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Elastic Light Scattering (ELS) is an innovative technique to identify bacterial pathogens directly on culture plates. Compelling results have already been reported for agri-food applications. Here, we have developed ELS for clinical diagnosis, starting with Staphylococcus aureus early screening. Our goal is to bring a result (positive/negative) after only 6 h of growth to fight surgical-site infections. The method starts with the acquisition of the scattering pattern arising from the interaction between a laser beam and a single bacterial colony growing on a culture medium. Then, the resulting image, considered as the bacterial species signature, is analyzed using statistical learning techniques. We present a custom optical setup able to target bacterial colonies with various sizes (30-500 microns). This system was used to collect a reference dataset of 38 strains of S. aureus and other Staphyloccocus species (5459 images) on ChromIDSAID/ MRSA bi-plates. A validation set from 20 patients has then been acquired and clinically-validated according to chromogenic enzymatic tests. The best correct-identification rate between S. aureus and S. non-aureus (94.7%) has been obtained using a support vector machine classifier trained on a combination of Fourier-Bessel moments and Local- Binary-Patterns extracted features. This statistical model applied to the validation set provided a sensitivity and a specificity of 90.0% and 56.9%, or alternatively, a positive predictive value of 47% and a negative predictive value of 93%. From a clinical point of view, the results head in the right direction and pave the way toward the WHO’s requirements for rapid, low-cost, and automated diagnosis tools.
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