A novel active learning-based digital pathology protocol annotation for histologic assessment in ulcerative colitis using PICASSO histologic remision index

Ulcerative colitis (UC) is an inflammatory bowel disease affecting the large intestine characterised by a relapse-remission cycle. Traditionally, the management of patients with ulcerative colitis has been based on the analysis of remission of inflammatory activity at the endoscopic level by evaluating videos recorded during endoscopic examinations. Recently, the treatment paradigm has shifted towards the study of biopsies for the analysis of histological remission at the microscopic level of tissues. One of the histological indicators of UC is the PICaSSO Histological Remission (PHRI) which consists of the assessment of inflammatory activity taking into account only neutrophils, key cells in inflammatory processes. PHRI is a simple assessment system which reduces the variability between subjects and facilitates the implementation of diagnostic support systems. The CVBLab group contributed to the validation of the application of the PHRI index in automated systems for the prediction of histological remission or the presence of ulcerative colitis-related activity. Close collaboration between CVBLab engineers and the group’s medical staff has enabled the translation of the problems they encounter in the clinic into solutions in the technical domain that contribute to the development of robust and effective deep learning models.