Version 1
: Received: 12 April 2024 / Approved: 12 April 2024 / Online: 15 April 2024 (09:07:12 CEST)
How to cite:
Munoz-Bolanos, J.D.; Shaik, T.A.; Miernik, A.; Popp, J.; Krafft, C. Design of a Dispersive 1064 nm Fiber Probe Raman Imaging Spectrometer and Its Application to Human Bladder Resectates. Preprints2024, 2024040864. https://doi.org/10.20944/preprints202404.0864.v1
Munoz-Bolanos, J.D.; Shaik, T.A.; Miernik, A.; Popp, J.; Krafft, C. Design of a Dispersive 1064 nm Fiber Probe Raman Imaging Spectrometer and Its Application to Human Bladder Resectates. Preprints 2024, 2024040864. https://doi.org/10.20944/preprints202404.0864.v1
Munoz-Bolanos, J.D.; Shaik, T.A.; Miernik, A.; Popp, J.; Krafft, C. Design of a Dispersive 1064 nm Fiber Probe Raman Imaging Spectrometer and Its Application to Human Bladder Resectates. Preprints2024, 2024040864. https://doi.org/10.20944/preprints202404.0864.v1
APA Style
Munoz-Bolanos, J.D., Shaik, T.A., Miernik, A., Popp, J., & Krafft, C. (2024). Design of a Dispersive 1064 nm Fiber Probe Raman Imaging Spectrometer and Its Application to Human Bladder Resectates. Preprints. https://doi.org/10.20944/preprints202404.0864.v1
Chicago/Turabian Style
Munoz-Bolanos, J.D., Juergen Popp and Christoph Krafft. 2024 "Design of a Dispersive 1064 nm Fiber Probe Raman Imaging Spectrometer and Its Application to Human Bladder Resectates" Preprints. https://doi.org/10.20944/preprints202404.0864.v1
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 conclusion, the 1064 nm Raman system 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 imaging.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
