Advancing Point-of-Care Diagnosis: Digitalizing Combinatorial Biomarker Signals for Lupus Nephritis

Author:

Guo Jiechang12,Teymur Aygun1,Tang Chenling1ORCID,Saxena Ramesh3ORCID,Wu Tianfu1ORCID

Affiliation:

1. Department of Biomedical Engineering, University of Houston, Houston, TX 77024, USA

2. Department of Computer Science, University of Houston, Houston, TX 77024, USA

3. Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX 75390, USA

Abstract

To improve the efficiency and patient coverage of the current healthcare system, user-friendly novel homecare devices are urgently needed. In this work, we developed a smartphone-based analyzing and reporting system (SBARS) for biomarker detection in lupus nephritis (LN). This system offers a cost-effective alternative to traditional, expensive large equipment in signal detection and quantification. This innovative approach involves using a portable and affordable microscopic reader to capture biomarker signals. Through smartphone-based image processing techniques, the intensity of each biomarker signal is analyzed. This system exhibited comparable performance to a commercial Genepix scanner in the detection of two potential novel biomarkers of LN, VISG4 and TNFRSF1b. Importantly, this smartphone-based analyzing and reporting system allows for discriminating LN patients with active renal disease from healthy controls with the area-under-the-curve (AUC) value = 0.9 for TNFRSF1b and 1.0 for VSIG4, respectively, indicating high predictive accuracy.

Funder

National Institutes of Health

Publisher

MDPI AG

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