Application of CT texture analysis in predicting histopathological characteristics of gastric cancers
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To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers.
Preoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed.
Mean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, −0.231 ~ −0.324, 0.228 ~ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = −0.265, −0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion.
CT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers.
• CT texture analysis is noninvasive and effective for gastric cancer.
• Portal venous CT images correlated significantly with differentiation degree and Lauren classification.
• Standard deviation, entropy and minimum attenuation in arterial phase reflect vascular invasion.
KeywordsGastric cancer Multidetector computed tomography Pathology Diagnosis Medical oncology
Area under the curve
Intraclass correlation coefficient
Receiver operating characteristic
Region of interest
Compliance with ethical standards
The scientific guarantor of this publication is Zhengyang Zhou.
Conflict of interest
The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
This study has received funding by the National Natural Science Foundation of China (ID: 81371516, 81501441), Foundation of National Health and Family Planning Commission of China (W201306), Social Development Foundation of Jiangsu Province (BE2015605), the Natural Science Foundation of Jiangsu Province (ID: BK20131281, BK20150109), Jiangsu Province Health and Family Planning Commission Youth Scientific Research Project (ID: Q201508), and Six Talent Peaks Project of Jiangsu Province (ID: 2015-WSN-079).
Statistics and biometry
No complex statistical methods were necessary for this paper.
Institutional Review Board approval was obtained.
Written informed consent was waived by the Institutional Review Board.
• diagnostic or prognostic study
• performed at one institution
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