FTIR Imaging of Tissues: Techniques and Methods of Analysis

In this chapter, we describe biomedical applications of infrared microscopic imaging applied to human tissue sections. The central focus is human diseases including cervical cancer, neurodegenerative pathologies, and dysfunctions of cardiac and liver tiss

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FTIR Imaging of Tissues: Techniques and Methods of Analysis Kamilla Malek, Bayden R. Wood and Keith R. Bambery

Abstract  In this chapter, we describe biomedical applications of infrared microscopic imaging applied to human tissue sections. The central focus is human diseases including cervical cancer, neurodegenerative pathologies, and dysfunctions of cardiac and liver tissues. In addition, we briefly describe the fundamentals of FTIR imaging instrumentation along with spectral pre-processing and hyperspectral image reconstruction. The chapter concludes with a summary of what is required to take FTIR imaging technology into the clinical environment. Keywords  FTIR imaging • Data processing • Cervical cancer • Heart disease • Neurodegenerative pathologies • Liver diseases

15.1 Introduction Fourier Transform infrared (FTIR) spectroscopic imaging is set to become a true independent modality for the diagnosis of disease. The spectroscopic advantage lies in the fact that the chemical change must precede or accompany any morphological change that is symptomatic of disease [1]. The ability to spectroscopically analyse and spatially locate macromolecules within single cells and tissues offers a platform to investigate, diagnose and monitor the treatment of neoplasia and other diseases. In terms of diseases cancer grading by light microscopy is notoriously subjective and highly dependent on the training and experience of the pathologist examining the tissues, as well as the sample quality and quantity. Many neoplasias require anK. Malek () Faculty of Chemistry and Jagiellonian Centre for Experimental Therapeutics, Jagiellonian University, Ingardena 3, 30-060, Krakow, Poland e-mail: [email protected] B. R. Wood Centre for Biospectroscopy and School of Chemistry, Monash University, 3800, Victoria, Australia K. R. Bambery Australian Synchrotron, 800 Blackburn Road, Clayton, VIC, 3168, Australia M. Baranska (ed.), Optical Spectroscopy and Computational Methods in Biology and Medicine, Challenges and Advances in Computational Chemistry and Physics 14, DOI 10.1007/978-94-007-7832-0_15, © Springer Science+Business Media Dordrecht 2014

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cillary diagnostics (e.g., IHC, flow cytometry, PCR) to further characterize their cell origin, clonality and/ or malignant risk, and these tests are often time-consuming, laborious, and costly. Cancer research has focused intently on identifying mutations and other biomarkers to help detect neoplasias earlier, or to develop treatments [2– 5]. However, disease phenotypes are typically extremely complex, and the examination of a single gene mutation for instance, does not adequately characterize the disease [6]. Metabolomics, in comparison to proteomics or genomics, can quantify many metabolites in complex biological systems [7]. Metabolism is more closely associated with an organism’s phenotype [8] and will almost certainly be affected by disease, so metabolic biomarkers are likely to be accurate indicators of disease. Fourier transform infrared spectroscopy and

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