Paper
23 February 2009 Bladder cancer diagnosis during cystoscopy using Raman spectroscopy
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Abstract
Raman spectroscopy is an optical technique that can be used to obtain specific molecular information of biological tissues. It has been used successfully to differentiate normal and pre-malignant tissue in many organs. The goal of this study is to determine the possibility to distinguish normal tissue from bladder cancer using this system. The endoscopic Raman system consists of a 6 Fr endoscopic probe connected to a 785nm diode laser and a spectral recording system. A total of 107 tissue samples were obtained from 54 patients with known bladder cancer during transurethral tumor resection. Immediately after surgical removal the samples were placed under the Raman probe and spectra were collected and stored for further analysis. The collected spectra were analyzed using multivariate statistical methods. In total 2949 Raman spectra were recorded ex vivo from cold cup biopsy samples with 2 seconds integration time. A multivariate algorithm allowed differentiation of normal and malignant tissue with a sensitivity and specificity of 78,5% and 78,9% respectively. The results show the possibility of discerning normal from malignant bladder tissue by means of Raman spectroscopy using a small fiber based system. Despite the low number of samples the results indicate that it might be possible to use this technique to grade identified bladder wall lesions during endoscopy.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. C. M. Grimbergen, C. F. P. van Swol, R. O. P. Draga, P. van Diest, R. M. Verdaasdonk, N. Stone, and J. H. L. R. Bosch "Bladder cancer diagnosis during cystoscopy using Raman spectroscopy", Proc. SPIE 7161, Photonic Therapeutics and Diagnostics V, 716114 (23 February 2009); https://doi.org/10.1117/12.807811
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Cited by 13 scholarly publications.
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KEYWORDS
Raman spectroscopy

Tissues

Pathology

Bladder

Biopsy

Bladder cancer

Signal to noise ratio

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