The need for automated image analysis of gastrointestinal cancers has been increasing. Gastric cancer and colorectal cancer are among the five major cancers in Japan thus, a large number of endoscopically obtained specimens are being submitted for pathological analysis. This considerable workload for surgical pathologists needs to be reduced automated screening for negative specimens that do not require the review of a pathologist could be effective.

Moreover, application of automated image analysis is expected to contribute to the quality control of routine pathological diagnosis. NEC Corporation has developed the e-Pathologist image analysis software that can classify digitized histological images of gastric biopsy specimens into three categories that correspond to carcinoma or suspicion of carcinoma (positive), adenoma or suspicion of a neoplastic lesion (caution), and no malignancy (negative). However, the validity of this software analysis in routine pathological practice remains unclear. The aim of the present study was to evaluate the accuracy of the classification of the e-Pathologist image analysis software and clarify the requirements for using an automated screening system in clinical settings. Patient selection, tissue section preparation, and pathological diagnosis Sims 4 cancer mod 2018 software# The study was conducted in accordance with the Declaration of Helsinki, and with the approval of the Institutional Review Board of the National Cancer Center, Tokyo, Japan. We consecutively collected a total of 3062 gastric biopsy specimens between January 19 and April 30 in 2015 at the National Cancer Center (Tsukiji and Kashiwa campus). The specimens were fixed in 10% buffered formalin and embedded in paraffin. Each block was sliced into 4-μm-thick sections.