FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm

Paul Bassan; Ashwin Sachdeva; Achim Kohler; Caryn Hughes; Alex Henderson; Jonathan Boyle; Jonathan H. Shanks; Michael Brown; Noel W. Clarke; Peter Gardner

doi:10.1039/C2AN16088A

FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm

Paul Bassan,†^a Ashwin Sachdeva,†^a Achim Kohler,^b Caryn Hughes,^a Alex Henderson,^a Jonathan Boyle,^c Jonathan H. Shanks,^d Michael Brown,^e Noel W. Clarke^e and Peter Gardner*^a

Author affiliations

* Corresponding authors

^a Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess Street, Manchester, UK
E-mail: peter.gardner@manchester.ac.uk
Fax: +0161 306 5201
Tel: +0161 306 4463

^b Nofima Mat, Centre for Biospectroscopy and Data Modelling, Osloveien 1, Norway

^c Research Applications & Collaboration Team, IT Services for Research, Devonshire House, The University of Manchester, Manchester

^d Department of Histopathology, The Christie NHS Foundation Trust, Manchester, UK, UK

^e Genito Urinary Cancer Research Group, School of Cancer and Enabling Sciences, Paterson Institute for Cancer Research, The University of Manchester, Manchester Academic Health Science Centre, and Department of Urology, The Christie NHS Foundation Trust, Manchester, UK, UK

Abstract

Transmission and transflection infrared microscopy of biological cells and tissue suffer from significant baseline distortions due to scattering effects, predominantly resonant Mie scattering (RMieS). This scattering can also distort peak shapes and apparent peak positions making interpretation difficult and often unreliable. A correction algorithm, the resonant Mie scattering extended multiplicative signal correction (RMieS-EMSC), has been developed that can be used to remove these distortions. The correction algorithm has two key user defined parameters that influence the accuracy of the correction. The first is the number of iterations used to obtain the best outcome. The second is the choice of the initial reference spectrum required for the fitting procedure. The choice of these parameters influences computational time. This is not a major concern when correcting individual spectra or small data sets of a few hundred spectra but becomes much more significant when correcting spectra from infrared images obtained using large focal plane array detectors which may contain tens of thousands of spectra. In this paper we show that, classification of images from tissue can be achieved easily with a few (<10) iterations but a reliable interpretation of the biochemical differences between classes could require more iterations. Regarding the choice of reference spectrum, it is apparent that the more similar it is to the pure absorption spectrum of the sample, the fewer iterations required to obtain an accurate corrected spectrum. Importantly however, we show that using three different non-ideal reference spectra, the same unique correction solution can be obtained.

Analyst

FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm

Abstract

Article information

Download Citation

Permissions

FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm

Social activity

Search articles by author

Spotlight

Advertisements