ABSTRACT
Goal: 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. This study aims to develop a deep-learning-based automatic detection framework to assist diagnosis. Methods: The present study proposes a framework consisting of a Structurally-REfined Deep Portal Segmentation module and an Infiltrated Periportal Region Detection module based on heterogeneous infiltration features to accurately identify the infiltrated periportal regions in liver Whole Slide Images. Results: The proposed method achieves 0.725 in F1-score of lymphocyte-infiltrated periportal region detection. Moreover, the statistics of the ratio of the detected infiltrated portal boundary have high correlation to the Ishak grade (Spearman's correlations more than 0.87 with p-values less than 0.001) and medium correlation to the liver function index aspartate aminotransferase and alanine aminotransferase (Spearman's correlations more than 0.63 and 0.57 with p-values less than 0.001). Conclusions: The 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.
ABSTRACT
Betel quid chewing has been associated with several human cancers. However, the role of betel quid in carcinogenesis remains uncertain. Piper betel contains high concentrations of safrole (an inducer of DNA oxidative damage). Safrole may be metabolized by hepatic sulfotransferase 1A1 (SULT1A1), or glutathione S-transferases (GSTM1, GSTT1, and GSTP1). Thus, we investigated the association of genetic polymorphisms of SULT1A1, GSTM1, GSTT1, and GSTP1 with DNA oxidative damage among betel quid chewers. A biomarker for oxidative stress, urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) level, was analyzed using isotope-dilution LC-MS/MS in 64 betel quid chewers and 129 non-betel quid chewers. Data on demographics and habits (smoking, alcohol drinking, and betel quid chewing) were obtained from questionnaires. Our results revealed that urinary 8-OHdG level was higher in chewers with SULT1A1 Arg-His genotype than in chewers with SULT1A1 Arg-Arg genotype. Urinary 8-OHdG level was also higher in chewers with GSTP1 Ile-Ile genotype. Furthermore, the combined effect of SULT1A1 and GSTP1 genotypes on urinary 8-OHdG was evaluated. Non-chewers with both SULT1A1 Arg-Arg and GSTP1 Val-Val/Ile-Val (reference group) had the lowest mean level (3.6 ng/mg creatinine), whereas chewers with either SULT1A1 Arg-His or GSTP1 Ile-Ile had the highest 8-OHdG mean level (6.2 ng/mg creatinine; vs. reference group, P = 0.04). Chewers with both of SULT1A1 Arg-Arg and GSTP1 Val-Val/Ile-Val (4.6 ng/mg creatinine), and non-chewers with either SULT1A1 Arg-His or GSTP1 Ile-Ile (4.7 ng/mg creatinine) had a moderately increased 8-OHdG level. Thus, the susceptible SULT1A1 and GSTP1 genotypes may modulate increased DNA oxidative stress elicited by betel-quid chewing.
