Low-dose CT lung cancer screening appears set to be the next major population-based cancer screening exam. But much work remains to make LDCT screening available to as many eligible people as possible while optimizing scanning protocols.
That’s according to sessions at IASLC’s World Conference on Lung Cancer (WCLC 2026), which just wrapped up in Seoul, South Korea.
- WCLC 2026 sessions ranged from expanding scanning to people at high risk but without smoking histories to using AI to not only detect and characterize lung nodules but to predict future cancer risk.
Some of the key findings from WCLC 2026 included…
- Australia started its national LDCT screening program in 2025, and researchers expect a national-level stage shift to earlier diagnosis. At a 50% participation rate, stage I diagnoses should grow from 32% currently to 42% for women and 43% for men.
- The Ready to Screen (R2S) trial in Australia found that of 1.7k eligible screening candidates surveyed, 85% “definitely” intended to get screened and 26% said they had already received an LDCT scan.
- Taiwan’s national screening program showed that – at least in East Asia – people with a family history of lung cancer should be screened. Of 2.8k cancers detected, there was a 74% higher detection rate in those with family histories versus smoking histories (18 vs. 10 cancers per 1k screened), with more early-stage cancers detected (92% vs. 83%).
- An LDCT screening program in China screened 6.7k people – including those with risk factors besides smoking – finding a 56% lung cancer mortality reduction.
- French clinicians successfully added smoking cessation therapy to their LDCT program, with 88% screening attendance and participants 44% less likely to smoke.
- MIT’s Sybil AI algorithm was more accurate than Lung-RADS in predicting one-year cancer risk from suspicious nodules, with higher AUC when applied to two large lung screening trials (NLST and P-IELCAP).
- Researchers found that applying Sybil to coronary artery calcium scans could also predict lung cancer risk for both smokers and non-smokers over a 15-year follow-up period.
- Researchers used Softek Illuminate’s Illuminate AI software for identifying incidental pulmonary nodules as a complement to an LDCT screening program, finding that the algorithm discovered more lung cancer cases than conventional screening.
The Takeaway
This week’s WCLC 2026 sessions point out the rapid progress being made around the world in expanding access to LDCT lung cancer screening – as well as the role that AI-based software tools can play in making screening more effective and more widely accessible.
