Version 2 2025-08-14, 07:00Version 2 2025-08-14, 07:00
Version 1 2025-01-17, 05:55Version 1 2025-01-17, 05:55
preprint
posted on 2025-08-14, 07:00authored byLakhvir Singh, Melody Yeh, Linghao Hu, Brian Ko, Mike McShane, Alex Walsh
Luminescence lifetimes provide insight into the local microenvironment
of luminescent molecules, enabling precise measurement of cellular and tissue states.This makes it a powerful tool for research and diagnosis of diseases affecting the skin, brain, eyes, bones, blood vessels, and internal organs, as well as for drug evaluation, benefiting from its high sensitivity, specificity, non-toxicity, and non-ionizing nature. Traditional systems for measuring luminescence lifetimes rely on expensive ultrafast
detectors and electronics. Here, a novel optical luminescence lifetime estimation method, MAX-alif (Modular Analysis and eXtraction System for Affordable Lifetime Imaging of Fluorescence Signals), was developed to provide a high-speed, low-cost, and scalable solution for luminescence lifetime measurements. In MAX-alif, excitation light with sinusoidal intensity modulation is combined with synthetic path-length difference analysis and machine learning regression to compute luminescence lifetimes from intensity image features. An acousto-optical modulator within the detection path transfers the synthesized phase difference between the excitation and emission light into intensity differences that a standard camera can capture. Both simulation and experimental data were used to generate and validate models for the calibration and extraction of lifetime values from intensity datasets. MAX-alif measurements of phosphorescent and fluorescent samples achieved mean and median lifetime values within 5% of the reference lifetime values. By eliminating the need for expensive
hardware and enabling accurate lifetime imaging with standard cameras, MAX-alif allows widespread, cost-effective luminescence lifetime imaging for medical diagnostics applications.
National Institutes of Health (NIH NIGMS R35 GM142990 ); NSF Engineering Research Center for Precise Advanced Technologies and Health Systems for Under-resourced Populations (1648451)