Journal: Journal of thoracic imaging
This publication reviews the integration of artificial intelligence (AI) with low-dose computed tomography (LDCT) in lung cancer screening, highlighting its evolution over more than 30 years through the International Early Lung Cancer Action Program (I-ELCAP).
It outlines key advances in AI, including:
- Lung nodule detection
- Emphysema quantification
- Cardiovascular risk assessment
The review emphasizes the development of the open-source IELCAP-AIRS system and the ScreeningPLUS infrastructure for AI training and deployment.
The paper also addresses challenges such as imaging variability and clinical integration, while underscoring AI’s potential to:
- Reduce radiologist workload
- Enable precise disease quantification
- Broaden screening to multiple diseases from a single LDCT scan
Finally, the authors stress the importance of collaboration, standardized protocols, and large datasets to advance AI-driven, preventive care.