The struggle against tuberculosis is one of the World Health Organization priorities. Identifying in a short time, patients with active tuberculosis, would bring a tremendous improvement to the current situation. Recovering from this infectious and deadly disease (2 million of death per year) is possible with a correct diagnosis to give an appropriate treatment. Unfortunately, most common tuberculosis diagnoses have few drawbacks: - skin tests: not reliable at 100% and need an incubation of 2 days before the diagnosis, - blood tests: costly and sophisticated technology, - chest X-ray: the first step before the sputum tests used for a bacterial culture with a final diagnosis given within 2 weeks. A tuberculosis test based on exhaled breath analysis is a prospective and noninvasive solution, cheap and easy to use and to transport. This test lies on a fluoregenic detection of niacin, a well-known mycobacterium tuberculosis specific metabolite. In this paper, it is assumed that the selected probe is specific to niacin and that exhaled breath does not contain any interfering species. To address this problem, a fluorimeter is developed with a cheap and cooled CCD ( 2k$) as a sensor, to easily determine the suitable “fluorescent zone”. In comparing aqueous solutions with and without niacin, 250 pM of niacin have been detected. With a commercial fluorimeter (Fluorolog from Horiba), only 200 nM of niacin are detected. The present detection remains 10 times above the estimated targeted value for a tuberculosis test. The excitation source is a LED, which typically emits 20 W at 265 nm through an optical fiber. The emission signal is detected around 545 nm. A typical light exposure lasts 700 seconds. Analysis of biomarkers with a liquid fluorimeter is generic and promising as health diagnosis.

Date Published: 5 March 2013
PDF: 11 pages
Proc. SPIE 8570, Frontiers in Biological Detection: From Nanosensors to Systems V, 85700N (5 March 2013); doi: 10.1117/12.2000553

Published in SPIE Proceedings Vol. 8570:
Frontiers in Biological Detection: From Nanosensors to Systems V
Benjamin L. Miller; Philippe M. Fauchet, Editor(s)