A robust method for autofluorescence-free immunofluorescence using high-speed fluorescence lifetime imaging microscopy.

Autofluorescence from endogenous biomolecules presents a significant challenge in immunofluorescence microscopy, often severely hindering the detection of specific fluorescence signals. While various techniques, including chemical- and quencher-based methods, photobleaching, and digital-based protocols like autofluorescence image subtraction, have been developed to suppress autofluorescence, each approach has inherent limitations that restrict their efficacy across different tissue types. Fluorescence lifetime imaging microscopy (FLIM) offers a powerful alternative by leveraging the distinct lifetime-spectrum profiles of fluorophores to differentiate specific immunofluorescence signals from autofluorescence. However, traditional FLIM methods are slow and have hampered its use for autofluorescence suppression in routine imaging applications. In this study, we demonstrate that GPU-accelerated high-speed FLIM can effectively separate autofluorescence from immunofluorescence signals in various tissue samples, achieving high throughput to meet the demands of biomedical and clinical workflows. Furthermore, our findings show that the FLIM-based autofluorescence suppression method enhances the correlation of immunofluorescence images with immunohistochemistry data, outperforming other methods like chemically-assisted photobleaching and hyperspectral imaging. These results highlight the potential of the high speed FLIM to improve the reliability of immunofluorescence microscopy significantly.