
AbstractBackground and ObjectivesAutofluorescence and diffuse reflectance spectroscopy have been used separately and combined for tissue diagnostics. Previously, we assessed the value of autofluorescence spectroscopy for the classification of oral (pre‐)malignancies. In the present study, we want to determine the contributions of diffuse reflectance and autofluorescence spectroscopy to diagnostic performance.Study Design/Materials and MethodsAutofluorescence and diffuse reflectance spectra were recorded from 172 oral lesions and 70 healthy volunteers. Autofluorescence spectra were corrected in first order for blood absorption effects using diffuse reflectance spectra. Principal Components Analysis (PCA) with various classifiers was applied to distinguish (1) cancer and (2) all lesions from healthy oral mucosa, and (3) dysplastic and malignant lesions from benign lesions. Autofluorescence and diffuse reflectance spectra were evaluated separately and combined.ResultsThe classification of cancer versus healthy mucosa gave excellent results for diffuse reflectance as well as corrected autofluorescence (Receiver Operator Characteristic (ROC) areas up to 0.98). For both autofluorescence and diffuse reflectance spectra, the classification of lesions versus healthy mucosa was successful (ROC areas up to 0.90). However, the classification of benign and (pre‐)malignant lesions was not successful for raw or corrected autofluorescence spectra (ROC areas <0.70). For diffuse reflectance spectra, the results were slightly better (ROC areas up to 0.77).ConclusionsThe results for plain and corrected autofluorescence as well as diffuse reflectance spectra were similar. The relevant information for distinguishing lesions from healthy oral mucosa is probably sufficiently contained in blood absorption and scattering information, as well as in corrected autofluorescence. However, neither type of information is capable of distinguishing benign from dysplastic and malignant lesions. Combining autofluorescence and reflectance only slightly improved the results. Lasers Surg. Med. © 2005 Wiley‐Liss, Inc.
combined classifiers, Adult, Male, Adolescent, DIAGNOSIS, Diagnosis, Differential, reflectance spectroscopy, Humans, autofluorescence spectroscopy, IN-VIVO, Aged, Aged, 80 and over, Principal Component Analysis, IDENTIFICATION, Spectrum Analysis, Reproducibility of Results, oral cancer, Middle Aged, INTRINSIC FLUORESCENCE, CANCER, cancer detection, FLUORESCENCE SPECTROSCOPY, ROC Curve, TURBID MEDIA, TISSUE, PATTERN-RECOGNITION, Female, EMC MM-03-32-09, Mouth Diseases, Precancerous Conditions, Algorithms, OPTICAL SPECTROSCOPY
combined classifiers, Adult, Male, Adolescent, DIAGNOSIS, Diagnosis, Differential, reflectance spectroscopy, Humans, autofluorescence spectroscopy, IN-VIVO, Aged, Aged, 80 and over, Principal Component Analysis, IDENTIFICATION, Spectrum Analysis, Reproducibility of Results, oral cancer, Middle Aged, INTRINSIC FLUORESCENCE, CANCER, cancer detection, FLUORESCENCE SPECTROSCOPY, ROC Curve, TURBID MEDIA, TISSUE, PATTERN-RECOGNITION, Female, EMC MM-03-32-09, Mouth Diseases, Precancerous Conditions, Algorithms, OPTICAL SPECTROSCOPY
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