Chen Hui, Gao Yuxin, Li Gaojian, Alam Manasvi, Udayakumar Srisruthi, Mateen Qazi Noorul, Rostamian Sahar, Cilley Katherine, Kim Sungwan, Cho Giwon, Gwak Juyong, Song Yixuan, Hardie Joseph Michael, Kanakasabapathy Manoj Kumar, Kandula Hemanth, Thirumalaraju Prudhvi, Song Younseong, Parandakh Azim, Bigdeli Arafeh, Fricker Gregory P, Gustafson Jenna, Chung Raymond T, Mera Jorge, Shafiee Hadi
Division of Engineering in Medicine, Division of Renal Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.
Liver Center, Gastrointestinal Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
Sci Adv. 2025 Mar 21;11(12):eadt3803. doi: 10.1126/sciadv.adt3803. Epub 2025 Mar 19.
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.
病毒性肝炎仍然是一个重大的全球健康问题，慢性乙型肝炎（HBV）和丙型肝炎（HCV）每年导致约100万人死亡，主要原因是肝癌和肝硬化。每年有超过150万人感染HCV，对包括美国印第安人和阿拉斯加原住民（AI/AN）在内的弱势群体影响尤为严重。虽然直接抗病毒药物（DAA）非常有效，但及时准确的HCV诊断仍然是一项挑战，特别是在资源有限的环境中。目前的两步HCV检测过程成本高昂且耗时，常常导致患者在治疗前流失。即时检测（POC）HCV抗原（Ag）检测提供了一种有前景的替代方法，但没有获得美国食品药品监督管理局（FDA）批准的检测方法能满足所需的灵敏度和特异性。为了解决这一问题，我们利用铂纳米颗粒、深度学习图像处理和微流体技术开发了一种基于智能手机的全自动即时检测HCV Ag检测方法。这种具有成本效益的便携式设备总体准确率为94.59%，有可能减少与HCV相关的健康差距，特别是在AI/AN人群中，提高医疗服务的可及性和公平性。
