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Updated: Feb 17, 2026
Fluorescence Lifetime Macro Imager for Biomedical Applications
Published on: April 7, 2023
Multi-parameter fluorescence lifetime imaging for high-noise neuroscience applications
Abdelrahman M Salem1, Christopher M Lacny1, Paula-Marie E Ivey1
1Purdue University, West Lafayette, IN 47907, USA.
Abstract:
Fluorescence lifetime imaging microscopy (FLIM) is a sensitive technique that provides insight into molecular interactions, making it a powerful tool for understanding protein dynamics in neurodegenerative diseases. However, longitudinal FLIM studies over a number of days aimed at capturing complex protein behavior in live samples with high spatial granularity are limited by the need for rapid acquisition, implying few signal photons and high noise. Microscopy studies are further challenged by the complex lifetime mixtures present in many samples, leading to a more challenging extraction problem and the prospect of obscuring insight into the underlying molecular interactions. To enable accurate recovery in such situations, we present a noise estimation method that allows precise, pixel-wise determination of fluorescence lifetime parameters in such high-noise environments. In addition, we introduce a multi-exponential constrained fitting approach that enables robust multiparameter extraction from measured data with noisy data typical of neuron studies. The approach is validated using reference dyes and is further illustrated for neuronal imaging of the aggregation of alpha-synuclein, a key protein related to the onset and progression of Parkinson's disease. More broadly, reliable studies of protein dynamics become possible, thereby providing a means to advance our understanding of neurodegenerative disease etiology and offering applications across diverse molecular systems and in various disciplines.
Insights
We developed new methods for Fluorescence Lifetime Imaging Microscopy (FLIM) to accurately analyze noisy cellular data. This improves understanding of protein dynamics in neurodegenerative diseases like Parkinson's.
Area of Science:
- Biophysics
- Neuroscience
- Microscopy
Background:
- Fluorescence Lifetime Imaging Microscopy (FLIM) offers insights into molecular interactions and protein dynamics relevant to neurodegenerative diseases.
- Longitudinal FLIM studies in live samples are hindered by rapid acquisition needs, resulting in low signal-to-noise ratios and complex lifetime mixtures.
- Extracting accurate molecular interaction data from noisy FLIM images is challenging, potentially obscuring critical biological insights.
Purpose of the Study:
- To develop advanced methods for precise pixel-wise determination of fluorescence lifetime parameters in high-noise environments.
- To introduce a robust multi-exponential constrained fitting approach for reliable multiparameter extraction from noisy microscopy data.
- To validate the developed methods and demonstrate their application in neuronal imaging of alpha-synuclein aggregation.
Main Methods:
- A novel noise estimation method for accurate, pixel-wise fluorescence lifetime parameter determination.
- A multi-exponential constrained fitting approach for robust multiparameter extraction from noisy data.
- Validation using reference dyes and application to neuronal imaging of alpha-synuclein.
Main Results:
- Precise, pixel-wise determination of fluorescence lifetime parameters in high-noise environments.
- Robust multiparameter extraction from noisy neuronal imaging data.
- Successful validation and illustration in the context of Parkinson's disease-related protein aggregation.
Conclusions:
- The developed methods enable accurate fluorescence lifetime analysis in challenging, high-noise conditions typical of live neuronal studies.
- This advancement facilitates reliable studies of protein dynamics, crucial for understanding neurodegenerative disease etiology.
- The approach has broad applicability across diverse molecular systems and scientific disciplines.
