Commercially available AI products for CT-based lung cancer screening: capabilities, clinical evidence, and alignment with international screening frameworks

Purpose: To evaluate certified capabilities of CE-marked AI products for lung nodule analysis in CT lung cancer screening, assess their alignment with international screening frameworks, and analyze their supporting peer-reviewed evidence. Methods: Six core clinical tasks (nodule detection, classification, measurement, growth assessment, malignancy risk estimation, structured management) were defined by analyzing four major screening frameworks: Lung CT Screening Reporting and Data System (Lung-RADS) version 2022, British Thoracic Society (BTS) guidelines, European Union Position Statement (EUPS) recommendations, and European Society of Thoracic Imaging (ESTI) nodule management recommendations. CE-marked AI products were identified through the Health AI Register. Vendors confirmed certified capabilities using a standardized questionnaire; public documentation supplemented non-responders. Scientific evidence was evaluated using a six-level efficacy framework and assessed for study characteristics. Results: In total, 16 products from 16 vendors were included, and 10 vendors completed the questionnaire. Regarding capabilities, 14 products detect and measure solid and subsolid nodules, 12 support growth assessment, while none support endobronchial or cystic lesion evaluation. For risk estimation, 9 products provide malignancy-risk outputs: 5 use the PanCan model and 4 provide proprietary AI-based scores. A total of 6 products had no peer-reviewed publications. Across 60 studies for remaining products: 7% were prospective, 45% vendor-independent, with external testing on multicenter (40%), multinational (7%), and screening cohort (40%) datasets. Overall, evidence was concentrated at lower efficacy levels: 70% assessed standalone diagnostic accuracy, 25% examined effects on diagnostic decision-making, and none reported patient or societal outcomes. Conclusion: CE-marked AI solutions fulfill core functions for nodule assessment but lack certified functionality for endobronchial and cystic lesions and are supported by limited prospective, higher-level clinical evidence. Limitations: Product functionality assessment relied on publicly available and vendor-reported data.