Peritumoral and intratumoral radiomics for predicting visceral pleural invasion in lung adenocarcinoma based on preoperative computed tomography (CT)
Preoperative CT-based radiomics models can predict VPI in patients with LAC; the LR algorithm combined the GPTV radiomics was the optimal choice, demonstrating high sensitivity, specificity, accuracy and clinical usefulness.
Authors
- Zhimin Geng (ORCID: https://orcid.org/0000-0003-2645-9808)
- Xuan Yang (ORCID: https://orcid.org/0000-0002-1921-8929)
- Jiuwei Cui (ORCID: https://orcid.org/0000-0001-6496-7550)
- Po‐Hao Feng (ORCID: https://orcid.org/0000-0002-3569-3746)
- Y-Q Zuo
- Yixia Yin (ORCID: https://orcid.org/0000-0002-0326-1658)
- Dongmei Gao (ORCID: https://orcid.org/0000-0003-3442-5704)
- Zhao Gao (ORCID: https://orcid.org/0000-0003-4541-9019)
Institutions
- Hebei Medical University (CN)
- Third Hospital of Hebei Medical University (CN)
- United Imaging Healthcare (China) (CN)
Publication Details
- Journal
- Clinical Radiology
- Published
- 2024-10-19
- DOI
- https://doi.org/10.1016/j.crad.2024.10.010
- Citations
- 6
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.43