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Development of mass spectrometric techniques for 3D imaging and in-vivo analysis of biological tissues (DESI_JeDI-Imaging)
Start date: 01 Sep 2008, End date: 31 Aug 2013 PROJECT  FINISHED 

Recent development of atmospheric pressure desorption ionization methods has opened a unique area of application for analytical mass spectrometry. Most of these methods do not require any modification of samples, and this feature, together with the minimal invasiveness of these methods allows direct analytical interrogation of biological tissues, even the real-time, in-vivo observation of biochemical processes. The proposed research focuses on the development of atmospheric pressure desorption ionization mass spectrometric methods for the characterization of biological tissues. The first question to answer is aimed at the nature of information which can be obtained, using a variety of desorption ionization methods including desorption electrospray ionization and jet desorption ionization methods. Preliminary results show, that APDI-MS methods provide information on lipids, metabolic compounds, drugs and certain proteins. First task of the proposed research is to implement a chemical imaging system, which is capable of producing 3D concentration distribution functions for various constituents of tissue samples. The developed methodology will be used to tackle fundamental pathophysiological problems including development of various malignant tumors. A database will be created for the unequivocal identification of various tissues including healthy and malignant tissue samples. In-vivo applications of MS will also be developed. JeDI-MS,similarly to water jet surgery, also utilizes high velocity water jet can directly be used as an intelligent scalpel. Real-time in-situ tissue identification has the potential of revolutionizing cancer surgery, since this way the amount of removed tissue can be minimized, while the tumor removal efficiency is maximized. The identical experimental platform can also be used to gather real-time in-situ metabolic information, which can help to understand pathophysiological changes.
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