We are involved in early studies of CT lung cancer screening as well as incorporation of artificial intelligence tools for lung nodule detection, follow-up and management.
Lung cancer is one of the most fatal cancers, with a poor outcome mostly due to late detection. The early identification of lung nodules is vital to ensure early stage (and treatable/curable) lung cancer is diagnosed. Edinburgh Imaging is playing a central role in this, working together with clinical colleagues at NHS Lothian and academic colleagues at the Usher Institute.
There are several strands to this research:
- Development of novel nodule detection and characterization software, which serves as a back-up for radiologists and has been shown to improve detection of these early lung nodules. Software has been rolled out across NHS Lothian for detection of lung nodules on routine chest CT. A HDRUK funded project, INPACT, will further explore the impact of this software on patient management
- Development of a standardized reporting template with patient management according to established guidelines, once lung nodules are detected. A European project (PINPOINT), funded by Astra Zeneca and Aidence, will evaluate the automation of lung nodule detection and lung nodule management.
- Support of CT based lung cancer screening, which is focused on particular groups of people who are at increased risk for developing lung cancer. This first Scottish pilot particularly aims to develop ways of including those who are hard to reach, who tend to be in underprivileged areas around Edinburgh and beyond (the LUNGSCOT study).
Lead lung cancer researcher
To discuss new research & collaborative imaging projects with Edinburgh Imaging, please contact:
Enquiries: studies / collaborations / facilities
- Email: firstname.lastname@example.org
Research staff with a lung cancer focus
- David Senyszak
- Prof David Weller
- Dr Miguel Bernabeu Llinares
- Dr John Murchison
- Dr Rishi Ramaesh
- Dr Melanie MacKean
Funding organisations and groups
Organisations are listed alphabetically:
Relevant Edinburgh Imaging publications
- 20 May 22. Featured Paper. Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population
- 07 May 22. Featured Paper. Lung tissue shows divergent gene expression between chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis
Caulo, A., et al. Integrated imaging of non-small cell lung cancer recurrence: CT and PET-CT findings, possible pitfalls and risk of recurrence criteria. Eur Radiol 22, 588–606 (2012). https://doi.org/10.1007/s00330-011-2299-8
Mirsadraee S., et al. The 7th lung cancer TNM classification and staging system: Review of the changes and implications. World J Radiol. 2012 Apr 28;4(4):128-34. doi: 10.4329/wjr.v4.i4.128. PMID: 22590666; PMCID: PMC3351680.
Wild, J.M., et al. MRI of the lung (1/3): methods. Insights Imaging 3, 345–353 (2012). https://doi.org/10.1007/s13244-012-0176-x
Biederer, J., et al. MRI of the lung (2/3). Why … when … how?. Insights Imaging 3, 355–371 (2012). https://doi.org/10.1007/s13244-011-0146-8
Biederer, J., et al. MRI of the lung (3/3)—current applications and future perspectives. Insights Imaging 3, 373–386 (2012). https://doi.org/10.1007/s13244-011-0142-z
Walker AE., et al. Chest radiographs and the elusive lung cancer. Digit Med 2016;2:120-6
Lee G., et al. Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art. European Journal of Radiology. 2016 Sep 10. https://doi.org/10.1016/j.ejrad.2016.09.005
Biederer J., J et al. Screening for lung cancer: Does MRI have a role? European Journal of Radiology. 2016 Sep 16. https://doi.org/10.1016/j.ejrad.2016.09.016
for the COPDGene Investigators, van Beek E. Lung Mass in Smokers. Academic Radiology. 2017 Aug 30;24(4):386-392. https://doi.org/10.1016/j.acra.2016.10.011
International Workshop for Pulmonary Functional Imaging (IWPFI), Ohno Y, Kauczor H-U, Hatabu H, Seo JB, van Beek EJR. MRI for solitary pulmonary nodule and mass assessment: Current state of the art. Journal of Magnetic Resonance Imaging. 2018 Mar 23. https://doi.org/10.1002/jmri.26009