Detection of the carcinogenic liver fluke, Opisthorchis viverrini: comparison of two coprological methods versus the automatic feces analyzer.

Abstract

Liver fluke infection, particularly Opisthorchis viverrini, poses a significant public health risk in Thailand, where it is closely associated with cholangiocarcinoma and contributes to substantial mortality in the northeastern region. Diagnosis of this condition employs various parasitological approaches. This research aims to compare the diagnostic accuracy of three parasitological techniques: the Kato Katz technique (KKT), the formalin-ethyl acetate concentration technique (FECT), and the Fully Automatic Feces Analyzer (FAFA) for O. viverrini identification. A total of 455 fecal specimens were collected from rural areas across five provinces in northeastern Thailand. The specimens were processed according to each method and examined through microscopy for KKT and FECT, and by utilizing an artificial intelligence-based machine for FAFA. Data analysis was conducted to assess parasitic infection rates and observe diagnostic accuracy. The results revealed a parasitic infection rate of 19.34%, with the majority of infections attributed to O. viverrini (18.02%), followed by Strongyloides stercoralis (0.88%). FECT exhibited the highest positive detection of O. viverrini eggs (16.48%), followed by FAFA (10.55%), and KKT (8.57%), respectively. Statistical analysis indicated sensitivity and specificity values for O. viverrini detection by KKT (100% and 89.21%), FECT (98.67% and 97.63%), and FAFA (97.92% and 91.15%). The positive predictive value, negative predictive value, and kappa were reported for FECT (89.16%, 99.73%, 0.92), FAFA (56.63%, 99.73%, 0.67), and KKT (45.78%, 100%, 0.58). Additionally, the preparation time for KKT, FECT, and FAFA was 30, 15, and 10 min, respectively. In conclusion, this study highlights FECT, KKT, and FAFA as comparably sensitive in diagnosing O. viverrini. The FAFA machine emerges as a potentially valuable tool for detecting O. viverrini and other parasitic infections, showcasing promise for clinical use. The findings provide valuable insights into the diagnostic landscape and underscore the potential of FAFA in enhancing efficiency and accuracy in parasitological assessments.