The ability to provide quantitative, objective and automated pathological analysis would provide enormous benefits for national cancer screening programmes, in terms of both resource reduction and improved patient wellbeing. The move towards molecular pathology through spectroscopic methods shows great promise, but has been restricted by spectral quality, acquisition times and lack of direct clinical application. In this paper, we present the application of wavelength modulated Raman spectroscopy for the automated label- and fluorescence-free classification of fixed squamous epithelial cells in suspension, such as those produced during a cervical smear test. Direct comparison with standard Raman spectroscopy shows marked improvement of sensitivity and specificity when considering both human papillomavirus (sensitivity +12.0%, specificity +5.3%) and transformation status (sensitivity +10.3%, specificity +11.1%). Studies on the impact of intracellular sampling location and storage effects suggest that wavelength modulated Raman spectroscopy is sufficiently robust to be used in fixed cell classification, but requires further investigations of potential sources of molecular variation in order to improve current clinical tools.
Bibliographical noteFunding Information:
This work was supported by the Engineering and Physical Sciences Research Council and Medical Research Council (EP/L016559/1, EP/P030017/1), and CRUK (A18075 Core Award). We acknowledge M Squared Lasers Ltd for the use of a Solstis laser. Thanks to Professor Ted Hupp for the provision of technical advice and reagents for primary cell culture. We would also like to thank Ramya Bhatia for fixed cell sample donations from the Scottish HPV Archive, and Jan Irvine for facilitating collaboration and research visits.
© 2017 The Authors. Journal of Biophotonics published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
All Science Journal Classification (ASJC) codes
- Materials Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Physics and Astronomy(all)