Evaluation of Minimum-to-Severe Global and Macrovesicular Steatosis in Human Liver Specimens: A Portable Ambient Light-Compatible Spectroscopic Probe.

BACKGROUND AND AIMS: Hepatic steatosis (HS), particularly macrovesicular steatosis (MaS), influences transplant outcomes. Accurate assessment of MaS is crucial for graft selection. While traditional assessment methods have limitations, non-invasive spectroscopic techniques like Raman and reflectance spectroscopy offer promise. This study aimed to evaluate the efficacy of a portable ambient light-compatible spectroscopic system in assessing global HS and MaS in human liver specimens. METHODS: A two-stage approach was employed on thawed snap-frozen human liver specimens under ambient room light: biochemical validation involving a comparison of fat content from Raman and reflectance intensities with triglyceride (TG) quantifications and histopathological validation, contrasting Raman-derived fat content with evaluations by an expert pathologist and a "Positive Pixel Count" algorithm. Raman and reflectance intensities were combined to discern significant (≥ 10%) discrepancies in global HS and MaS. RESULTS: The initial set of 16 specimens showed a positive correlation between Raman and reflectance-derived fat content and TG quantifications. The Raman system effectively differentiated minimum-to-severe global and macrovesicular steatosis in the subsequent 66 specimens. A dual-variable prediction algorithm was developed, effectively classifying significant discrepancies (> 10%) between algorithm-estimated global HS and pathologist-estimated MaS. CONCLUSION: Our study established the viability and reliability of a portable spectroscopic system for non-invasive HS and MaS assessment in human liver specimens. The compatibility with ambient light conditions and the ability to address limitations of previous methods marks a significant advancement in this field. By offering promising differentiation between global HS and MaS, our system introduces an innovative approach to real-time and quantitative donor HS assessments. The proposed method holds the promise of refining donor liver assessment during liver recovery and ultimately enhancing transplantation outcomes.

An interferometric-based tensile tester to resolve damage events within reconstituted multi-filaments collagen bundles.

Understanding how mechanical damage propagates in load-bearing tissues such as skin, tendons and ligaments, is key to developing regenerative medicine solutions for when these tissues fail. For collagenous tissues in particular, damage is typically assessed after mechanical testing using a broad range of microscopy techniques because standard tensile testing systems do not have the time and force sensitivity to resolve mechanical damage events. Here we introduce an interferometric detection scheme to measure the displacement of a cantilever with a resolution of 0.03% of full scale at a sampling rate of 5000 samples/s. The system is validated using collagen fibers engineered to mimic mammalian tendons. The system can detect sudden decrease in force due to slippage between collagen filaments, one to five microns in diameter, within a fiber in air. It can also detect yield events associated with local collagen unfolding or sliding within collagen fibrils within a fiber in liquid. This is opening the road to the sub-failure study of damage propagation within a broad range of hierarchical biomaterials.

Real-time assessment of liver fat content using a filter-based Raman system operating under ambient light through lock-in amplification.

During liver procurement, surgeons mostly rely on their subjective visual inspection of the liver to assess the degree of fatty infiltration, for which misclassification is common. We developed a Raman system, which consists of a 1064 nm laser, a handheld probe, optical filters, photodiodes, and a lock-in amplifier for real-time assessment of liver fat contents. The system performs consistently in normal and strong ambient light, and the excitation incident light penetrates at least 1 mm into duck fat phantoms and duck liver samples. The signal intensity is linearly correlated with MRI-calibrated fat contents of the phantoms and the liver samples.