Professional background
Arjun is a Consultant Radiologist with a sub-specialty interest in cardiothoracic imaging at University College London Hospital and an Honorary Associate Professor at University College London. He is the author/co-author of several peer-reviewed scientific papers and book chapters on cardiothoracic imaging. Arjun is currently the joint Royal College of Radiologists/ British Society of Thoracic Imaging Travelling Professor.
Arjun completed his undergraduate medical training at the University of Edinburgh in 2001, and his Membership of the Royal College of Physicians in 2005. Following this he specialised in radiology, and was awarded the Fellowship of the Royal College of Radiologists in 2008, after which he pursued cardiothoracic imaging subspecialisation. Arjun was awarded the Thoracic Imaging Fellowship at the Royal Brompton Hospital between 2011 and 2013, and during this time completed his thesis on “Computed Tomography Reading Strategies in Lung Cancer Screening”, for which he was awarded an MD by the University of Edinburgh in 2014.
Arjun has been actively involved in several lung screening trials, beginning with the UK Lung Screening Pilot trial in 2011 and continuing through the SUMMIT Lung cancer screening study over the last 6 years. Arjun was the Joint Clinical Lead for the National Lung Cancer Screening programme between 2019-2025 and currently co-chairs the British Thoracic Society Pulmonary Nodule Guideline Development Group. He is currently a member of several committees, including the Lung Cancer Screening workshop and Diploma subsections of the European Society of Thoracic Imaging Training and Educational Committee.
Specialties
Research interests
Lung cancer screening, lung cancer, interstitial lung disease, COPD, Artificial intelligence applications, imaging biomarkers, cancer bioinformatics, cardiac computed tomography, novel imaging techniques
Languages spoken
Malay
Publications
Selected publications- for full list please see Scopus ID 36241963000
Bhamani A, Creamer A, Verghese P, et al. Low-dose CT for lung cancer screening in a high-risk population (SUMMIT): a prospective, longitudinal cohort study. Lancet Oncol. 2025;26(5):609-619. doi:10.1016/S1470-2045(25)00082-8
Creamer AW, Horst C, Prendecki R, et al. Performance of volume and diameter thresholds in malignancy prediction of solid nodules in lung cancer screening. Thorax. 2025;80(9):624-631. Published 2025 Aug 15. doi:10.1136/thorax-2024-222086
Nair A, Dyer DS, Heuvelmans MA, Mashar M, Silva M, Hammer MM. Contextualizing the Role of Volumetric Analysis in Pulmonary Nodule Assessment: AJR Expert Panel Narrative Review. AJR Am J Roentgenol. 2023;220(3):314-329. doi:10.2214/AJR.22.27830
Hall H, Ruparel M, Quaife SL, et al. The role of computer-assisted radiographer reporting in lung cancer screening programmes. Eur Radiol. 2022;32(10):6891-6899. doi:10.1007/s00330-022-08824-1
Nair A, Bartlett EC, Walsh SLF,et al. Variable radiological lung nodule evaluation leads to divergent management recommendations. Eur Respir J. 2018 Dec 20;52(6).
Nair A, Gartland N, Barton B, et al. The Impact of Trained Radiographers as Concurrent Readers on Performance and Reading Time of Experienced Radiologists in the UK Lung cancer screening (UKLS) trial. Eur Radiol. 2018 Jan;28(1):226-234.
Devaraj A, van Ginneken B, Nair A, Baldwin D. Use of Volumetry for Lung Nodule Management: Theory and Practice. Radiology. 2017 Sep;284(3):630-644. doi: 10.1148/radiol.2017151022. PMID: 28825886.
Moser JB, Mak SM, McNulty WH, Padley S, Nair A, Shah PL, Devaraj A. The influence of inspiratory effort and emphysema on pulmonary nodule volumetry reproducibility. Clin Radiol. 2017 Nov;72(11):925-929. doi: 10.1016/j.crad.2017.06.117. Epub 2017 Aug 4. PMID: 28784319.
Nair A, Gartland N, Barton B, Jones D, et al. Comparing the performance of trained radiographers against experienced radiologists in the UK lung cancer screening (UKLS) trial. Br J Radiol. 2016 Oct;89(1066):20160301
Nair A, Rodrigues JCL, Hare S, et al. A British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic. Clin Radiol. 2020 May;75(5):329-334.