Kosin Medical Journal

Original article

A prospective study of the correlation between hepatic fibrosis and noninvasively measured fibrosis markers including serum M2BPGi and acoustic radiation force impulse elastography: Kwang Il Seo, Hyunyong Hwang, Byung Cheol Yun, Hyung Hwan Moon, Young Il Choi, Dong Hoon Shin, Myunghee Yoon; Kosin Med J. 2022;37(2):146-153. Published online June 24, 2022; DOI: https://doi.org/10.7180/kmj.22.110

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Background
Mac-2 binding protein glycosylation isomer (M2BPGi) was introduced as a noninvasively measurable serologic marker for liver fibrosis. Acoustic radiation force impulse imaging (ARFI) elastography is another noninvasive method of measuring hepatic fibrosis. There are limited data about the correlations between histologic fibrosis grade and noninvasively measured markers, including M2BPGi and ARFI.
Methods
This prospective study was conducted among patients admitted consecutively for liver resection, cholecystectomy, or liver biopsy. ARFI elastography, serum M2BPGi levels, and the AST to Platelet Ratio Index (APRI) score were evaluated before histologic evaluation. Histologic interpretation was performed by a single pathologist using the METAVIR scoring system.
Results
In patients with high METAVIR scores, M2BPGi levels and ARFI values showed statistically significant differences between patients with fibrosis and those without fibrosis. In 41 patients with hepatocellular carcinoma, as METAVIR scores increased, M2BPGi levels also tended to increase (p=0.161). ARFI values changed significantly as METAVIR scores increased (p=0.039). In 33 patients without hepatocellular carcinoma, as METAVIR scores increased, M2BPGi levels significantly increased (p=0.040). ARFI values also changed significantly as METAVIR scores increased (p=0.033). M2BPGi levels were significantly correlated with ARFI values (r=0.604, p<0.001), and APRI values (r=0.704, p<0.001), respectively.
Conclusions
Serum M2BPGi levels increased with liver fibrosis severity and could be a good marker for diagnosing advanced hepatic fibrosis regardless of the cause of liver disease.

Citations

Citations to this article as recorded by

Predicting Safe Liver Resection Volume for Major Hepatectomy Using Artificial Intelligence
Chol Min Kang, Hyung June Ku, Hyung Hwan Moon, Seong-Eun Kim, Ji Hoon Jo, Young Il Choi, Dong Hoon Shin
Journal of Clinical Medicine.2024; 13(2): 381. CrossRef

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