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Breath Test Proposed to Diagnose Multiple Sclerosis

By LabMedica International staff writers
Posted on 09 Nov 2011
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Sensors have been developed to detect volatile organic compounds from exhaled breath to diagnose multiple sclerosis (MS).

The test is described as a landmark in the long search for a fast, inexpensive, and noninvasive test for MS, which is the most common neurological disease in young adults.

Scientists at the Technion − Israel Institute of Technology (Haifa, Israel) developed a new sensor array that can diagnose MS by analyzing the determined chemical compounds that appear in the breath of MS patients. The developed sensors were used to perform a proof-of-concept clinical study on 34 MS patients and 17 healthy volunteers and found that the developed sensors are just as accurate as a spinal tap but without the pain or the risk of side effects.

A cross-reactive array of polycyclic aromatic hydrocarbons and single wall-carbon nanotube bilayers was designed for the detection of volatile organic compounds, for instance hexanal and 5-methyl-undecane, that identify the presence of disease in the exhaled breath of patients with MS. The results obtained from a clinical study consisting of 51 volunteers showed that the sensors could discriminate between multiple sclerosis and healthy states from exhaled breath samples with 85.3% sensitivity, 70.6% specificity, and 80.4% accuracy.

The scientists concluded that their results open new frontiers in the development of fast, noninvasive and inexpensive medical diagnostic tools for detection of chronic neurological diseases. The results could serve as a launching pad for the discrimination between different subphases of stages of multiple sclerosis as well as for the identification of multiple sclerosis patients who would respond well to immunotherapy. A large clinical study with the reported sensors is underway and will be reported in the future. The study was published online on September 22, 2011, in the journal Chemical Neuroscience.

Related Links:

Technion - Israel Institute of Technology


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