TY - JOUR T1 - External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules JF - Thorax JO - Thorax SP - 306 LP - 312 DO - 10.1136/thoraxjnl-2019-214104 VL - 75 IS - 4 AU - David R Baldwin AU - Jennifer Gustafson AU - Lyndsey Pickup AU - Carlos Arteta AU - Petr Novotny AU - Jerome Declerck AU - Timor Kadir AU - Catarina Figueiras AU - Albert Sterba AU - Alan Exell AU - Vaclav Potesil AU - Paul Holland AU - Hazel Spence AU - Alison Clubley AU - Emma O'Dowd AU - Matthew Clark AU - Victoria Ashford-Turner AU - Matthew EJ Callister AU - Fergus V Gleeson Y1 - 2020/04/01 UR - http://thorax.bmj.com/content/75/4/306.abstract N2 - 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. ER -