The project was extended in 9 months due to delays caused by the covid 19 pandemic. However, we still managed to perform all of the planned activities.
Briefly:
• The Sensors array was further optimized, and sensor redundancy was adopted from a research group of Prof Denatale in Rome who demonstrated a significant noise reduction and drift compensation. In the last year of the project, we initiated a collaborative work with them for the analysis of the Vogas results. It seems that the implementation of the "adaptive neural network method" (ANN) developed by the Denatale group, works well on the Vogas results.
• Device manufacturing - Due to the need to test the VOGAS device in clinical trials, including a large number of subjects in a limited time, it was decided to build six devices of the final format, instead of three which were originally planned. This decision was discovered to be of great importance due to the outbreak of covid-19 which delayed some of the activities, limiting the actual time to recruit GC patients. Thus, six devices were built, distributed and collected breath samples for WP4 and WP5 at the different clinical centers.
• VOC analysis – UOL, PUC, NCIU, ACCCC, and CJO-HUSI collected samples of gastric cancer tissue and stomach content form GC patients as well as from heathy volunteers. These were shipped to UIBK for Volatile Organic Compound (VOC) analysis by GC/MS. The analysis was done along with a tissue culture study comparing VOC emission from normal and gastric cancer cell lines. This study comprising most of the work of work package 1, led to the finding of several unique and novel VOC’s whose levels are altered in malignant tissue relative to normal ones. These findings are currently submitted to scientific publication.
• Clinical studies - All five clinical centers, obtained the necessary permits, agreed upon Standard Operating Procedures (SOPs) and the two main clinical studies were launched (WP4 and WP5). Two units were sent to Latvia, one to Brazil, one to Chile and one unit to Ukraine. Later, two of the units (from Chile and Ukraine) were fixed, re-calibrated and sent to Colombia. We have put the two Colombian units in parallel so we could compare their function on the same patients. Despite some technical problems we recruited all of the planned number of subjects for these studies.
• Obtainment of results – JLM has dedicated a very large storage space in the Vogas cloud. Each center uploaded the Vogas breath sample results to the cloud where it was stored for statistical analysis. Both Juha and Johannes inspect the results daily to make sure that both the GNP and the IR units are generating meaningful results. This proved to be very important since technical problems did accrue, and we needed to respond in a timely manner.
• Statistical analysis – Breath samples of healthy volunteers and gastric cancer patients were analyzed by VTT according to conventional statistical methods. The results show about 80% accuracy for single clinical site. This is an average accuracy figure coming from four units, after excluding technical problems. However, when we force the model to use the same parameters for all units, the accuracy level drops to about 74% of the combined generic model of all sites. In order to increase our analytical capability, we have initiated collaboration with the Denatale group in Rome. This group is the inventor and world leader in what is called "adaptive neural network method" (ANN). We have sheard a partial set of results with the Denatale group and their initial analysis shows about 88% accuracy for a single site. We will follow up with the complete set of results and tentatively add this to the final publication.
• Ethics – An external ethical board (EEB) was formed, and all informed consent forms were evaluated. Periodic ethical meetings were held, and the ethical summaries of these meetings were included into the periodic reports. Finally, a responsible research and innovation (RRI) study and a few filed exercises were performed.
