Jonathan R. Weir-McCall, Elise Debruyn, Scott Harris, Nagmi R. Qureshi, Robert C. Rintoul, Fergus V. Gleeson, Fiona J. Gilbert, Anindo Banerjee Lucy Brindle, Matthew Callister, Andrew Clegg, Andrew Cook, Kelly Cozens, Philip Crosbie, Sabina Dizdarevic, Rosemary Eaton, Kathrin Eichhorst, Anthony Frew, Ashley Groves, Sai Han, Jeremy Jones, Osie Kankam, Kavitasagary Karunasaagarar, Lutfi Kurban, Louisa Little, Jackie Madden, Chris McClement, Ken Miles, Patricia Moate, Charles Peebles, Lucy Pike, Fat-Wui Poon, Donald Sinclair, Andrew Shah, Luke Vale, Steve George, Richard Riley, Andrea Lodge, John Buscombe, Theresa Green, Amanda Stone, Neal Navani, Robert Shortman, Gabriella Azzopardi, Sarah Doffman, Janice Bush, Jane Lyttle, Kenneth Jacob, Joris van der Horst, Joseph Sarvesvaran, Barbara McLaren, Lesley Gomersall, Ravi Sharma, Kathleen Collie, Steve O’Hickey, Jayne Tyler, Sue King, John O’Brien, Rajiv Srivastava, Hugh Lloyd-Jones, Sandra Beech, Andrew Scarsbrook, Victoria Ashford-Turner, Elaine Smith, Susan Mbale, Nick Adams, and Gail Pottinger
Solitary pulmonary nodules (SPNs) measuring 8 to 30 mm in diameter require further workup to determine the likelihood of malignancy.What is the diagnostic performance of a lung cancer prediction convolutional neural network (LCP-CNN) in SPNs using unenhanced and contrast-enhanced CT imaging compared with the current clinical workup?This was a post hoc analysis of the Single Pulmonary Nodule Investigation: Accuracy and Cost-Effectiveness of Dynamic Contrast Enhanced Computed Tomography in the Characterisation of Solitary Pulmonary Nodules trial, a prospective multicenter study comparing the diagnostic accuracy of dynamic contrast-enhanced (DCE) CT imaging with PET imaging in SPNs. The LCP-CNN was designed and validated in an external cohort. LCP-CNN-generated risk scores were created from the noncontrast and contrast-enhanced CT scan images from the DCE CT imaging. The gold standard was histologic analysis or 2 years of follow-up. The area under the receiver operating characteristic curves (AUC) were calculated using LCP-CNN score, maximum standardized uptake value, and DCE CT scan maximum enhancement and were compared using the DeLong test.Two hundred seventy participants (mean ± SD age, 68.3 ± 8.8 years; 49% women) underwent PET with CT scan imaging and DCE CT imaging with CT scan data available centrally for LCP-CNN analysis. The accuracy of the LCP-CNN on the noncontrast images (AUC, 0.83; 95% CI, 0.79-0.88) was superior to that of DCE CT imaging (AUC, 0.76; 95% CI, 0.69-0.82; P = .03) and equal to that of PET with CT scan imaging (AUC, 0.86; 95% CI, 0.81-0.90; P = .35). The presence of contrast resulted in a small reduction in diagnostic accuracy, with the AUC falling from 0.83 (95% CI, 0.79-0.88) on the noncontrast images to 0.80 to 0.83 after contrast (P .05 for 240 s after contrast only).An LCP-CNN algorithm provides an AUC equivalent to PET with CT scan imaging in the diagnosis of solitary pulmonary nodules.ClinicalTrials.gov Identifier; No.: NCT02013063.