Design of a Dispersive 1064 nm Fiber Probe Raman Imaging Spectrometer and Its Application to Human Bladder Resectates

Abstract

This study introduces a compact Raman spectrometer with a 1064 nm excitation laser coupled with a fiber probe and an inexpensive motorized stage, offering a promising alternative to widely used Raman imaging instruments with 785 nm excitation lasers. The benefits of 1064 nm excitation for biomedical applications include further suppression of fluorescence background and deeper tissue penetration. The performance of the 1064 nm instrument in detecting cancer in human bladder resectates is demonstrated. Raman images with 1064 nm excitation were collected ex vivo from 10 human tumor and non-tumor bladder specimens, and the results are compared to previously published Raman images with 785 nm excitation. K-Means cluster (KMC) analysis is used after pre-processing to identify Raman signatures of control, tumor, necrosis, and lipid-rich tissues. Hierarchical cluster analysis (HCA) groups the KMC centroids of all specimens as input. The tools for data processing and hyperspectral analysis were compiled in an open-source Python library called SpectraMap (SpMap). In spite of lower spectral resolution, the 1064 nm Raman instrument can differentiate between tumor and non-tumor bladder tissues in a similar way to 785 nm Raman spectroscopy. These findings hold promise for future clinical hyperspectral Raman imaging, in particular for specimens with intense fluorescence background, e.g., kidney stones that are discussed as another widespread urological application.

Keywords

• bladder tumor
• Raman imaging
• 1064 nm
• cluster analysis
• Python toolbox