Experimental Evaluation of a Gas Sensors Array for the Identification of Complex VOCs Mixtures in the Breath of Patients by Pattern Recognition Techniques

Lung cancer is one of the deadliest form of cancer in Europe, being the first and second cause of cancer death respectively for men and women (Ferlay et al., 2018).
This high death toll has to be blamed on the lack of obvious symptoms in the early stages of the illness, during which surgery has to be performed in order to give high chances of recovery to the patient (The National Lung Screening Trial Research Team, 2011). Current diagnostic methods tend to be expensive, cumbersome, slow and requiring rare, qualified personnel. This often means that screening is costly and difficult to organise at a large scale. Asymptomatic subjects and people in remote areas are rarely tested overall, leading to late discovery of the cancer and poor survival chances (Silvestri et al., 2016; Westeel et al., 2007).
There is therefore a need for a diagnostic method that could be used remotely while being simple enough to be used with little prior formation. Ideally, that method would also be cheap enough to be widely deployed, and non-invasive for simplicity.
An interesting technology would be gas sensor arrays. Already widely used in a variety of sectors (food industry, odour characterization, environmental monitoring), they have gained interest as an experimental medical diagnostic method.
This thesis is part of the PATHACOV (Pathacov project, 2020) research project, funded by Interreg France-Wallonie-Vlaanderen. This project aims a gas sensor array to serve as a screening apparatus to detect early stage lung cancer.