An explainable imaging-clinical biomarker for non-small cell lung cancer prognostication based on normalised hotspot to centroid distance and [18F]FDG PET/CT radiomics
NHOC enhances NSCLC patient survival prediction, and when integrated with PET-CT radiomics and disease stage, offers a robust, non-invasive approach to disease prognostication.
Authors
- Patrizia Viola (ORCID: https://orcid.org/0000-0002-2869-3908)
- Andrea Rockall (ORCID: https://orcid.org/0000-0001-8270-5597)
- Sue Chua (ORCID: https://orcid.org/0000-0001-5369-8156)
- Susan J. Copley (ORCID: https://orcid.org/0000-0003-1856-9951)
- Gary Cook (ORCID: https://orcid.org/0000-0002-8732-8134)
- Mitchell Chen (ORCID: https://orcid.org/0000-0002-3779-5615)
- Tara Barwick (ORCID: https://orcid.org/0000-0002-9776-8766)
- David Landau (ORCID: https://orcid.org/0000-0003-1770-9086)
- Richard A. O’Connor (ORCID: https://orcid.org/0000-0001-7100-0233)
- Tina Stoycheva
- John Dickson (ORCID: https://orcid.org/0000-0002-1793-3822)
- Yidong Han
- Kristofer Linton‐Reid (ORCID: https://orcid.org/0000-0003-4723-7198)
- Eric O. Aboagye (ORCID: https://orcid.org/0000-0003-2276-6771)
- Mubarik Arshad (ORCID: https://orcid.org/0000-0002-7086-6112)
- Danielle Power
Institutions
- St Thomas' Hospital (GB)
- Royal Marsden NHS Foundation Trust (GB)
- Imperial College Healthcare NHS Trust (GB)
- Mount Vernon Hospital (GB)
- Hammersmith Hospital (GB)
- Charing Cross Hospital (GB)
- Royal Marsden Hospital (GB)
- Queen's Medical Centre (GB)
- University College London (GB)
- Imperial College London (GB)
Publication Details
- Journal
- European Journal of Nuclear Medicine and Molecular Imaging
- Published
- 2025-12-12
- DOI
- https://doi.org/10.1007/s00259-025-07659-4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Imperial College London
- Imperial College Healthcare NHS Trust