Open Access
1 September 2009 Fiber evanescent wave spectroscopy using the mid-infrared provides useful fingerprints for metabolic profiling in humans
Marie-Laure Anne, Caroline Le Lan, Valerie Monbet, Catherine Boussard-Plédel, Martine Ropert, Olivier Sire, Michel Pouchard, Christine Jard, Jacques Lucas, Jean-Luc Adam, Pierre Brissot M.D., Bruno Bureau, Olivier Loréal
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Abstract
Fiber evanescent wave spectroscopy (FEWS) explores the mid-infrared domain, providing information on functional chemical groups represented in the sample. Our goal is to evaluate whether spectral fingerprints obtained by FEWS might orientate clinical diagnosis. Serum samples from normal volunteers and from four groups of patients with metabolic abnormalities are analyzed by FEWS. These groups consist of iron overloaded genetic hemochromatosis (GH), iron depleted GH, cirrhosis, and dysmetabolic hepatosiderosis (DYSH). A partial least squares (PLS) logistic method is used in a training group to create a classification algorithm, thereafter applied to a test group. Patients with cirrhosis or DYSH, two groups exhibiting important metabolic disturbances, are clearly discriminated from control groups with AUROC values of 0.94±0.05 and 0.90±0.06, and sensibility/specificity of 86/84% and 87/87%, respectively. When pooling all groups, the PLS method contributes to discriminate controls, cirrhotic, and dysmetabolic patients. Our data demonstrate that metabolic profiling using infrared FEWS is a possible way to investigate metabolic alterations in patients.
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Marie-Laure Anne, Caroline Le Lan, Valerie Monbet, Catherine Boussard-Plédel, Martine Ropert, Olivier Sire, Michel Pouchard, Christine Jard, Jacques Lucas, Jean-Luc Adam, Pierre Brissot M.D., Bruno Bureau, and Olivier Loréal "Fiber evanescent wave spectroscopy using the mid-infrared provides useful fingerprints for metabolic profiling in humans," Journal of Biomedical Optics 14(5), 054033 (1 September 2009). https://doi.org/10.1117/1.3253319
Published: 1 September 2009
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CITATIONS
Cited by 47 scholarly publications and 4 patents.
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KEYWORDS
Iron

Spectroscopy

Mid-IR

Statistical analysis

Proteins

Profiling

Infrared spectroscopy

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