Bladder cancer diagnosis during cystoscopy using Raman spectroscopy

M. C.M. Grimbergen, C. F.P. Van Swol, R. O.P. Draga, P. Van Diest, R. M. Verdaasdonk, N. Stone, J. H.L.R. Bosch

Research output: Contribution to journalConference articleAcademicpeer-review

17 Citations (Scopus)
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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.

Original languageEnglish
Article number716114
JournalProgress in Biomedical Optics and Imaging
Volume7161
DOIs
Publication statusPublished - 8 Jun 2009
Externally publishedYes
EventPhotonic Therapeutics and Diagnostics V 2009 - San Jose, United States
Duration: 24 Jan 200926 Jan 2009
Conference number: 5

Keywords

  • Biopsies
  • Bladder cancer
  • Raman spectroscopy

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