Lung cancer is the top cause of cancer deaths in the U.S., affecting more lives than breast, prostate, and colon cancers combined. At UI Health, a dedicated team is using artificial intelligence (AI) and molecular science to catch it early and understand who is most at risk.
Dr. Frank Weinberg, who leads the Thoracic Oncology Program at UI Health, emphasizes, “Early detection can make all the difference.” The aim is not just to screen but to predict and prevent advanced lung cancer from ever developing.
The Lung Cancer Program at UI Health consists of experts from various fields, all working together. They include Dr. Kevin Kovitz, who leads interventional pulmonology, and nurse practitioner Mary Pasquinelli, the director of the Lung Cancer Screening Program. This teamwork creates a well-rounded approach that connects clinics, labs, and communities.
“Forty years ago, we could do very little for lung cancer,” Kovitz notes. “Now, we have advanced, minimally invasive technologies for diagnosis and staging. If we catch lung cancer early, we can save lives.”
Recently, UI Health secured two significant research grants aimed at improving early detection and identifying those at highest risk for lung cancer. The first, for $3 million from AstraZeneca, involves collaboration with institutions like Massachusetts General Hospital and Baptist Memorial Health Care. This partnership utilizes an AI model called Sybil, which can predict a person’s lung cancer risk based on a low-dose CT scan.
Previous studies showed Sybil worked primarily in white populations. However, UI Health has recently shown that it also performs well across diverse racial and socioeconomic groups at higher risk of lung cancer. Dr. Pasquinelli presented these findings at a major conference in Barcelona. The upcoming “Resolve Study” will test whether Sybil can help interpret incidental findings in scans—tiny nodules that can indicate a risk of cancer.
“By collaborating across institutions, we prove that these tools can help everyone, not just a select few,” Pasquinelli says. “We want to ensure that innovation in lung cancer screening reaches high-risk populations.”
The second grant for $1 million from Lilly will help develop a precision lung cancer screening program that combines AI with population health and molecular science. This program is designed to increase access to lung cancer screening, particularly for people who don’t fit existing criteria but may still be at risk. For instance, it considers anyone with a long history of tobacco use, even if they stopped smoking years ago.
Pasquinelli stresses, “If you have lungs, you’re at risk. Half of those diagnosed with lung cancer wouldn’t meet current screening guidelines. We aim to change that.”
Moreover, the plan aims to incorporate Sybil’s predictions into routine practice. If it suggests someone is likely to develop lung cancer, proactive measures could be taken to prevent it.
Lastly, the initiative aims to link molecular blood-based biomarkers that indicate inflammation and metabolic changes with cancer risk. Identifying these biomarkers could allow early intervention, potentially before tumors appear on scans.
Dr. Weinberg explains, “Connecting CT scan results with molecular data enables us to identify those most at risk sooner.” This work illustrates the importance of collaboration—uniting scientists, clinicians, and communities in the fight against lung cancer.
For more detailed insights on early lung cancer detection, you can refer to the National Cancer Institute.
