Differentiation of pathological subtypes and Ki-67 and TTF-1 expression by dual-energy CT (DECT) volumetric quantitative analysis in non-small cell lung cancer
The combined predictive model based on volumetric quantitative analysis in DECT offers valuable information to discriminate immunohistochemical expression status, facilitating clinical decision-making for patients with NSCLC.
Authors
- Mingwang Chen (ORCID: https://orcid.org/0009-0009-4043-5379)
- Jianbin Huang
- Chenggong Yan (ORCID: https://orcid.org/0000-0002-2968-4595)
- Lisheng Huang
- Xiaomei Li (ORCID: https://orcid.org/0000-0002-3221-5888)
- Yuting Wu (ORCID: https://orcid.org/0000-0001-6278-5366)
- Chen Zhao (ORCID: https://orcid.org/0000-0002-6200-8142)
- Li Ding (ORCID: https://orcid.org/0009-0000-1504-3212)
- Jingxu Li (ORCID: https://orcid.org/0009-0006-1707-4091)
- Xiang Qin
- Yikai Xu
Institutions
- First Affiliated Hospital of Guangzhou Medical University (CN)
- Nanfang Hospital (CN)
- Southern Medical University (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1186/s40644-024-00793-6
- Citations
- 7
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.29
Funders
- National Natural Science Foundation of China