Fluorescence lifetime imaging microscopy approach reveals quantitative signatures for hepatocellular carcinoma diagnosis.

Hepatocellular carcinoma (HCC) remains a critical global health challenge, and current histopathological diagnosis relies heavily on hematoxylin and eosin (H&E) staining-a widely adopted clinical tool for assessing tissue morphology. However, H&E staining alone cannot provide quantitative data for diagnosis of tumor samples. Poorly differentiated or unclear lesions are difficult to distinguish. Pathologists often need to rely on subjective judgment. Additional immunostaining is usually required to confirm the diagnosis. In this work, we have applied fluorescence lifetime imaging microscopy (FLIM) method into detecting H&E staining HCC tissue sections. This method provided the eosin fluorescence information of tissue sections, resulting in improved diagnostic accuracy and efficiency. We employed FLIM to compare the fluorescence lifetime distributions between the cancerous regions and the corresponding peritumoral regions. These results demonstrated that the fluorescence lifetime values in cancerous tissues significantly exceeded those of peritumoral region tissues, with their averages ranging from 2000-2500 picoseconds (ps) compared to 500-1000 ps in peritumoral region tissues. This finding has indicated higher fluorescence lifetime values of the fluorescent molecules in cancerous regions, suggesting distinct microenvironment of these regions. Furthermore, correlation analysis was applied between the ratio of fluorescence lifetime values and a series of liver function indicators, such as total bilirubin and transaminases, suggesting potential biochemical markers for clinical monitoring and diagnosis of HCC. The synergistic use of FLIM and H&E staining can bridge morphological and functional characterization, providing a quantitative method to investigate HCC microenvironments. This approach not only preserves the diagnostic utility of H&E but also adds metabolic profiling capabilities, facilitating deeper mechanistic exploration of tumor progression. Future work can be explored into integration and optimization of FLIM-H&E protocols in larger samples for further clinical diagnosis.