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The early diagnosis and treatment of hepatitis is essential to reduce hepatitis-related liver function deterioration and mortality. One component of the widely-used Ishak grading system for the grading of periportal interface hepatitis is based on the percentage of portal borders infiltrated by lymphocytes. Thus, the accurate detection of lymphocyte-infiltrated periportal regions is critical in the diagnosis of hepatitis. However, the infiltrating lymphocytes usually result in the formation of ambiguous and highly-irregular portal boundaries, and thus identifying the infiltrated portal boundary regions precisely using automated methods is challenging. The present study proposes a framework consisting of a Structurally-REfined Deep Portal Segmentation (SREDPS) module and an Infiltrated Periportal Region Detection (IPRD) module based on heterogeneous infiltration features to accurately identify the infiltrated periportal regions in liver Whole Slide Images (WSIs). The experimental results show that the proposed method achieves an F1-score of 0.725. Moreover, the statistics of the ratio of the detected infiltrated portal boundary are highly correlated with the Ishak grade, with Spearman&#x0027;s correlations of more than 0.87 and p-values of less than 0.001. The statistics also have medium correlation to the liver function index aspartate aminotransferase (AST) and alanine aminotransferase (ALT), with Spearman&#x0027;s correlations of more than 0.63 and 0.57 respectively and p-values of less than 0.001. The present study shows the statistics of the ratio of infiltrated portal boundary have correlation to the Ishak grade and liver function index. The proposed framework provides pathologists with a useful and reliable tool for hepatitis diagnosis.

Lymphocyte-Infiltrated Periportal Region Detection with Structurally-Refined Deep Portal Segmentation and Heterogeneous Infiltration Features