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  • Title: Autofluorescence endoscopy in the diagnosis of early laryngeal cancer and its precursor lesions.
    Author: Malzahn K, Dreyer T, Glanz H, Arens C.
    Journal: Laryngoscope; 2002 Mar; 112(3):488-93. PubMed ID: 12148859.
    Abstract:
    OBJECTIVES: Because early detection and preoperative assessment of laryngeal cancer and its precursor lesions are essential for curative and function-preserving surgical treatment, autofluorescence endoscopy has been developed to gain more information about the biologic character of these lesions. The aim of the present study is to investigate a high, representative number of patients and to evaluate the diagnostic potential and the limitations of this method. METHODS: In a prospective study, 127 patients were investigated during microlaryngoscopy. A total of 111 patients were suspected of having precancerous or cancerous lesions, 12 had benign lesions, and 4 patients had normal epithelium. Autofluorescence was induced by filtered blue light (380-460 nm) of a xenon short arc lamp and processed by a CCD camera system (D-light-AF system; Storz, Tuttlingen, Germany). Autofluorescence endoscopic images were immediately assessed for diagnosis, correlated to the dysplasia grading system and compared with the histopathologic findings. RESULTS: Normal laryngeal mucosa displayed a typical green fluorescence signal. Moderate and high epithelial dysplasia, carcinoma in situ, and invasive carcinoma showed a diminished green fluorescence. False-negative results (n = 2) were the result of extreme hyperkeratosis. False positive cases (n = 8) either showed mild dysplasia with inflammatory reactions or scarring of the vocal folds. In 105 of 111 cases (94.6%), we found concordant results (sensitivity, 97.3%; specificity, 83.8%). CONCLUSION: Autofluorescence endoscopy facilitates the detection and delineation of precancerous lesions, carcinoma in situ, and microinvasive cancer of the larynx more accurately than clinical observation alone. Scarring, marked hyperkeratosis, and inflammation can limit the predictive value of the method.
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