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Background <p>Since the progress of hepatitis C Virus (HCV) infection to chronic liver disease and finally cirrhosis and hepatocellular&#xa0;carcinoma, HCV infection has become a worldwide challenge to public health.</p> Results <p>The progression from liver biopsy and antibody based test to the current time in the advancements in HCV diagnostic method is reviewed in this analysis with detailed discussion of enzyme immunoassay (EIAs), nucleic acid tests (NATs) and genotyping in enhancing accuracy of HCV detection. Next generation sequencing (NGS) and point of care testing (POCT) provided fast and economical diagnostic solutions. However, as promising diagnostic tools, Artificial Intelligence (AI) as well as Machine Learning (ML) can only be used in well-resourced environments, whereas Rapid Diagnostic Tests (RDTs) are advantageous for low and middle income countries.</p> Conclusion <p>This review discusses some of the future challenges that face lowering of diagnostic costs in low resource settings and promoting early detection, some of which can be addressed by microfluidic platforms. Research in this area is far from over, and past and ongoing research has tremendous potential to access new technology for a myriad of purposes in the course of HCV control and global HCV elimination.</p>

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A review of historical landmarks and pioneering technologies for the diagnosis of Hepatitis C Virus (HCV)

  • 期刊论文

  • 发表日期：

    2025年3月22日

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  • Kajal Sharma,
  • Meesala Krishna Murthy

摘要

Background

Since the progress of hepatitis C Virus (HCV) infection to chronic liver disease and finally cirrhosis and hepatocellular carcinoma, HCV infection has become a worldwide challenge to public health.

Results

The progression from liver biopsy and antibody based test to the current time in the advancements in HCV diagnostic method is reviewed in this analysis with detailed discussion of enzyme immunoassay (EIAs), nucleic acid tests (NATs) and genotyping in enhancing accuracy of HCV detection. Next generation sequencing (NGS) and point of care testing (POCT) provided fast and economical diagnostic solutions. However, as promising diagnostic tools, Artificial Intelligence (AI) as well as Machine Learning (ML) can only be used in well-resourced environments, whereas Rapid Diagnostic Tests (RDTs) are advantageous for low and middle income countries.

Conclusion

This review discusses some of the future challenges that face lowering of diagnostic costs in low resource settings and promoting early detection, some of which can be addressed by microfluidic platforms. Research in this area is far from over, and past and ongoing research has tremendous potential to access new technology for a myriad of purposes in the course of HCV control and global HCV elimination.