1. Deep Learning-Enhanced Paper-Based Vertical Flow Assay for High-Sensitivity Troponin Detection Using Nanoparticle Amplification.
- Author
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Han, Gyeo-Re, Goncharov, Artem, Eryilmaz, Merve, Joung, Hyou-Arm, Ghosh, Rajesh, Yim, Geon, Chang, Nicole, Kim, Minsoo, Ngo, Kevin, Veszpremi, Marcell, Liao, Kun, Garner, Omai, Di Carlo, Dino, and Ozcan, Aydogan
- Subjects
cardiovascular disease ,deep learning ,high sensitivity ,nanoparticle amplification ,point-of-care ,troponin ,vertical flow assay ,Humans ,Paper ,Deep Learning ,Troponin I ,Point-of-Care Testing ,Biosensing Techniques ,Limit of Detection ,Gold ,Biomarkers ,Colorimetry ,Nanoparticles - Abstract
Successful integration of point-of-care testing (POCT) into clinical settings requires improved assay sensitivity and precision to match laboratory standards. Here, we show how innovations in amplified biosensing, imaging, and data processing, coupled with deep learning, can help improve POCT. To demonstrate the performance of our approach, we present a rapid and cost-effective paper-based high-sensitivity vertical flow assay (hs-VFA) for quantitative measurement of cardiac troponin I (cTnI), a biomarker widely used for measuring acute cardiac damage and assessing cardiovascular risk. The hs-VFA includes a colorimetric paper-based sensor, a portable reader with time-lapse imaging, and computational algorithms for digital assay validation and outlier detection. Operating at the level of a rapid at-home test, the hs-VFA enabled the accurate quantification of cTnI using 50 μL of serum within 15 min per test and achieved a detection limit of 0.2 pg/mL, enabled by gold ion amplification chemistry and time-lapse imaging. It also achieved high precision with a coefficient of variation of
- Published
- 2024