Normalized Raman Imaging for Studies of Tissue Physiology of the Kidney

Histology is the cornerstone of clinical pathology and an essential tool for many areas of medicine. Nevertheless, conventional histological methods, which rely on fixation, embedding, secitoning, and staining, distort cellular architecture, extract key molecules such as lipids, and introduce variability that severely limits reproducibility. Here, we present Normalized Raman Imaging (NoRI), a form of stimulated Raman scattering applied to organ pathology. NoRI enables quantitative, label-free measurements of proteins and lipids at high spatial resolution. NoRI overcomes heterogeneous light scattering from homogeneous tissues by computationally correcting each signal by the combined Raman signals of protein, lipid, and water. This enables quantitative biomass measurements while preserving tissue architecture, thereby facilitating advanced analysis by convolutional neural networks and feature discovery. Here we apply NoRI to the mouse kidney, showing that such imaging can be used to accurately classify tubule types (median F1 [harmonic mean of precision and recall against manual annotation]=0.93), anatomical regions (F1=0.91), and biological sex (F1=0.97) from regions as small as 132.5μm². Under these circumstances, NoRI has revealed novel sex-specific features, including higher cytoplasmic lipid (+6.9mg/mL; p=0.028), nuclear protein (+26.3mg/mL; p<0.001), and capillary protein concentrations (+3.1mg/mL; p<0.001) in female tubules, along with differences in intracellular lipid droplet morphology. In a time-course model of acute kidney injury (AKI), NoRI captured dynamic changes in protein and lipid organization, most pronounced at day 2 post-injury (F1=0.97), and quantified recovery of brush border structures and lipid droplets over 25 days. Lipid measurements were particularly critical for the high accuracy of feature classification and discovery in AKI (F1=1.0). These results establish NoRI as a reproducible, high-resolution, and fully quantitative framework for tissue analysis and feature discovery, far surpassing conventional histology. By preserving tissue architecture and accurately quantifying lipids and proteins, NoRI provides a unique platform to explore and identify unknown biological phenomena in complex tissues, and present as a powerful diagnostic tool for histopathology.