Department of Biomedical Engineering, University of Houston, Houston, TX 77024, USA.
Department of Computer Science, University of Houston, Houston, TX 77024, USA.
Biosensors (Basel). 2024 Mar 18;14(3):147. doi: 10.3390/bios14030147.
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.
为了提高当前医疗保健系统的效率和患者覆盖率，迫切需要用户友好的新型家庭护理设备。在这项工作中，我们开发了一种基于智能手机的生物标志物检测分析和报告系统（SBARS），用于狼疮肾炎（LN）的检测。该系统为传统的昂贵大型设备在信号检测和量化方面提供了一种具有成本效益的替代方案。这种创新方法涉及使用便携式和经济实惠的显微镜读取器来捕获生物标志物信号。通过基于智能手机的图像处理技术，分析每个生物标志物信号的强度。该系统在检测两种潜在的 LN 新型生物标志物 VISG4 和 TNFRSF1b 时的性能与商业 Genepix 扫描仪相当。重要的是，这种基于智能手机的分析和报告系统能够区分具有活跃肾脏疾病的 LN 患者和健康对照者，TNFRSF1b 的 AUC 值为 0.9，VSIG4 的 AUC 值为 1.0，表明具有较高的预测准确性。
