eNose analysis of exhaled breath for diagnosing and phenotyping respiratory diseases

In respiratory disease, the lungs and/or other parts of the respiratory system are affected, thereby negatively impacting human breathing. The magnitude of the global burden of respiratory disease is staggering: every year hundreds of millions of people suffer and four million people die prematurely from respiratory diseases. A delayed diagnosis of respiratory disease will inevitably lead to delayed treatment and other mitigations such as smoking-cessation intervention. Therefore, an early and accurate diagnosis of respiratory disease offers a window of opportunity to make a real difference to the lives of many patients. This thesis will discuss the diagnosis and phenotyping of asthma, COPD and lung cancer using an emerging technology: eNose analysis of exhaled breath. Exhaled breath contains a matrix of biomarkers, many of which provide relevant information about a person’s health status. This almost unlimited resource can be easily collected without burden to the test person, making it highly appealing as diagnostic tool. The detection and recognition of odors using an eNose appears similar to the functioning of the mammalian olfactory system and results in a pattern of firing sensors (breathprint) powered by mixtures of volatile organic compounds (VOCs) in exhaled breath. As a result, an eNose can differentiate between diseases by analysis and comparing the detected breath profiles with those previously recognized and stored in an online database.