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

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

doi:10.1117/12.876094

22 February 2011 Detection of cancer cells in prostate tissue with time-resolved fluorescence spectroscopy

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

Proceedings Volume 7897, Optical Interactions with Tissue and Cells XXII; 78970R (2011) https://doi.org/10.1117/12.876094
Event: SPIE BiOS, 2011, San Francisco, California, United States

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, λ). 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 D_F ). The results of the finding and the D_F -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.

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C. E. Gerich, J. Opitz, M. Toma, M. Sergon, S. Füssel, R. Nanke, J. Fehre, M. Wirth, G. Baretton, and J. Schreiber "Detection of cancer cells in prostate tissue with time-resolved fluorescence spectroscopy", Proc. SPIE 7897, Optical Interactions with Tissue and Cells XXII, 78970R (22 February 2011); https://doi.org/10.1117/12.876094

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KEYWORDS

Tissues

Luminescence

Fractal analysis

Prostate

Cancer

Statistical analysis

Biopsy

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