Normalizing the Optical Signal Enables Robust Assays with Lateral Flow Biosensors

Area of Science:

• Biomedical Diagnostics
• Optical Engineering
• Mobile Health Technology

Background:

• Lateral flow assays (LFAs) offer rapid, point-of-care molecular diagnostics but often lack precision due to environmental optical variations.
• Dedicated optical setups are typically required to ensure accuracy, limiting LFA's on-site applicability.

Purpose of the Study:

• To develop a smartphone-based system for robust, high-precision quantitative analysis of LFAs.
• To enable accurate molecular diagnostics at point-of-use settings without specialized equipment.

Main Methods:

• Introduced quick light normalization exam (qLiNE), a method using a reference card for real-time optical calibration of smartphone images.
• Developed a smartphone app to process LFA test strip images with the reference card, correcting for distortion, illumination, and color imbalances.
• Adapted qLiNE for quantitative detection of cortisol in saliva samples.

Main Results:

• qLiNE provided consistent optical signal, enabling quantitative molecular analyses under diverse illumination conditions.
• The cortisol assay demonstrated high sensitivity (0.16 ng/mL) and speed (15 min).
• The system successfully detected diurnal cortisol variations and stress-induced cortisol level changes.

Conclusions:

• qLiNE transforms smartphones into reliable readers for quantitative LFAs, overcoming previous precision challenges.
• This technology enhances the utility of LFAs for accessible, on-site molecular diagnostics, exemplified by cortisol monitoring.