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Classification of fixed urological cells using Raman tweezers
Tim J Harvey1, Caryn Hughes, Andrew D Ward
1School of Chemical Engineering and Analytical Science, Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess Street, Manchester, UK.
Journal of Biophotonics
|April 4, 2009
Summary
Raman tweezers can classify fixed urological cells, including prostate cancer and benign hyperplasia cells, with high accuracy. Fixative choice impacts results, but urine exposure does not hinder classification performance.
Area of Science:
- Biomedical Optics
- Spectroscopy
- Urological Oncology
Background:
- Raman tweezers methodology was previously developed to differentiate live prostate cancer (CaP) and bladder cell lines.
- This study expands on prior work by investigating fixed cells and additional cell types.
Purpose of the Study:
- To investigate the efficacy of Raman tweezers for classifying chemically fixed urological cell lines.
- To compare the performance of two fixative methods (SurePath and formalin/PBS) for cell classification.
- To assess the impact of urine exposure on cell classification accuracy.
Main Methods:
- Chemically fixed urological cells (CaP, BPH, urethral) were analyzed using Raman tweezers with a 514.5 nm Ar-ion laser.
- Spectra were collected in back-scattering configuration.
- Principal component-linear discriminate analysis (PC-LDA) models were generated and validated via blind comparison.
Main Results:
- High classification accuracies were achieved: >72% sensitivity and >90% specificity for SurePath fixed cells.
- >93% sensitivity and >98% specificity were achieved for formalin/PBS fixed cells, attributed to better signal-to-noise ratio.
- Exposure to urine for up to 12 hours did not negatively impact cell classification results.
Conclusions:
- Raman tweezers, particularly with formalin/PBS fixation, offer a highly accurate method for classifying fixed urological cell lines.
- The technique demonstrates robustness, as urine exposure does not compromise classification performance.
- This approach shows potential for objective classification of urological cell types.
