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Detection of squamous cell carcinomas and pre‐cancerous lesions in the oral cavity by quantification of 5‐aminolevulinic acid induced fluorescence endoscopic images
Author(s) -
Zheng Wei,
Soo Khee Chee,
Sivanandan Ranjiv,
Olivo Malini
Publication year - 2002
Publication title -
lasers in surgery and medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 112
eISSN - 1096-9101
pISSN - 0196-8092
DOI - 10.1002/lsm.10105
Subject(s) - protoporphyrin ix , fluorescence , pathology , histology , cancer , lesion , medicine , in vivo , photodynamic therapy , oral cavity , basal cell , endoscopy , radiology , chemistry , biology , optics , organic chemistry , physics , microbiology and biotechnology , orthodontics
Background and Objectives Studies of 5‐aminolevulinic acid‐induced protoporphyrin IX fluorescence have shown a sensitivity of 95–100% for oral cancer diagnosis, but the specificity is only about 50–60%. Here, we explore the applicability of quantifying PPIX fluorescence images to improve the diagnostic specificity and detect early oral lesions. Study Design/Materials and Methods PPIX Fluorescence endoscopy and imaging were performed on 28 patients with a known or suspected premalignant or malignant oral cavity lesion. A total of 70 biopsies were taken from the tissue sites imaged for histological analysis. The red‐to‐blue and red‐to‐green intensity ratios were calculated from the fluorescence images to correlate with histology. Results Suspicious lesions display bright reddish fluorescence, while normal mucosas exhibit blue color background in the fluorescence images. The red‐to‐blue and red‐to‐green intensity ratios of malignant tissues are larger than those of benign tissues. Combining the two ratio diagnostic algorithms yields a sensitivity and specificity of 95% and 97%, respectively, exceeding each diagnostic algorithm alone for discriminating malignant tissue from benign tissue. Conclusions Quantifying PPIX fluorescence endoscopic images combined with the ratio diagnostic algorithms developed in this study has the potential to significantly improve the noninvasive diagnosis of oral cavity lesions in vivo. Lasers Surg. Med. 31:151–157, 2002. © 2002 Wiley‐Liss, Inc.