An Enhanced Electrochemiluminescence Immunoassay Platform via Optimized Magnetic Bead Uniformity for Reliable Thyroid-Stimulating Hormone Monitoring
Electrochemiluminescence immunoassay (ECLIA) is widely used in clinical diagnostics owing to its high sensitivity, broad dynamic range, and excellent analytical stability. However, the influence of magnetic bead deposition behavior on electrochemiluminescence (ECL) signal performance remains insufficiently characterized. In this study, a quantitative evaluation method for magnetic bead distribution uniformity on the electrode surface was established and applied to optimize fluidic parameters in an ECLIA measurement system. By combining microscopic imaging with image analysis, magnetic bead spreading behavior under different flow conditions was systematically characterized and correlated with luminescence signal intensity. Optimization of the flow rate (18.46 µL·s<sup>-1</sup>) improved bead distribution uniformity and resulted in a 26.32% increase in luminescence intensity without altering bead coverage or assay chemistry. The optimized system was further validated using thyroid-stimulating hormone (TSH) detection, showing a linear response over 0.016-120 µIU·mL<sup>-1</sup> (R<sup>2</sup> > 0.996) and high consistency with a commercial analyzer (R<sup>2</sup> = 0.998) from Roche. These results demonstrate that quantitative control of magnetic bead distribution provides an effective strategy for improving ECLIA performance and offers a general optimization framework for bead-based electrochemiluminescence systems.
Authors
- Xinyu Huang (ORCID: https://orcid.org/0000-0002-3449-1907)
- Xiang Cao
- Hengbo Lei
- Yang Ge
- Yuguo Tang
Institutions
- Shenyang Medical College (CN)
- University of Science and Technology of China (CN)
- Chinese Academy of Sciences (CN)
- Suzhou Institute of Biomedical Engineering and Technology (CN)
Publication Details
- Journal
- Bioengineering
- Published
- 2026-03-13
- DOI
- https://doi.org/10.3390/bioengineering13030333
- Primary Topic
- Advanced biosensing and bioanalysis techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Liaoning Province
- Shenzhen Science and Technology Innovation Program