Xu, Binbin Zhu, Wenzhuo Han, Yudong Lin, Qiang PLoS One Research Article 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. Public Library of Science 2015-06-10 /pmc/articles/PMC4465676/ /pubmed/26061252 http://dx.doi.org/10.1371/journal.pone.0129206 Text en © 2015 Peng et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Peng, Mingzheng
Peng, Fei
Zhang, Chengzhong
Wang, Qingguo
Li, Zhao
Hu, Haiyang
Liu, Sida
Xu, Binbin
Zhu, Wenzhuo
Han, Yudong
Lin, Qiang
Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)
title Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)
title_full Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)
title_fullStr Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)
title_full_unstemmed Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)
title_short Preoperative Prediction of Ki-67 Labeling Index By Three-dimensional CT Image Parameters for Differential Diagnosis Of Ground-Glass Opacity (GGO)
title_sort preoperative prediction of ki-67 labeling index by three-dimensional ct image parameters for differential diagnosis of ground-glass opacity (ggo)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4465676/
https://www.ncbi.nlm.nih.gov/pubmed/26061252
http://dx.doi.org/10.1371/journal.pone.0129206
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