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Research Papers

Clinical study for classification of benign, dysplastic, and malignant oral lesions using autofluorescence spectroscopy

[+] Author Affiliations
Diana C. G. de Veld

University Hospital Groningen, Department of Oral and Maxillofacial Surgery, Division of Oncology, Groningen?9700?RB

University Hospital Rotterdam, Department of Radiation Oncology, Photodynamic Therapy & Optical Spectroscopy Program, PO Box 2040, 3000 CA?Rotterdam, The Netherlands

Marina Skurichina

Technical University of Delft, Pattern Recognition Group, Faculty of Applied Sciences, Delft, The Netherlands

Max J. H. Witjes

University Hospital Groningen, Department of Oral and Maxillofacial Surgery, Division of Oncology, Groningen?9700?RB, The Netherlands

Robert P. W. Duin

Technical University of Delft, Pattern Recognition Group, Faculty of Applied Sciences, Delft, The Netherlands

Henricus J. C. M. Sterenborg

University Hospital Rotterdam, Department of Radiation Oncology, Photodynamic Therapy & Optical Spectroscopy Program, PO Box 2040, 3000 CA?Rotterdam, The Netherlands E-mail: h.j.c.m.sterenborg@erasmusmc.nl

Jan L. N. Roodenburg

University Hospital Groningen, Department of Oral and Maxillofacial Surgery, Division of Oncology, Groningen?9700?RB, The Netherlands

J. Biomed. Opt. 9(5), 940-950 (Sep 01, 2004). doi:10.1117/1.1782611
History: Received Sep. 16, 2003; Revised Jan. 20, 2004; Accepted Feb. 17, 2004; Online September 17, 2004
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Autofluorescence spectroscopy shows promising results for detection and staging of oral (pre-)malignancies. To improve staging reliability, we develop and compare algorithms for lesion classification. Furthermore, we examine the potential for detecting invisible tissue alterations. Autofluorescence spectra are recorded at six excitation wavelengths from 172 benign, dysplastic, and cancerous lesions and from 97 healthy volunteers. We apply principal components analysis (PCA), artificial neural networks, and red/green intensity ratio’s to separate benign from (pre-)malignant lesions, using four normalization techniques. To assess the potential for detecting invisible tissue alterations, we compare PC scores of healthy mucosa and surroundings/contralateral positions of lesions. The spectra show large variations in shape and intensity within each lesion group. Intensities and PC score distributions demonstrate large overlap between benign and (pre-)malignant lesions. The receiver-operator characteristic areas under the curve (ROC-AUCs) for distinguishing cancerous from healthy tissue are excellent (0.90 to 0.97). However, the ROC-AUCs are too low for classification of benign versus (pre-)malignant mucosa for all methods (0.50 to 0.70). Some statistically significant differences between surrounding/contralateral tissues of benign and healthy tissue and of (pre-)malignant lesions are observed. We can successfully separate healthy mucosa from cancers (ROC-AUC>0.9). However, autofluorescence spectroscopy is not able to distinguish benign from visible (pre-)malignant lesions using our methods (ROC-AUC<0.65). The observed significant differences between healthy tissue and surroundings/contralateral positions of lesions might be useful for invisible tissue alteration detection. © 2004 Society of Photo-Optical Instrumentation Engineers.

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© 2004 Society of Photo-Optical Instrumentation Engineers

Citation

Diana C. G. de Veld ; Marina Skurichina ; Max J. H. Witjes ; Robert P. W. Duin ; Henricus J. C. M. Sterenborg, et al.
"Clinical study for classification of benign, dysplastic, and malignant oral lesions using autofluorescence spectroscopy", J. Biomed. Opt. 9(5), 940-950 (Sep 01, 2004). ; http://dx.doi.org/10.1117/1.1782611


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