Histogram Analysis of Computed Tomography Images for Quantitative Assessment of Gastric Cancer Invasiveness

Abstract

Introduction:To explore the role of computed tomography (CT) texture analysis in predicting T-stage of gastric cancers (GC).Methods:Preoperative enhanced CT images of 110 patients (men: 84, women: 26) with GC were reviewed retrospectively. Regions of interest were manually drawn along the margin of the lesion on the section where it appeared largest on the portal venous CT images, which yielded texture parameters (1, 10, 50, 90, and 99% percentiles; minimum, mean, and maximum norm; variance; skewness, and kurtosis). Correlations between texture parameters and pathological stage were analysed with Spearman’s correlation test. The distributions of all variables were checked with the aid of the Kolmogorov-Smirnov test. The Independent-Samples t-test and the Mann-Whitney U test were used (as appropriate) to compare quantitative data. The chi-squared test was employed to compare qualitative data. The diagnostic performance of CT texture parameters in differentiating different stages was evaluated using receiver operating characteristic analysis.Results:The T4 variance was significantly greater than that of the T1-to-T3 group (p˂0.05). The T4 skewness was significantly lower than that of the T1-to-T3 group (p˂0.05) but the T4 kurtosis significantly higher (p˂0.05).Conclusion:The histogram parameters of CT-TA, especially skewness and kurtosis derived from portal, venous phase CT images, may serve as biomarkers stratifying the risk of serosal invasion (stage-T4) by locally advanced GC. Thus, histogram analysis can be used preoperatively to evaluate serosal invasion.

Keywords

• gastric cancer
• t-staging
• ct
• histogram analysis