Leveraging Artificial Intelligence and Radiomics for Improved Nasopharyngeal Carcinoma Prognostication
Radiomics holds promise for improving NPC risk stratification, potentially allowing for personalised treatment strategies. The most important radiomics feature, maximum 2D diameter, suggests a need to reconsider tumour size as a prognostic criterion despite its current exclusion from TNM staging. Larger prospective studies are needed to validate these findings.
Authors
- Nicholas B. Shannon (ORCID: https://orcid.org/0000-0001-8742-8285)
- Melvin L.K. Chua (ORCID: https://orcid.org/0000-0002-1648-1473)
- Narayanan Gopalakrishna lyer
Institutions
- Singapore General Hospital (SG)
- SingHealth Duke-NUS Academic Medical Centre (SG)
- National Cancer Centre Singapore (SG)
- Imperial College London (GB)
Publication Details
- Journal
- Cancer Medicine
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1002/cam4.70706
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 5.44