OBJECTIVES: This paper is aimed at establishing infrared spectral patterns for the different tissue types found in, and for different stages of disease of squamous cervical epithelium. Methods for the unsupervised distinction of these tissue types are discussed. METHODS: Fourier transform infrared (FTIR) maps of the squamous and glandular cervical epithelium, and of the cervical transformation zone, were obtained and analyzed by multivariate unsupervised hierarchical cluster methods. The resulting clusters are correlated to the corresponding stained histopathological features in the tissue sections. RESULTS: Multivariate statistical analysis of FTIR spectra collected for tissue sections permit an unsupervised method of distinguishing tissue types, and of differentiating between normal and diseased tissue. By analyzing different spectral windows and comparing the results with histology, we found the amide I and II region (1740-1470 cm(-1)) to be very important in correlating anatomical and histopathological features in tissue to spectral clusters. Since an unsupervised, rather than a diagnostic, algorithm was used in these efforts, no statistical analysis of false-positive/false-negative results is reported at this time. CONCLUSIONS: The combination of FTIR micro-spectroscopy and multivariate spectral processing provides important insights into the fundamental spectral signatures of individual cells and consequently shows potential as a diagnostic tool for cervical cancer.
OBJECTIVES: This paper is aimed at establishing infrared spectral patterns for the different tissue types found in, and for different stages of disease of squamous cervical epithelium. Methods for the unsupervised distinction of these tissue types are discussed. METHODS: Fourier transform infrared (FTIR) maps of the squamous and glandular cervical epithelium, and of the cervical transformation zone, were obtained and analyzed by multivariate unsupervised hierarchical cluster methods. The resulting clusters are correlated to the corresponding stained histopathological features in the tissue sections. RESULTS: Multivariate statistical analysis of FTIR spectra collected for tissue sections permit an unsupervised method of distinguishing tissue types, and of differentiating between normal and diseased tissue. By analyzing different spectral windows and comparing the results with histology, we found the amide I and II region (1740-1470 cm(-1)) to be very important in correlating anatomical and histopathological features in tissue to spectral clusters. Since an unsupervised, rather than a diagnostic, algorithm was used in these efforts, no statistical analysis of false-positive/false-negative results is reported at this time. CONCLUSIONS: The combination of FTIR micro-spectroscopy and multivariate spectral processing provides important insights into the fundamental spectral signatures of individual cells and consequently shows potential as a diagnostic tool for cervical cancer.
Authors: Bayden R Wood; Tatyana Chernenko; Christian Matthäus; Max Diem; Connie Chong; Uditha Bernhard; Cassandra Jene; Alice A Brandli; Don McNaughton; Mark J Tobin; Alan Trounson; Orly Lacham-Kaplan Journal: Anal Chem Date: 2008-12-01 Impact factor: 6.986
Authors: Andrew T Harris; Andrew Rennie; Haroon Waqar-Uddin; Sarah R Wheatley; Samit K Ghosh; Dominic P Martin-Hirsch; Sheila E Fisher; Alec S High; Jennifer Kirkham; Tahwinder Upile Journal: Head Neck Oncol Date: 2010-10-05