On July 15, the research team led by Academician Dai Qionghai and Associate Professor Wu Jiamin from the Department of Automation at Tsinghua University published a research paper titled "High-Fidelity, High-Speed Fluorescence Lifetime Microscopy Imaging via First-Photon Event Detection" in Nature Biotechnology. The study introduces a fluorescence lifetime microscopy imaging method known as EFLIM, which leverages first-photon event detection. By treating each laser excitation as a binary event—essentially determining whether the first photon is detected—and employing spatiotemporal self-supervised denoising techniques, this method effectively harnesses sparse photon data. Under conditions of equivalent imaging quality, EFLIM reduces the required photon count by over two orders of magnitude, achieving stable lifetime image reconstruction with an average of less than one photon per pixel.

The research team rigorously validated EFLIM’s performance across four biological systems: in vivo mouse brain imaging, subcellular calcium dynamics in living cells, multi-component dynamic imaging of immune responses in lymph nodes, and label-free rapid pathological imaging of human brain gliomas. Experimental results confirm that EFLIM consistently produces high signal-to-noise ratio fluorescence lifetime images even under extremely low-light conditions, outperforming existing methods across all evaluated metrics. This breakthrough offers a powerful new tool for advancing research in neuroscience, immunology, and clinical pathology diagnosis.