The rationale behind this project is that lung cancer screening and follow-up programs that are based on computerized tomography (CT) are emerging in many countries worldwide. However, the high false positive rate of this technique has been a major challenge in front those plans. This is because a significant part of this population undergo unnecessary invasive procedures that are both costly and associated with significant morbidity and mortality. To increase the specificity of the CT based screening and follow-up programs, an auxiliary noninvasive breath test was developed and used to distinguish between malignant and non-cancerous CT findings and to follow up the treatment process. A stand-alone prototype of a breath testing system was assembled from nanomaterial-based sensors and artificial intelligence developed during the ERC’s “DIAG-CANCER” Project of the Technion. After comprehensive quality checks, the device was used in a clinical setting to examine 143 breath samples collected from patients with lung cancer and control groups. The exhaled breath signature was correlated with the CT findings before and during the disease treatment. The nanomaterial-based stand-alone breath test exhibited an ability to detect and discriminate between lung cancer states (benign vs. malignant) and to monitor changes in malignant tumor response across therapy, indicating any lack of further response to therapy. Using one sensor analysis, 59% of the follow-up samples were identified correctly. There was 85% success in monitoring disease control stable disease and progressive disease. These findings provide the medical doctor with a quick bed-side method of identifying the existence of malignant vs. non-malignant tumor as well as a lack of response to an anti-cancer treatment. This may allow quicker recognition than the current analysis. Early recognition of treatment failure could improve patient care. As part of the economic implication of the project the IP portfolio of the stand-alone breath analyzer device was competed and a market research was conducted to identify the optimal placement in the healthcare market.
