Automated three-dimensional radiomic body composition analysis enhances survival prediction in resectable non‑small cell lung cancer.
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| Title: | Automated three-dimensional radiomic body composition analysis enhances survival prediction in resectable non‑small cell lung cancer. |
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| Authors: | Huang Y; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China.; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China., Li C; School of Biomedical Engineering, Southern Medical University, Guangzhou, China.; Guangdong Provincial Key Laboratory of Medical Image Processing, Guangzhou, China., Yang F; The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China., Chen X; Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China., Chen X; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China., Huang Y; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China.; Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands., Zhang Z; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China., Yang L; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China., Jiang Y; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China., Cun H; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China., Mou Z; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China., Yang W; School of Biomedical Engineering, Southern Medical University, Guangzhou, China. weiyanggm@gmail.com.; Guangdong Provincial Key Laboratory of Medical Image Processing, Guangzhou, China. weiyanggm@gmail.com., Liu Z; Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China. liuzaiyi@gdph.org.cn.; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, China. liuzaiyi@gdph.org.cn., He B; Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, China. kmmu_hb@163.com. |
| Source: | European radiology experimental [Eur Radiol Exp] 2026 Sep 18; Vol. 10 (1). Date of Electronic Publication: 2026 Sep 18. |
| Publication Type: | Journal Article; Multicenter Study |
| Journal Info: | Publisher: SpringerOpen Country of Publication: England NLM ID: 101721752 Publication Model: Electronic Cited Medium: Internet ISSN: 2509-9280 (Electronic) Linking ISSN: 25099280 NLM ISO Abbreviation: Eur Radiol Exp Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2509-9280 |
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| DOI: | 10.1186/s41747-026-00802-2 |
