Authors: Hui Chen, Yuxin Gao, Gaojian Li, Manasvi Alam, Srisruthi Udayakumar, Qazi Noorul Mateen, Sahar Rostamian, Katherine Cilley, Sungwan Kim, Giwon Cho, Juyong Gwak, Yixuan Song, Joseph Michael Hardie, Manoj Kumar Kanakasabapathy, Hemanth Kandula, Prudhvi Thirumalaraju, Younseong Song, Azim Parandakh, Arafeh Bigdeli, Gregory P. Fricker, Jenna Gustafson, Raymond T. Chung, Jorge Mera, Hadi Shafiee
Published: 2025-03-19
Source: Full article
Viral hepatitis remains a major global health issue, with chronic hepatitis B (HBV) and hepatitis C (HCV) causing approximately 1 million deaths annually, primarily due to liver cancer and cirrhosis. More than 1.5 million people contract HCV each year, disproportionately affecting vulnerable populations, including American Indians and Alaska Natives (AI/AN). While direct-acting antivirals (DAAs) are highly effective, timely and accurate HCV diagnosis remains a challenge, particularly in resource-limited settings. The current two-step HCV testing process is costly and time-intensive, often leading to patient loss before treatment. Point-of-care (POC) HCV antigen (Ag) testing offers a promising alternative, but no FDA-approved test meets the required sensitivity and specificity. To address this, we developed a fully automated, smartphone-based POC HCV Ag assay using platinum nanoparticles, deep learning image processing, and microfluidics. With an overall accuracy of 94.59%, this cost-effective, portable device has the potential to reduce HCV-related health disparities, particularly among AI/AN populations, improving accessibility and equity in care.