Background/Objectives: Understanding the diagnostic landscape is essential prior to developing artificial intelligence (AI)-based diagnostic strategies for automating the diagnosis of duodenal biopsies. This study aims to (1) determine the frequencies of different diagnoses seen in endoscopic duodenal biopsies in a large, tertiary referral centre; (2) identify key words on histopathology request forms that could indicate that a biopsy may contain a serious pathology and should not be diagnosed by an AI system; and (3) investigate the proportion of cases described as showing “intraepithelial lymphocytosis” that might be coeliac disease. Methods: To achieve this, we audited 18 months’ worth of duodenal biopsy reports in our centre. Results: A total of 6245 duodenal biopsies were identified, of which 73.76% were normal and at least 8.84% fell within the spectrum of coeliac disease. Additionally, 6.47% were classified as showing non-specific inflammation, 1.86% were adenomas, 0.45% were carcinomas, 0.06% were neuroendocrine tumours, 0.10% were lymphomas, and 0.03% were cases of flat dysplasia, giving a total of 0.64% of dysplastic or malignant diagnoses. Rarer diagnoses included ulceration, Helicobacter pylori infection, giardiasis, lymphangiectasia, transplant rejection, and lymphoma. Furthermore, 227 biopsies (3.63%) showed isolated intraepithelial lymphocytosis, of which 33 cases (14.5%) gave an overall clinicopathological picture of coeliac disease. Conclusions: We present the first long-term audit of all endoscopic duodenal biopsies received by the histopathology department of a tertiary-care facility. The results indicate that a fully automated diagnostic histopathology reporting system able to identify normal duodenal biopsies and biopsies within the spectrum of coeliac disease-associated enteropathy could decrease pathologists’ endoscopic duodenal biopsy workload by up to 80%.

Understanding the diagnostic landscape prior to developing novel diagnostic strategies is key to managing expectations and authenticating results. In considering the possibility of developing alternate diagnostic approaches for coeliac disease based on duodenal biopsies, we audited 18 months’ worth of duodenal biopsies received in our centre to determine the exact proportions of different diagnoses. A total of 6245 duodenal biopsies were audited, of which 73.76% were normal and 8.84% fell within the spectrum of coeliac disease. Additionally, 6.47% were classified as showing non-specific inflammation, 1.86% were adenomas, 0.42% were carcinomas, and 0.06% were neuroendocrine tumours. Rarer diagnoses included ulceration, Helicobacter pylori infection, Giardiasis, lymphangiectasia, transplant rejection, and lymphoma. Furthermore, 227 biopsies (3.63%) showed isolated intraepithelial lymphocytosis, of which 24 cases eventually received a definitive diagnosis of coeliac disease. We present the first long-term audit of all endoscopic duodenal biopsies received by the histopathology department of a tertiary care facility. The results indicate that a fully automated system that could identify normal duodenal biopsies and biopsies within the spectrum of coeliac disease-associated enteropathy could decrease pathologists’ endoscopic duodenal biopsy workload by up to 80%.