This study presents a portable spectroscopic system compatible with ambient light to assess hepatic steatosis (HS) and macrovesicular steatosis (MaS) in human liver specimens. Traditional assessment methods for MaS are limited, prompting the need for non-invasive alternatives. The study utilized a two-stage approach on thawed snap-frozen liver specimens. Biochemical validation compared fat content from Raman and reflectance intensities with triglyceride (TG) quantifications, while histopathological validation contrasted Raman-derived fat content with pathologist evaluations and an algorithm. Analysis of 16 specimens showed a positive correlation between spectroscopic data and TG quantifications. The Raman system differentiated various degrees of global HS and MaS in an additional 66 specimens. A dual-variable prediction algorithm classified significant discrepancies (≥10%) between algorithm-estimated global HS and pathologist-estimated MaS. This study demonstrates the viability of a portable spectroscopic system for non-invasive HS and MaS assessment to enhance real-time donor liver assessments during recovery to improve transplantation outcomes.

This study explores a combined strategy of Raman and reflectance spectroscopy for quantifying liver fat content and fat droplet size, crucial in assessing donor livers. By using Monte Carlo simulations and experimental setups with oil-in-water phantoms, our findings indicate that Raman scattering can solely differentiate between varying fat contents, while reflectance intensity is influenced by both fat content and oil droplet size, with a more pronounced sensitivity to fat droplet size. This study demonstrates the efficacy of combined Raman and reflectance spectroscopy in assessing liver steatosis and fat droplet size, potentially aiding in assessing donor livers for transplantation.