BACKGROUND: Estimation of the risk of malignancy in pulmonary nodules detected by CT is central in clinical management. The use of artificial intelligence (AI) offers an opportunity to improve risk prediction. Here we compare the performance of an AI algorithm, the lung cancer prediction convolutional neural network (LCP-CNN), with that of the Brock University model, recommended in UK guidelines. METHODS: A dataset of incidentally detected pulmonary nodules measuring 5-15 mm was collected retrospectively from three UK hospitals for use in a validation study. Ground truth diagnosis for each nodule was based on histology (required for any cancer), resolution, stability or (for pulmonary lymph nodes only) expert opinion. There were 1397 nodules in 1187 patients, of which 234 nodules in 229 (19.3%) patients were cancer. Model discrimination and performance statistics at predefined score thresholds were compared between the Brock model and the LCP-CNN. RESULTS: The area under the curve for LCP-CNN was 89.6% (95% CI 87.6 to 91.5), compared with 86.8% (95% CI 84.3 to 89.1) for the Brock model (p≤0.005). Using the LCP-CNN, we found that 24.5% of nodules scored below the lowest cancer nodule score, compared with 10.9% using the Brock score. Using the predefined thresholds, we found that the LCP-CNN gave one false negative (0.4% of cancers), whereas the Brock model gave six (2.5%), while specificity statistics were similar between the two models. CONCLUSION: The LCP-CNN score has better discrimination and allows a larger proportion of benign nodules to be identified without missing cancers than the Brock model. This has the potential to substantially reduce the proportion of surveillance CT scans required and thus save significant resources.

• MeSH
• algoritmy MeSH
• časná detekce nádoru metody   MeSH
• databáze faktografické MeSH
• dospělí MeSH
• hodnocení rizik MeSH
• incidence MeSH
• invazivní růst nádoru patologie   MeSH
• kohortové studie MeSH
• lidé středního věku MeSH
• lidé MeSH
• mnohočetné plicní uzly epidemiologie   patologie   patofyziologie   MeSH
• nádorová transformace buněk patologie   MeSH
• nádory plic epidemiologie   patologie   patofyziologie   MeSH
• neuronové sítě (počítačové) * MeSH
• plocha pod křivkou MeSH
• prediktivní hodnota testů MeSH
• prognóza MeSH
• retrospektivní studie MeSH
• ROC křivka MeSH
• senioři MeSH
• staging nádorů MeSH
• umělá inteligence * MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• práce podpořená grantem MeSH
• validační studie MeSH