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Congress: ECR25
Poster Number: C-27307
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-27307
Authorblock: R. Vliegenthart1, G. Sidorenkov1, M. Prokop2, H. Groen1, P. De Jong3, C. Jacobs1, F. A. A. Mohamed Hoesein3, R. Stadhouders4, G. De Bock1; 1Groningen/NL, 2Nijmegen/NL, 3Utrecht/NL, 4Rotterdam/NL
Disclosures:
Rozemarijn Vliegenthart: Grant Recipient: Institutional research grants, Siemens Healthineers Speaker: Siemens Healthineers, Bayer Healthcare
Grigory Sidorenkov: Nothing to disclose
Mathias Prokop: Other: royalties to institution from MeVis medical solutions Speaker: Siemens Healthineers, Bayer, Bracco, Canon Medical Systems
Harry Groen: Nothing to disclose
Pim De Jong: Research/Grant Support: Institutional support, Philips healthcare
Colin Jacobs: Speaker: Canon medical systems, Johnson&Johnson Research/Grant Support: MeVis medical solutions, Philips medical systems Other: Royalties to institution from MeVis medical solutions
Firdaus A. A. Mohamed Hoesein: Nothing to disclose
Ralph Stadhouders: Nothing to disclose
Geertruida De Bock: Nothing to disclose
Keywords: Artificial Intelligence, Lung, CT, Outcomes analysis, Screening, Arteriosclerosis, Cancer, Chronic obstructive airways disease
Purpose Trials, including the Dutch-Belgian lung cancer screening trial (NELSON), have demonstrated that low-dose CT screening reduces lung cancer mortality among long-term (former) smokers. However, a significant proportion of individuals will not derive benefit from screening. Some may have a low risk of developing lung cancer despite their smoking history and age, while others may have limited life expectancy, precluding any survival advantage. Therefore, optimizing the selection of individuals who are most likely to benefit remains a critical challenge. Additionally, many...
Read more Methods and materials   The NELSON study is a population-based, randomized controlled lung cancer screening trial conducted in the Netherlands and Belgium. It includes a follow-up period of 10 years after the first screening round. The study enrolled 15,792 individuals aged 50–75 years with a smoking history of more than 15 cigarettes per day for over 25 years or more than 10 cigarettes per day for at least 30 years. Former smokers were eligible if they had quit smoking within the past 10 years....
Read more Results This project aims to achieve the following objectives: Develop and refine polygenic risk scores for lung cancer prediction. Assess environmental risk scores based on air pollution exposure for lung cancer prediction. Estimate malignancy probability of lung nodules using an AI-derived risk score. Quantify chest CT biomarkers in NELSON screening rounds, including emphysema, coronary calcifications, bone density, vertebral height, and body composition. Develop and validate multisource data-driven prediction models to identify individuals at the highest risk of lung cancer. Design and validate multisource data prediction models for...
Read more Conclusion The results of NELSON-POP will contribute to an accessible, sustainable, and affordable healthcare system when lung cancer screening is implemented. 
Read more References Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. de Koning HJ, van der Aalst CM, de Jong PA, et al. N Engl J Med. 2020;382:503-513. doi: 10.1056/NEJMoa1911793. PMID: 31995683 Lung Nodule Management in Low-Dose CT Screening for Lung Cancer: Lessons from the NELSON Trial. Zhong D, Sidorenkov G, Jacobs C, et al. Radiology. 2024;313:e240535. doi: 10.1148/radiol.240535.PMID: 39436294Multi-source data approach for personalized outcome prediction in lung cancer screening: update from the NELSON trial. Sidorenkov G, Stadhouders R, Jacobs C, et al....
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