Quantification of histopathological findings using a novel image analysis platform

TLDR

Digital pathology has advanced with AI‑based image analysis platforms such as HALO, which enable automated tissue segmentation. This study employed HALO to quantify histopathological changes that are difficult to analyze with conventional software. HALO’s tissue classifier, cytonuclear, and vacuole modules were trained to segment and quantify morphological features of liver, kidney, thymus, spleen, and parotid tissues, and the quantitative results were correlated with pathologist‑graded histopathology. Using HALO, morphological features were recognized, histopathological changes were analyzed, and grades were quantified, thereby supporting pathology evaluations.

Abstract

Digital pathology, including image analysis and automatic diagnosis of pathological tissue, has been developed remarkably. HALO is an image analysis platform specialized for the study of pathological tissues, which enables tissue segmentation by using artificial intelligence. In this study, we used HALO to quantify various histopathological changes and findings that were difficult to analyze using conventional image processing software. Using the tissue classifier module, the morphological features of degeneration/necrosis of the hepatocytes and muscle fibers, bile duct in the liver, basophilic tubules and hyaline casts in the kidney, cortex in the thymus, and red pulp, white pulp, and marginal zone in the spleen were learned and separated, and areas of interest were quantified. Furthermore, using the cytonuclear module and vacuole module in combination with the tissue classifier module, the number of erythroblasts in the red pulp of the spleen and each area of acinar cells in the parotid gland were quantified. The results of quantitative analysis were correlated with the histopathological grades evaluated by pathologists. By using artificial intelligence and other functions of HALO, we recognized morphological features, analyzed histopathological changes, and quantified the histopathological grades of various findings. The analysis of histopathological changes using HALO is expected to support pathology evaluations.