Imaging and Pathology Concordance in Head and Neck Cancer: Retrospective Analysis
Our study shows moderate imaging-pathology concordance. Key predictors like lymph node size suggest refining criteria with machine learning could enhance head and neck cancer diagnosis. These results could guide more accurate preoperative imaging assessments, leading to better surgical planning and patient outcomes. Subsequent exploration of adjusting lymph node size thresholds or integrating novel imaging technologies would be useful.
Authors
- Hongyu Yang (ORCID: https://orcid.org/0000-0002-0367-4938)
- Shiyue Shen
- Youdan Yao
- Shunji Wang
- Tianwen Zhang (ORCID: https://orcid.org/0000-0003-1309-9209)
- Xin Ye (ORCID: https://orcid.org/0000-0002-2798-8923)
- Bo Lin (ORCID: https://orcid.org/0000-0003-1608-4109)
- Yufan Wang (ORCID: https://orcid.org/0000-0001-9083-2465)
- Huijun Yang (ORCID: https://orcid.org/0000-0003-1121-7806)
- Xia Hong (ORCID: https://orcid.org/0000-0001-6282-8469)
- Feng Wang (ORCID: https://orcid.org/0000-0003-3036-6735)
Institutions
- Hong Kong University of Science and Technology (HK)
- Peking University Shenzhen Hospital (CN)
- University of Hong Kong - Shenzhen Hospital (CN)
Publication Details
- Journal
- Oral Diseases
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1111/odi.15268
- Citations
- 2
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 3.70
Funders
- Sanming Project of Medicine in Shenzhen