Stainless Steel vs Calcium Fluoride for biomedical Raman Spectroscopy
- 1University College London
Abstract
Raman spectroscopy (RS) has been shown to differentiate various disease states in tissue samples, yet the impact of sample substrate on spectral quality and downstream machine-learning (ML) performance is under-explored. We collected 960 spectra from 36 formalin-fixed, paraffin-embedded colonic specimens mounted in parallel on calcium fluoride (CaF2) and mirrored stainless-steel (SS) slides. Raw SS spectra were more intense than CaF2, and routine dewaxing left prominent paraffin peaks on CaF2 that were largely absent on SS. Extending CaF2 xylene immersion to 48 h reduced key paraffin peaks by 11 to 23%, aligning its biochemical profile with SS. Nested cross-validated classifiers were built to distinguish true disease (T1) from epithelial misplacement (EM). The highest accuracies were observed on SS (0.65 - 0.66), while CaF2 improved from 0.41 - 0.57 to 0.65 - 0.69 after extended dewaxing, chiefly via gains in recall. Although optimal dewaxing renders CaF2 diagnostically non-inferior, SS still offers superior accuracy, faster preparation, at approximately 4% of the cost, supporting its integration into scalable, AI-enabled RS pathology workflows.
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BibTeX
@misc{ng2026stainless,
title = {{Stainless Steel vs Calcium Fluoride for biomedical Raman Spectroscopy}},
author = {C. Ng and N. Blake and G. Thomas},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.09.753418},
url = {https://www.biorxiv.org/content/10.64898/2026.10.09.753418v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Stainless Steel vs Calcium Fluoride for biomedical Raman Spectroscopy
AU - C. Ng
AU - N. Blake
AU - G. Thomas
PY - 2026
DA - 2026/10/09
PB - bioRxiv
DO - 10.64898/2026.10.09.753418
UR - https://www.biorxiv.org/content/10.64898/2026.10.09.753418v1
AB - Raman spectroscopy (RS) has been shown to differentiate various disease states in tissue samples, yet the impact of sample substrate on spectral quality and downstream machine-learning (ML) performance is under-explored. We collected 960 spectra from 36 formalin-fixed, paraffin-embedded colonic specimens mounted in parallel on calcium fluoride (CaF2) and mirrored stainless-steel (SS) slides. Raw SS spectra were more intense than CaF2, and routine dewaxing left prominent paraffin peaks on CaF2 that were largely absent on SS. Extending CaF2 xylene immersion to 48 h reduced key paraffin peaks by 11 to 23%, aligning its biochemical profile with SS. Nested cross-validated classifiers were built to distinguish true disease (T1) from epithelial misplacement (EM). The highest accuracies were observed on SS (0.65 - 0.66), while CaF2 improved from 0.41 - 0.57 to 0.65 - 0.69 after extended dewaxing, chiefly via gains in recall. Although optimal dewaxing renders CaF2 diagnostically non-inferior, SS still offers superior accuracy, faster preparation, at approximately 4% of the cost, supporting its integration into scalable, AI-enabled RS pathology workflows.
ER -