Segmentation-guided photon pooling enables robust single cell analysis and fast fluorescence lifetime imaging...

Area of Science:

• Cellular and Molecular Imaging
• Biophotonics
• Metabolic Imaging

Background:

• Fluorescence lifetime imaging microscopy (FLIM) offers label-free, non-invasive probing of cellular metabolic states.
• Current FLIM methods require long acquisition times due to low signal from endogenous fluorophores, hindering real-time analysis.
• Accurate metabolic profiling necessitates high photon counts for precise multi-exponential decay fitting at the pixel level.

Purpose of the Study:

• To develop a faster method for label-free, single-cell FLIM acquisition and analysis.
• To overcome the limitations of long integration times in conventional FLIM.
• To enable rapid, high-resolution metabolic imaging of living cells.

Main Methods:

• Implementation of a 'region-of-interest' photon pooling technique.
• Acquisition and analysis of FLIM data using the novel photon pooling approach.
• Comparison of acquisition speed and data quality against conventional pixel-level analysis.

Main Results:

• Achieved single-cell metabolic information at acquisition intervals as short as one second.
• Enabled the acquisition of large FLIM mosaics 15 times faster than conventional methods.
• The technique is computationally efficient, requires no machine learning, and integrates with standard software.

Conclusions:

• The 'region-of-interest' photon pooling technique significantly accelerates label-free FLIM.
• This method provides a practical solution for rapid, high-throughput cellular metabolic analysis.
• The developed technique enhances the utility of FLIM for studying dynamic cellular processes.