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British Thoracic Society Pulmonary Nodule Guideline Development Group; British Thoracic Society Standards of Care Committee. British Thoracic Society guidelines for the investigation and management of pulmonary nodules. Thorax 2015;70:ii1–ii54. 7.… Click to show full abstract

British Thoracic Society Pulmonary Nodule Guideline Development Group; British Thoracic Society Standards of Care Committee. British Thoracic Society guidelines for the investigation and management of pulmonary nodules. Thorax 2015;70:ii1–ii54. 7. Gould MK, Donington J, Lynch WR, Mazzone PJ, Midthun DE, Naidich DP, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 2013;143:e93S–e120S. 8. Massion PP, Antic S, Ather S, Arteta C, Brabec J, Chen H, et al. Assessing the accuracy of a deep learning method to risk stratify indeterminate pulmonary nodules. Am J Respir Crit Care Med 2020; 202:241–249. 9. Choi HK, Ghobrial M, Mazzone PJ. Models to estimate the probability of malignancy in patients with pulmonary nodules. Ann Am Thorac Soc 2018;15:1117–1126. 10. Uthoff J, Stephens MJ, Newell JD Jr, Hoffman EA, Larson J, Koehn N, et al. Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT. Med Phys 2019;46:3207–3216. 11. Xu Y, Lu L, E LN, Lian W, Yang H, Schwartz LH, et al. Application of radiomics in predicting the malignancy of pulmonary nodules in different sizes. AJR Am J Roentgenol 2019; 213:1213–1220. 12. Peikert T, Duan F, Rajagopalan S, Karwoski RA, Clay R, Robb RA, et al. Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial. PLoS One 2018;13: e0196910. 13. Peikert T, Duan F, Rajagopalan S, Karwoski RA, Balar DK, Antic S, et al. Independent validation of a novel high-resolution computed tomography-based radiomic classifier for indeterminate lung nodules. J Thorac Oncol 2019;14:221–222. 14. Ardila D, Kiraly AP, Bharadwaj S, Choi B, Reicher JJ, Peng L, et al. Endto-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med 2019;25: 954–961. 15. Baldwin DR, Gustafson J, Pickup L, Arteta C, Novotny P, Declerck J, et al. External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules. Thorax 2020;75:306–312. 16. Crosbie PA, Balata H, Evison M, Atack M, Bayliss-Brideaux V, Colligan D, et al. Second round results from the Manchester ‘Lung Health Check’ community-based targeted lung cancer screening pilot. Thorax 2019;74:700–704.

Keywords: pulmonary nodules; lung; lung cancer; british thoracic; thoracic society

Journal Title: American Journal of Respiratory and Critical Care Medicine
Year Published: 2020

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