Mehdi Alilou, Ph.D.

Immune-checkpoint inhibitors have shown promising clinical efficacy for the treatment of advanced non-small cell lung cancer (NSCLC). The costs of immunotherapy can be prohibitive and the response rates to these drugs remain modest (about 20%). There is also a lack of objective methods for the early evaluation of clinical benefit from immunotherapy. We have pioneered computer-extracted features relating to NSCLC nodules on CT scans—specifically a new imaging biomarker called Quantitative Vessel Tortuosity (QVT)—which is associated with the degree to which a NSCLC tumor is resistant to immunotherapy. We will further optimize these features from pre- and post-treatment CT scans, build response prediction models based on QVT changes, and validate QVT for monitoring immunotherapy response on routine CT scans. We anticipate that at least 40% of the lung cancer population (stage III and IV NSCLC patients) would benefit from our research.