Endoscopic autofluorescence micro-spectroimaging of alveoli: comparative spectral analysis of amiodarone-induced pneumonitis patients and healthy smokers

G. Bourg-Heckly , C. Vever-Bizet , W. Blondel , M. Salauen , L. Thiberville

Bibtex , URL
ENDOSCOPIC MICROSCOPY VI, 7893, 789313 (2011)
DOI: 10.1117/12.874733
ISSN: 0277-786X


Fibered confocal fluorescence microscopy (FCFM) with spectroscopic analysis capability was used during bronchoscopy, at 488nm excitation, to record autofluorescence images and associated emission spectra of the alveoli of 5 healthy smoking volunteers and 7 non-smoking amiodarone-induced pneumonitis (AIP) patients. Alveolar fluorescent cellular infiltration was observed in both groups. Our objective was to assess the potential of spectroscopy in differentiating these two groups. Methods: We previously demonstrated that in healthy smokers alveolar elastin backbone and tobacco tar contained in macrophages contribute to the observed signal. Each normalized spectrum was modeled as a linear combination of 3 components: S-exp(lambda) = C-e.S-e(lambda)+ C-t.S-t(lambda)+ C-G.S-G(lambda), C-e, C-t and C-G are amplitude coefficients. S-e(lambda) and S-t(lambda) are respectively the normalized elastin and tobacco tar emission spectra measured experimentally and SG(lambda) a gaussian spectrum with tunable width and central wavelength. Levenbergt-Marquardt algorithm determined the optimal set of coefficients. Results: AIP patient autofluorescence spectra can be uniquely modelized by the linear combination of the elastin spectrum (C-e = 0.61) and of a gaussian spectrum (center wavelength 550nm, width 40nm); the tobacco tar spectrum coefficient C-t is found to be zero. For healthy smoking volunteers, only two spectral components were considered: the tobacco tar component (C-t = 1,03) and the elastin component (C-e = 0). Conclusion: Spectral analysis is able to distinguish cellular infiltrated images from AIP patients and healthy smoking volunteers. It appears as a powerful complementary tool for FCFM.

Cette publication est associée à :

Biophotonique : Spectro-imagerie à visée diagnostique