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Diagnostics of tumor cells by combination of Raman spectroscopy and microfluidics

Title data

Neugebauer, U. ; Dochow, S. ; Krafft, C. ; Bocklitz, Thomas ; Clement, J. H. ; Popp, J.:
Diagnostics of tumor cells by combination of Raman spectroscopy and microfluidics.
In: Clinical and Biomedical Spectroscopy and Imaging II. - Bellingham, Wash. : SPIE , 2011 . - 8087-16 . - (Proceedings of SPIE ; 8087 )
ISBN 978-0-8194-8684-4
DOI: https://doi.org/10.1364/ECBO.2011.80870J

Abstract in another language

Circulating epithelial tumor cells are of increasing importance for tumor diagnosis and therapy monitoring of cancer patients. The definite identification of the rare tumor cells within numerous blood cells is challenging. Therefore, within the research initiative “Jenaer Zell-Identifizierungs-Gruppe” (JenZIG) we develop new methods for cell identification, micromanipulation and sorting based on spectroscopic methods and microfluidic systems. In this contribution we show, that classification models based on Raman spectroscopic analysis allow a precise discrimination of tumor cells from non-tumor cells with high prediction accuracies, up to more than 99% for dried cells. That holds true for unknown cell mixtures (tumor cells and leukocytes/erythrocytes) under dried conditions as well as in solution using the Raman laser as an optical tweezers to keep the cells in focus. We extended our studies by using a capillary system consisting of a quartz capillary, fiber optics and an adjustable fitting to trap cells. This system allows a prediction accuracy of 92.2% on the single cell level, and is a prerequisite for the development of a cell sorting and identification device based on a microfluidic chip. Initial experiments show that tumor cell lines can be differentiated from healthy leukocyte cells with an accuracy of more than 98%.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz
Result of work at the UBT: No
DDC Subjects: 500 Science > 530 Physics
Date Deposited: 15 May 2023 13:32
Last Modified: 15 May 2023 13:32
URI: https://eref.uni-bayreuth.de/id/eprint/76349