Automated histological classification of whole-slide images of gastric biopsy specimens

• Published in: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association 2018-03, Vol.21 (2), p.249-257
• Main Authors: Yoshida, Hiroshi, Shimazu, Taichi, Kiyuna, Tomoharu, Marugame, Atsushi, Yamashita, Yoshiko, Cosatto, Eric, Taniguchi, Hirokazu, Sekine, Shigeki, Ochiai, Atsushi
• Format: Article
• Language: English
• Subjects: Abdominal Surgery; Adenocarcinoma - classification; Adenocarcinoma - diagnosis; Adenocarcinoma - pathology; Adenoma; Automation; Automation, Laboratory - methods; Biopsy; Cancer Research; Classification; Gastric cancer; Gastroenterology; Humans; Image Interpretation, Computer-Assisted - methods; Image processing; Machine Learning; Medicine; Medicine & Public Health; Oncology; Original Article; Pathology; Pathology, Clinical - methods; Software; Stomach Neoplasms - classification; Stomach Neoplasms - diagnosis; Stomach Neoplasms - pathology; Surgical Oncology
• ISSN: 1436-3291; 1436-3305
• DOI: 10.1007/s10120-017-0731-8

Background Automated image analysis has been developed currently in the field of surgical pathology. The aim of the present study was to evaluate the classification accuracy of the e-Pathologist image analysis software. Methods A total of 3062 gastric biopsy specimens were consecutively obtained and stained. The specimen slides were anonymized and digitized. At least two experienced gastrointestinal pathologists evaluated each slide for pathological diagnosis. We compared the three-tier (positive for carcinoma or suspicion of carcinoma; caution for adenoma or suspicion of a neoplastic lesion; or negative for a neoplastic lesion) or two-tier (negative or non-negative) classification results of human pathologists and of the e-Pathologist. Results Of 3062 cases, 33.4% showed an abnormal finding. For the three-tier classification, the overall concordance rate was 55.6% (1702/3062). The kappa coefficient was 0.28 (95% CI, 0.26–0.30; fair agreement). For the negative biopsy specimens, the concordance rate was 90.6% (1033/1140), but for the positive biopsy specimens, the concordance rate was less than 50%. For the two-tier classification, the sensitivity, specificity, positive predictive value, and negative predictive value were 89.5% (95% CI, 87.5–91.4%), 50.7% (95% CI, 48.5–52.9%), 47.7% (95% CI, 45.4–49.9%), and 90.6% (95% CI, 88.8–92.2%), respectively. Conclusions Although there are limitations and requirements for applying automated histopathological classification of gastric biopsy specimens in the clinical setting, the results of the present study are promising.