Label-free pathology by spectrally sliced femtosecond stimulated Raman scattering (SRS) microscopy
Related Experiment Video
Updated: Mar 1, 2026

A Multimodal Wide-Field Fourier-Transform Raman Microscope
Published on: December 30, 2025
Andrew Francis1, Kyla Berry1, Yikai Chen1
1Department of Chemistry, University of Washington, Seattle, Washington, United States of America.
Abstract:
Optical "virtual biopsy" is an attractive way to improve disease diagnosis and surgical guidance. Many optical microscopy techniques have been developed to provide diagnostic information without the need for tissue sectioning or staining. Among these techniques, label-free chemical imaging is the most desirable. Recently, it has been shown that narrowband, picosecond stimulated Raman scattering (SRS) can achieve comparable morphological contrast to hematoxylin and eosin staining (H&E staining), the 'gold standard' of pathology. However, to translate the technique from the bench to the bedside, optimal laser sources and parameters have yet to be identified. Here we describe an improvement to the narrowband SRS microscopy techniques for label-free tissue imaging. Through spectral slicing of broadband, femtosecond pulses, we are able to maintain the same protein/lipid contrast as narrowband SRS while achieving a higher signal-to-noise ratio (SNR). Our method draws upon the benefits of femtosecond pulses (e.g. higher peak power) while preserving those of picosecond pulses (e.g. adequate spectral resolution). We demonstrate this achievement through protein/lipid signal and contrast quantification of mouse brain tissue as a function of bandwidth, and comparison with numerical simulations. Further method validation is provided through imaging of additional mouse tissues: liver, kidney, and skin.
More Related Videos
Related Concept Videos
Super-resolution Fluorescence Microscopy
Raman Spectroscopy: Overview
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...

