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CT Textural Analysis Of Gastric Cancer: Correlations With Immunohistochemical Biomarkers
Shunli Liu, H. Shi, Changfeng Ji, W. Guan, L. Chen, Y. Sun, Lei Tang, Y. Guan, W. Li, Yun Ge, J. He, Song Liu, Zhengyang Zhou
Published 2018 · Medicine
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To investigate the ability of CT texture analysis to assess and predict the expression statuses of E-cadherin, Ki67, VEGFR2 and EGFR in gastric cancers, the enhanced CT images of 139 patients with gastric cancer were retrospectively reviewed. The region of interest was manually drawn along the margin of the lesion on the largest slice in the arterial and venous phases, which yielded a series of texture parameters. Our results showed that the standard deviation, width, entropy, entropy (H), correlation and contrast from the arterial and venous phases were significantly correlated with the E-cadherin expression level in gastric cancers (all P < 0.05). The skewness from the arterial phase and the mean and autocorrelation from the venous phase were negatively correlated with the Ki67 expression level in gastric cancers (all P < 0.05). The width, entropy and contrast from the venous phase were positively correlated with the VEGFR2 expression level in gastric cancers (all P < 0.05). No significant correlation was found between the texture features and EGFR expression level. CT texture analysis, which had areas under the receiver operating characteristic curve (AUCs) ranging from 0.612 to 0.715, holds promise in predicting E-cadherin, Ki67 and VEGFR2 expression levels in gastric cancers.
This paper references
Significance of vessel count and vascular endothelial growth factor and its receptor (KDR) in intestinal-type gastric cancer.
Y. Takahashi (1996)
A causal role for E-cadherin in the transition from adenoma to carcinoma
A. Perl (1998)
Low Ki‐67 proliferation index is an indicator of poor prognosis in gastric cancer
H. E. Lee (2010)
Hypervascular gastric masses: CT findings and clinical correlates.
Pamela T. Johnson (2010)
pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes
Extent of arterial tumor enhancement measured with preoperative MDCT gastrography is a prognostic factor in advanced gastric cancer after curative resection.
M. Komori (2013)
Epidermal growth factor receptor (EGFR) mutations in lung cancer: preclinical and clinical data
S.E.D.C. Jorge (2014)
Preoperative locoregional staging of gastric cancer: is there a place for magnetic resonance imaging? Prospective comparison with EUS and multidetector computed tomography
F. Giganti (2015)
preclinical and clinical data
S. E. Jorge (2014)
can it differentiate benign and malignant mediastinal lymph nodes in patients with primary lung cancer? Eur Radiol
Ki-67 and other proliferation markers useful for immunohistological diagnostic and prognostic evaluations in human malignancies.
J. Gerdes (1990)
EGFR gene and cancer
T. Mitsudomi (2010)
Combined evaluation of centromere protein H and Ki-67 as prognostic biomarker for patients with gastric carcinoma.
W. He (2013)
The biology of VEGF and its receptors
N. Ferrara (2003)
Gastric cancer staging at multi-detector row CT gastrography: comparison of transverse and volumetric CT scanning.
H. Kim (2005)
Exclusion of Kaposi Sarcoma From Analysis of Cancer Burden-Reply.
C. Fitzmaurice (2017)
Gastric cancer: texture analysis from multidetector computed tomography as a potential preoperative prognostic biomarker
F. Giganti (2016)
[Correlation of CT presentation with histo-differentiation and p53 and Ki67 expressions in gastric cancer].
J. Wang (2011)
A novel receptor tyrosine kinase inhibitor for the treatment of gastric cancer
Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016
C. Fitzmaurice (2018)
Apatinib: A novel receptor tyrosine kinase inhibitor for the treatment of gastric cancer.
G. Roviello (2016)
can the largest crosssectional area be used as an alternative to whole tumor analysis? Eur J Radiol
F. Ng (2013)
an international, randomised, multicentre, placebo-controlled, phase 3 trial
A systematic review and meta-analysis of the utility of EUS for preoperative staging for gastric cancer
Roberta Cardoso (2011)
Primary esophageal cancer: heterogeneity as potential prognostic biomarker in patients treated with definitive chemotherapy and radiation therapy.
C. Yip (2014)
evidence from a systematic meta-analysis
The prognostic value of E‐cadherin in gastric cancer: A meta‐analysis
X. Xing (2013)
Can Quantitative CT Texture Analysis be Used to Differentiate Fat-poor Renal Angiomyolipoma from Renal Cell Carcinoma on Unenhanced CT Images?
Taryn Hodgdon (2015)
Analysis of CT features and quantitative texture analysis in patients with lung adenocarcinoma: a correlation with EGFR mutations and survival rates.
B. Sacconi (2017)
Epidermal growth factor receptor in relation to tumor development: EGFR gene and cancer
T. Mitsudomi (2010)
Loss of E-cadherin expression correlates with poor differentiation and invasion into adjacent organs in gastric adenocarcinomas.
H. Chen (2003)
Prognostic evaluation of Nanog, Oct4, Sox2, PCNA, Ki67 and E-cadherin expression in gastric cancer
N. Li (2014)
Pre-treatment MDCT-based texture analysis for therapy response prediction in gastric cancer: Comparison with tumour regression grade at final histology.
F. Giganti (2017)
is there a place for magnetic resonance imaging? Prospective comparison with EUS and multidetector computed tomography
Can iodine concentration non-invasively assess angiogenesis? World J Gastroenterol
F. Ribeiro (2017)
Prediction of the therapeutic response after FOLFOX and FOLFIRI treatment for patients with liver metastasis from colorectal cancer using computerized CT texture analysis.
Su Yeon Ahn (2016)
Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis?
F. Ng (2013)
Ramucirumab monotherapy for previously treated advanced gastric or gastro-oesophageal junction adenocarcinoma (REGARD): an international, randomised, multicentre, placebo-controlled, phase 3 trial
C. Fuchs (2014)
Quantitative CT texture and shape analysis: Can it differentiate benign and malignant mediastinal lymph nodes in patients with primary lung cancer?
H. Bayanati (2014)
Ki-67 is a valuable prognostic predictor of lymphoma but its utility varies in lymphoma subtypes: evidence from a systematic meta-analysis
X. He (2013)
CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes
M. Lubner (2015)
Spectral computed tomography in advanced gastric cancer: Can iodine concentration non-invasively assess angiogenesis?
Xiao-hua Chen (2017)
Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival.
F. Ng (2013)
a correlation with EGFR mutations and survival rates
Relationship between expression of EGFR in gastric cancer tissue and clinicopathological features.
M. Gao (2013)
Application of CT texture analysis in predicting histopathological characteristics of gastric cancers
Shunli Liu (2017)
Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016:A Systematic Analysis for the Global Burden of Disease Study
Paula Esther Moraga-Serrano (2018)
heterogeneity as potential prognostic biomarker in patients treated with definitive chemotherapy and radiation therapy
CT findings and clinical correlates
P. T. Johnson (2010)
Prognostic significance of vascular endothelial growth factor and its receptors in endometrial carcinoma.
Y. Yokoyama (2000)
CT Gray-Level Texture Analysis as a Quantitative Imaging Biomarker of Epidermal Growth Factor Receptor Mutation Status in Adenocarcinoma of the Lung.
E. Ozkan (2015)
Accuracy of multidetector-row CT in diagnosing lymph node metastasis in patients with gastric cancer
T. Saito (2014)
CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges.
M. Lubner (2017)
The prognostic impact of epidermal growth factor receptor in patients with metastatic gastric cancer
A. Atmaca (2012)
Neoadjuvant chemotherapy for advanced gastric cancer: a meta-analysis.
W. Li (2010)
Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 32 Cancer Groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study
C. Fitzmaurice (2017)
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Acute Tumor Transition Angle on Computed Tomography Predicts Chromosomal Instability Status of Primary Gastric Cancer: Radiogenomics Analysis from TCGA and Independent Validation
Y. Lai (2019)
Prognosis assessment in metastatic gastrointestinal stromal tumors treated with tyrosine kinase inhibitors based on CT-texture analysis.
K. Ekert (2019)
Applying a random projection algorithm to optimize machine learning model for predicting peritoneal metastasis in gastric cancer patients using CT images
Seyedehnafiseh Mirniaharikandehei (2020)
Imaging biomarkers in upper gastrointestinal cancers
M. Gabelloni (2019)
A CT-based radiomics nomogram for prediction of human epidermal growth factor receptor 2 status in patients with gastric cancer
Y. Li (2020)