title: Infrared spectroscopy of exfoliated cervical cell specimens. Proceed with caution.
abstract: OBJECTIVE
  To determine whether diagnostic information may be recovered from the infrared spectra of exfoliated cell specimens by using a novel spectral feature extraction method, in conjunction with linear and quadratic discriminant analysis, for spectral classification.
  
  
  METHODS
  Over 800 infrared spectra were included in the study, with corresponding clinical diagnoses based upon cytology and, when available, histology reports. Three sets of classification trials were carried out with the aim of distinguishing the spectra corresponding to normal specimens from CIN 1, 2 and 3. For each of these three cases, the procedure was to: (1) develop a set of provisional classification models using only a "training" subset of the spectra, and (2) test each provisional model by its ability to correctly predict the diagnoses on the basis of the remaining spectra.
  
  
  RESULTS
  For optimal classification trials, training set classification accuracies were 68% for normal/CIN 1, 73% for normal/CIN 2 and 81% for normal/CIN 3; for the corresponding test sets the classification accuracies were 60%, 60% and 67%, respectively.
  
  
  CONCLUSIONS
  The infrared spectra of exfoliated cervical cells carry information regarding the presence or absence of dysplasia, and that information is recoverable--albeit imperfectly at this stage--from the spectra of "real life" cell preparations.
authors.affiliation: Spectroscopy Division, Institute for Biodiagnostics, National Research Council of Canada, Winnipeg, Manitoba, Canada. anthony.shaw@nrc.ca
authors.forename: R A
authors.initials: RA
authors.lastname: Shaw
authors.forename: F B
authors.initials: FB
authors.lastname: Guijon
authors.forename: M
authors.initials: M
authors.lastname: Paraskevas
authors.forename: S L
authors.initials: SL
authors.lastname: Ying
authors.forename: H H
authors.initials: HH
authors.lastname: Mantsch
mesh_terms: D000465:Algorithms; D002584:Cervix Uteri / Q000737:chemistry* / Q000473:pathology; D003094:Collagen / Q000032:analysis; D004273:DNA, Neoplasm / Q000032:analysis; D016208:Databases, Factual; D016002:Discriminant Analysis; D004847:Epithelial Cells / Q000737:chemistry / Q000473:pathology; D005260:Female; D006003:Glycogen / Q000032:analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008055:Lipids / Q000032:analysis; D008403:Mass Screening; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D002578:Uterine Cervical Dysplasia / Q000737:chemistry / Q000175:diagnosis; D002583:Uterine Cervical Neoplasms / Q000737:chemistry* / Q000175:diagnosis; D014626:Vaginal Smears / Q000379:methods*
chemical_list: D004273:DNA, Neoplasm; D008055:Lipids; D006003:Glycogen; D003094:Collagen