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Communication Dans Un Congrès Année : 2016

Optical elastic scattering for early label-free identification of clinical pathogens

Résumé

We report here on the ability of elastic light scattering in discriminating Gram+, Gram-and yeasts at an early stage of growth (6h). Our technique is non-invasive, low cost and does require neither skilled operators nor reagents. Therefore it is compatible with automation. It is based on the analysis of the scattering pattern (scatterogram) generated by a bacterial microcolony growing on agar, when placed in the path of a laser beam. Measurements are directly performed on closed Petri dishes. The characteristic features of a given scatterogram are first computed by projecting the pattern onto the Zernike orthogonal basis. Then the obtained data are compared to a database so that machine learning can yield identification result. A 10-fold cross-validation was performed on a database over 8 species (15 strains, 1906 scatterograms), at 6h of incubation. It yielded a 94% correct classification rate between Gram+, Gram-and yeasts. Results can be improved by using a more relevant function basis for projections, such as Fourier-Bessel functions. A fully integrated instrument has been installed at the Grenoble hospital's laboratory of bacteriology and a validation campaign has been started for the early screening of SA and MRSA (Staphylococcus aureus, methicillin-resistant S. aureus) carriers. Up to now, all the published studies about elastic scattering were performed in a forward mode, which is restricted to transparent media. However, in clinical diagnostics, most of media are opaque, such as blood-supplemented agar. That is why we propose a novel scheme capable of collecting back-scattered light which provides comparable results.
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Dates et versions

hal-01374265 , version 1 (04-10-2016)

Identifiants

Citer

Valentin Genuer, Olivier Gal, Jérémy Méteau, Pierre Marcoux, Emmanuelle Schultz, et al.. Optical elastic scattering for early label-free identification of clinical pathogens. SPIE BiOS - Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems, Feb 2016, san francisco, United States. pp.96980 - 96981, ⟨10.1117/12.2211021⟩. ⟨hal-01374265⟩
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