Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy.
There is no satisfactory mechanism to detect premalignant lesions in the upper aero-digestive tract. Fluorescence spectroscopy has potential to bridge the gap between clinical examination and invasive biopsy; however, optimal excitation wavelengths have not yet been determined. The goals of this study were to determine optimal excitation-emission wavelength combinations to discriminate normal and precancerous/cancerous tissue, and estimate the performance of algorithms based on fluorescence. Fluorescence excitation-emission matrices (EEM) were measured in vivo from 62 sites in nine normal volunteers and 11 patients with a known or suspected premalignant or malignant oral cavity lesion. Using these data as a training set, algorithms were developed based on combinations of emission spectra at various excitation wavelengths to determine which excitation wavelengths contained the most diagnostic information. A second validation set of fluorescence EEM was measured in vivo from 281 sites in 56 normal volunteers and three patients with a known or suspected premalignant or malignant oral cavity lesion. Algorithms developed in the training set were applied without change to data from the validation set to obtain an unbiased estimate of algorithm performance. Optimal excitation wavelengths for detection of oral neoplasia were 350, 380 and 400 nm. Using only a single emission wavelength of 472 nm, and 350 and 400 nm excitation, algorithm performance in the training set was 90% sensitivity and 88% specificity and in the validation set was 100% sensitivity, 98% specificity. These results suggest that fluorescence spectroscopy can provide a simple, objective tool to improve in vivo identification of oral cavity neoplasia.
Heintzelman
D L
DL
Department of Electrical and Computer Engineering, University of Texas at Austin, USA.
Utzinger
U
U
Fuchs
H
H
Zuluaga
A
A
Gossage
K
K
Gillenwater
A M
AM
Jacob
R
R
Kemp
B
B
Richards-Kortum
R R
RR
D000465:Algorithms; D016022:Case-Control Studies; D006801:Humans; D009062:Mouth Neoplasms / Q000175:diagnosis*; D018462:Photobiology; D011230:Precancerous Conditions / Q000175:diagnosis; D013050:Spectrometry, Fluorescence / Q000379:methods*