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Updated: Feb 27, 2026

Gene Regulation and Targeted Therapy in Gastric Cancer Peritoneal Metastasis: Radiological Findings from Dual Energy CT and PET/CT
Published on: January 22, 2018
Application of CT texture analysis in predicting histopathological characteristics of gastric cancers
Shunli Liu1, Song Liu1, Changfeng Ji1
1Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, No. 321 Zhongshan Road, Nanjing, Jiangsu Province, China, 210008.
Objectives:
To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers.
Methods:
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.
Results:
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.
Conclusion:
CT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers.
Key Points:
• 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.

