Computed Tomography for the Diagnosis of Intraperitoneal Infected Fluid Collections after Surgery for Gastric Cancer. Role of Texture Analysis

Abstract

Background & Aims: Several computed tomographic (CT) imaging features have been proposed to describe the infection of postoperative abdominal fluid collections; however, these features are vague, and there is a significant overlap between infected and non-infected collections. We assessed the role of textural parameters as additional diagnostic tools for distinguishing between infected and non-infected peritoneal collections in patients operated for gastric cancer. Methods: From 527 patients operated for gastric cancer, we retrospectively selected 82 cases with intraperitoneal collections who underwent CT exams. The fluid component was analyzed through a novel method (texture analysis); different patterns of pixel intensity and distribution were extracted and processed through a dedicated software (MaZda). A univariate analysis comparing the parameters of texture analysis between the two groups was performed. Afterwards, a multivariate analysis was performed for the univariate statistically significant parameters. Results: The study included 82 patients with bacteriologically verified infected (n=40) and noninfected (n=42) intraperitoneal effusions. The univariate analysis evidenced statistically significant differences between all the parameters involved. The multivariate analysis highlighted 10 parameters as being statistically significant, adjusted to Bonferroni correction. Conclusions: Our evidence supports the fact that textural analysis can be used as a complementary diagnostic tool for the detection of infected fluid collections after gastric cancer surgery. Further studies are required to validate the accuracy of this method.