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Detection of cancer cells in prostate tissue with time-resolved fluorescence spectroscopy

 
: Gerich, C.E.; Opitz, J.; Toma, M.; Sergon, M.; Füssel, S.; Nanke, R.; Fehre, J.; Wirth, M.; Baretton, G.; Schreiber, J.

:

Jansen, E.D. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Optical interactions with tissue and cells XXII : 24 - 26 January 2011, San Francisco, California, United States; Part of SPIE photonics west
Bellingham, WA: SPIE, 2011 (Proceedings of SPIE 7897)
ISBN: 978-0-8194-8434-5
ISSN: 1605-7422
Paper 78970R
Conference "Optical Interactions with Tissue and Cells" <22, 2011, San Francisco/Calif.>
Photonics West Conference <2011, San Franciso/Calif.>
English
Conference Paper
Fraunhofer IZFP, Institutsteil Dresden ( IKTS-MD) ()

Abstract
GoALS: Improving cancer diagnosis is one of the important challenges at this time. The precise differentiation between benign and malignant tissue is in the oncology and oncologic surgery of the utmost significance. A new diagnostic system, that facilitates the decision which tissue has to be removed, would be appreciated. In previous studies many attempts were made to use tissue fluorescence for cancer recognition. However, no clear correlation was found between tissue type and fluorescence parameters like time and wavelength dependent fluorescence intensity I(t, ). The present study is focused on cooperative behaviour of cells in benign or malignant prostates tissue reflecting differences in their metabolism. Material and Methods: 50 prostate specimens were obtained directly after radical prostatectomy and from each specimen 6 punch biopsies were taken. Time-resolved fluorescence spectra were recorded for 4 different measurement points for each biopsy. The pathologist evaluated each measurement point separately. An algorithm was developed to determine a relevant parameter of the time dependent fluorescence data (fractal dimension DF). The results of the finding and the DF-value were correlated for each point and then analysed with statistical methods. Results: A total of 1200 measurements points were analysed. The optimal algorithm and conditions for discrimination between malignant and non-malignant tissue areas were found. The correct classification could be stated in 93.4% of analysed points. The ROC-curve (AUC = 0.94) confirms the chosen statistical method as well as it informs about the specificity (0.94) and sensitivity (0.90). Conclusion: The new method seems to offer a very helpful diagnostic tool for pathologists as well as for surgery.

: http://publica.fraunhofer.de/documents/N-189917.html