Why Metabolism Matters in Steatotic Liver Disease
Metabolic dysfunction-associated steatotic liver disease (MASLD) is driven by excessive lipid accumulation in hepatocytes, triggering mitochondrial stress and progressive metabolic dysfunction. As the disease advances, mitochondrial respiration becomes increasingly impaired, contributing to oxidative stress, inflammation, fibrosis, and eventually liver failure.
Although non-invasive tests continue to improve, liver biopsy remains the clinical gold standard for assessing fibrosis and structural tissue changes. However, conventional histology primarily evaluates tissue morphology and often cannot directly report on the metabolic state of cells. In addition, histological scoring can be subjective and time-consuming, particularly in complex cases requiring multiple pathologists for evaluation.
This creates a critical gap between structural assessment and functional metabolic characterization. Since mitochondrial dysfunction is tightly linked to MASLD progression, imaging approaches capable of directly probing cellular metabolism could provide valuable complementary information beyond conventional histology.
FLIM as a Label-Free Readout of Liver Metabolism
To investigate metabolic dysfunction in liver tissue, Purdie et al., Communications Medicine (2026)1, the researchers applied fluorescence lifetime imaging microscopy (FLIM) to measure the autofluorescence lifetimes of endogenous metabolic cofactors. Instead of relying on exogenous dyes or labels, the method exploits naturally fluorescent molecules such as flavin adenine dinucleotide (FAD), which participate directly in mitochondrial energy metabolism.
Using TCSPC-based FLIM, fluorescence decay dynamics were recorded following pulsed 405 nm excitation. The measured fluorescence lifetimes varied depending on the molecular binding state of the metabolic cofactors, allowing the researchers to identify regions with distinct fluorescence lifetime signatures associated with different metabolic states. The study combined cellular models, precision-cut liver slices, and human liver biopsy samples to investigate how metabolic stress alters fluorescence lifetime signatures across disease conditions. Complementary microscopy experiments confirmed lipid accumulation, mitochondrial fragmentation, and impaired mitochondrial function in steatotic models.
Importantly, the FLIM workflow remained entirely label-free for metabolic imaging itself, enabling direct assessment of tissue metabolism from endogenous autofluorescence signals.
FLIM Reveals Metabolic Heterogeneity Beyond H&E Histology
One of the most significant findings of the study was that FLIM identified metabolic heterogeneity in liver tissue that was not clearly detectable using standard H&E histology alone. Healthy liver samples showed relatively uniform fluorescence lifetime distributions, whereas tissue affected by steatosis and fibrosis exhibited distinct regions with shorter fluorescence lifetimes. These regions were frequently associated with lipid droplet accumulation and impaired mitochondrial metabolism.
To quantify these metabolic abnormalities, the researchers introduced the FLIM-associated metabolic dysfunction (FAMD) index. The index measures the proportion of image regions exhibiting both high fluorescence intensity and short fluorescence lifetimes, features associated with metabolic dysfunction and consistent with reduced oxidative phosphorylation.
Interestingly, some tissue samples that appeared histologically normal still displayed elevated FAMD indices and localized regions of metabolic disruption. This suggests that FLIM may detect early metabolic abnormalities before clear structural changes become visible in conventional histological assessment.
Beyond simple structural imaging, the study therefore demonstrates how autofluorescence FLIM can provide functional insight into tissue metabolism and reveal spatial heterogeneity across human liver biopsies.
Toward Faster and More Quantitative Liver Biopsy Assessment with Luminosa
The findings highlight the potential of FLIM as a complementary tool for liver biopsy assessment in metabolically driven diseases. Because the technique directly reports on metabolic state without requiring exogenous staining, it may provide a faster and more quantitative workflow for evaluating tissue dysfunction. The workflow was compatible with standard FFPE tissue sections and could be integrated alongside conventional histopathology without destroying valuable tissue samples. In addition, fluorescence lifetime measurements themselves are largely independent of excitation intensity and detector gain settings, supporting reproducible metabolic characterization across samples.
These measurements were performed using Luminosa, PicoQuant’s dedicated single-photon counting confocal FLIM microscope. By combining single photon counting with an integrated fluorescence lifetime imaging workflow, the system enabled quantitative label-free metabolic imaging of hepatocyte models and human liver tissue throughout the study.
Making Advanced FLIM Accessible to Core Facilities
Beyond the scientific findings, the study also highlights an important consideration for bioimaging core facilities. Advanced imaging technologies only become widely adopted when they are accessible to users with different levels of microscopy experience. In an interview with PicoQuant, Professor Marco Fritzsche highlighted the accessibility of Luminosa for bioimaging core facilities. During an evaluation at the University of Oxford, a summer student with little prior fluorescence microscopy experience was able to generate independent data after only one to two days of training. This combination of quantitative FLIM performance and an intuitive workflow can help core facilities provide advanced metabolic imaging to a broader research community while reducing training effort and enabling faster adoption of fluorescence lifetime microscopy.
1 Reference: Kaitlyn Purdie, Narain Karedla, Thea Guy, Anna V. Schepers, Ana Isabel Espirito Santo, Huw Colin-York, Kseniya Korobchevskaya, Helena Coker, Carl Lee, Alex Gordon-Weeks, Jagdeep Nanchahal & Marco Fritzsche. Metabolic profiling of steatotic liver disease by fluorescence lifetime imaging microscopy. Commun Med 6, 369 (2026). https://doi.org/10.1038/s43856-026-01605-7
