Two Research Projects Aim to Improve Early Lung Cancer Detection

The LUNGevity Foundation announced its support for two significant research projects aimed at improving the early detection of lung cancer and the diagnosis of indeterminate pulmonary nodules (IPNs). The initiatives each receive $1 million for a three-year research period, undertaken in partnership with the Rising Tide Foundation for Clinical Cancer Research.

Each year, over 1.5 million Americans receive CT scans showing IPNs. Current non-invasive methods often fall short in reliably distinguishing benign from malignant nodules, potentially leading to unnecessary procedures, delayed diagnoses, or prolonged uncertainty for patients.

The first project is led by Dr. Steven Dubinett at UCLA. His research aims to develop a diagnostic tool that integrates advanced CT image analysis with a blood-based test. The goal is to reliably predict whether an indeterminate lung nodule is cancerous. The study will be validated in a cohort of 500 patients.

Dr. Lecia Sequist from Massachusetts General Hospital and Harvard Medical School leads the second project, The RESOLVE Study. This initiative will evaluate Sybil, an AI model capable of assessing lung cancer risk directly from CT scans without human annotation. The study will enroll 340 adults with low-risk pulmonary nodules and test the AI's real-world performance.

If successful, these studies could reduce unnecessary biopsies and surgeries, expand access to early detection through non-invasive approaches, and accelerate the identification of high-risk patients.