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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).

Peng M, Peng F, Zhang C, Wang Q, Li Z, Hu H, Liu S, Xu B, Zhu W, Han Y, Lin Q - PLoS ONE (2015)

Bottom Line: Diameter, TV, MAX, AVG and STD increased along with PIA, MIA and IAC significantly and consecutively.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Thoracic Surgery, Shanghai First People's Hospital Affiliated to The Shanghai Jiao Tong University School Of Medicine, Shanghai, China.

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.

No MeSH data available.


Related in: MedlinePlus

Example of nodule three-dimensional processed and measured on thin-section helical computed tomography (CT) images.(A) Typical ground-glass opacity (GGO, black arrow) nodule on high-resolution CT. (B) The software automatically processed and measured the nodule that be placed a marker (green square) on it. (C) The magnified measurement list of relative image parameters from picture B including diameter, total volume (TV), the maximum CT value (MAX), average CT value (AVG) and standard deviation of CT value (STD).
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pone.0129206.g001: Example of nodule three-dimensional processed and measured on thin-section helical computed tomography (CT) images.(A) Typical ground-glass opacity (GGO, black arrow) nodule on high-resolution CT. (B) The software automatically processed and measured the nodule that be placed a marker (green square) on it. (C) The magnified measurement list of relative image parameters from picture B including diameter, total volume (TV), the maximum CT value (MAX), average CT value (AVG) and standard deviation of CT value (STD).

Mentions: In the present study, we analyzed 5 radiologic parameters of GGO: 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) that were measured on a commercially available workstation (Advantage Workstation 4.3; GE Healthcare) with CT lung analysis software (Lung VCAR; GE Healthcare). This software can segment pulmonary nodules with ground-glass attenuation. Diameter, TV, MAX, AVE and STD are computed automatically after the operator placing a marker on the nodule. The CT lung analysis software system automatically identified the GGO nodules in all X-axis, Y-axis and Z-axis directions from the surrounding normal lung tissue. The elimination of normal structures within or around the nodule, such as vessels and bronchiole, was performed using several image-processing techniques[26]. Therefore, the nodule was identified as the lesion area without vessels and bronchiole. Some authors have described the concrete procedures and methods with the exact kind of software.[27–31] The judgment of successful segmentation was based on the observers’ visual assessment on axial CT images as well as sagittal and coronal multiplanar reconstructed images. (Fig 1)


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

Peng M, Peng F, Zhang C, Wang Q, Li Z, Hu H, Liu S, Xu B, Zhu W, Han Y, Lin Q - PLoS ONE (2015)

Example of nodule three-dimensional processed and measured on thin-section helical computed tomography (CT) images.(A) Typical ground-glass opacity (GGO, black arrow) nodule on high-resolution CT. (B) The software automatically processed and measured the nodule that be placed a marker (green square) on it. (C) The magnified measurement list of relative image parameters from picture B including diameter, total volume (TV), the maximum CT value (MAX), average CT value (AVG) and standard deviation of CT value (STD).
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4465676&req=5

pone.0129206.g001: Example of nodule three-dimensional processed and measured on thin-section helical computed tomography (CT) images.(A) Typical ground-glass opacity (GGO, black arrow) nodule on high-resolution CT. (B) The software automatically processed and measured the nodule that be placed a marker (green square) on it. (C) The magnified measurement list of relative image parameters from picture B including diameter, total volume (TV), the maximum CT value (MAX), average CT value (AVG) and standard deviation of CT value (STD).
Mentions: In the present study, we analyzed 5 radiologic parameters of GGO: 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) that were measured on a commercially available workstation (Advantage Workstation 4.3; GE Healthcare) with CT lung analysis software (Lung VCAR; GE Healthcare). This software can segment pulmonary nodules with ground-glass attenuation. Diameter, TV, MAX, AVE and STD are computed automatically after the operator placing a marker on the nodule. The CT lung analysis software system automatically identified the GGO nodules in all X-axis, Y-axis and Z-axis directions from the surrounding normal lung tissue. The elimination of normal structures within or around the nodule, such as vessels and bronchiole, was performed using several image-processing techniques[26]. Therefore, the nodule was identified as the lesion area without vessels and bronchiole. Some authors have described the concrete procedures and methods with the exact kind of software.[27–31] The judgment of successful segmentation was based on the observers’ visual assessment on axial CT images as well as sagittal and coronal multiplanar reconstructed images. (Fig 1)

Bottom Line: Diameter, TV, MAX, AVG and STD increased along with PIA, MIA and IAC significantly and consecutively.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Thoracic Surgery, Shanghai First People's Hospital Affiliated to The Shanghai Jiao Tong University School Of Medicine, Shanghai, China.

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.

No MeSH data available.


Related in: MedlinePlus