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En opptrent hund kan oppdage lungekreft fra menneskelig pust

Canine-assisted profiling of lung cancer from human breath

In Norway, more than 3000 people get lung cancer each year. Approximately two thirds of them do not survive.

Up until today, only screenings with CT scans has proved effective in detecting lung cancer, but this method is both costly and time consuming for the people involved – and for the society. Due to the method, and the fact that symptoms of lung cancer often emerge at an advanced stage of the disease, the patients often get their diagnosis in a stage when cure is not likely. New methods to detect lung cancer in an early and curable stage are desirable.

Scientists from Haukeland University Hospital and dog trainers from Fjellanger Detection and Training Academy (FDTA) are now collaborating on a project using trained dogs to detect lung cancer at an early stage. Detecting the cancer at an early stage can reduce mortality substantially. FDTA has selected the Belgian Malinois, which is one of the most widely used dog breeds for protection and scent detection. The idea is to train the dogs to detect cancer from human breath samples.

Remote Scent Tracing (RST) technique is applied in this project. The human breath samples are collected in the clinic by health personnel, transported to FDTA‘s lab facilities, and presented to the dogs in a systematic manner, allowing for an optimal detection environment. The dogs are trained to recognize specific target odors, work systematically smelling each sample in turn, and perform a trained behavior at any sample that contains the target odor.

The objective for this project is to identify a new and novel screening aid for the detection of human lung cancer from human breath using dog detection methods. The result from this project could initiate a process that can be scaled up and supplement the CT-scan as a pre-screening service, and thus separate the individuals that need to be further investigated for lung cancer.

The project has received verification funding from the FORNY2020 program at the Norwegian Research Council. BTO is the owner of the project, and contributes with business development and coordination of the project.

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