SPAIN – Based on the concept of artificial nose with the patient’s breath and a series of sensors that analyze it with mathematical algorithms, an international team of scientists with participation of the Complutense University of Madrid (UCM) has designed a tool to diagnose lung cancer.

“This method is used to identify and quantify volatile biomarkers and recognize high – risk groups for lung cancer,” says Joseph S. Torrecilla, professor at the Department of Chemical Engineering of the UCM and principal investigator of the Spanish group.

As revealed by an article published in Advanced Materials, technology which is being validated in several centers hospitals, detects the tumor to record chemical composition of breath. This is directly related to the chemistry of blood or metabolic activity that is altered due to the presence of cancer.

“One advantage is that the doctor can receive patient assessment few seconds after entering his breath on the team,” said John C. Cancilla, team researcher and co-author UCM.

Scientists at the Madrid University have applied intelligent mathematical algorithms that address signals from the sensors of the tool.  This can also be used to monitor the effectiveness of treatment in patients diagnosed with the disease.

Early noninvasive

The method has been developed within the framework of the European project LCAOS funded by the Seventh Framework Programme.  “It aims to reduce mortality from this tumor through early detection and non-invasive, with periodic analysis of the patient at reduced costs through something basic like breath” says Gemma Matute, a member of the group of the UCM that participates in the project.

Lung cancer accounts for 28% of deaths in the world. In Europe, they appear each year 384.0000 new cases and 342,000 people are killed as a result of the disease.

LCAOS part of the consortium, with the participation of the UCM and coordinated by Hossam Haick, the Israel Institute of Technology, is developing similar tools for early diagnosis of other cancers, gastric.