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A pilot study of autofluorescence in the diagnosis of pleural disease
Feng Wang1, Zhen Wang1, Zhaohui Tong1
1Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Background:
Conventional medical thoracoscopy (MT), routinely performed in patients with pleural disease, does not always lead to a conclusive diagnosis. The endoscopic appearance of pleural diseases under white light could be misleading. Autofluorescence has been shown to be an interesting and effective diagnostic tool. The objective of this study was to evaluate the diagnostic value of autofluorescence imaging during MT.
Methods:
Patients with undiagnosed pleural effusion admitted to our clinical center between August 2013 and February 2014 were enrolled. MT was performed first with white light and then by autofluorescence. Endoscopic results of different diseases were recorded, and biopsy specimens were obtained for pathologic analysis. We calculated the diagnostic sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the two methods by comparing them with the pathologic results.
Results:
Thirty-seven eligible patients were studied, including 21 with malignancy, nine with tuberculous pleurisy, three with infective pleurisy, and four with no diagnosed condition. Autofluorescence revealed additional malignant lesions, which were missed under white light in five patients. The diagnostic sensitivity and NPV of autofluorescence were 100% (95% CI, 98.5%-100%) and 100% (95% CI, 93.9%-100%), respectively. Autofluorescence was superior to white light, with a sensitivity of 92.8% (95% CI, 89.3%-95.3%) and NPV of 76.8% (95% CI, 67.0%-84.4%). For the specificity and PPV, no significant difference was found.
Conclusions:
The advantage of autofluorescence is its high sensitivity and NPV. It is useful to detect microlesions and delineate the pathologic margins. Autofluorescence can benefit patients with its better visualization.
