AI-driven body composition atlas reveals its association with NSCLC immunotherapy outcome and molecular background: a multicenter study.
Authors
Affiliations (16)
Affiliations (16)
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Hubei Provincial Clinical Research Center for Precision Radiology & Interventional Medicine, Wuhan, China.
- Hubei Key Laboratory of Molecular Imaging, Wuhan, China.
- Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
- Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, China.
- Department of Radiology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China.
- Department of Radiotherapy, 900th Hospital of Joint Logistics Support Force, Fuzhou, China.
- Department of Radiology, the Key Laboratory of Advanced Interdisciplinary Studies Center, National Center for Respiratory Medicine, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
- Department of Thoracic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. [email protected].
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. [email protected].
- Hubei Provincial Clinical Research Center for Precision Radiology & Interventional Medicine, Wuhan, China. [email protected].
- Hubei Key Laboratory of Molecular Imaging, Wuhan, China. [email protected].
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. [email protected].
- Hubei Provincial Clinical Research Center for Precision Radiology & Interventional Medicine, Wuhan, China. [email protected].
- Hubei Key Laboratory of Molecular Imaging, Wuhan, China. [email protected].
Abstract
Although previous studies have linked body composition to immunotherapy efficacy, comprehensive multidimensional analyses with biological explanations remain lacking. This study integrated eight independent cohorts comprising 2,132 non-small cell lung cancer (NSCLC) patients, including five immune checkpoint inhibitor prognostic cohorts (nā=ā1,919), two bulk RNA-seq cohorts (nā=ā190), and one prospective single-cell RNA-seq cohort (nā=ā23). Using deep learning algorithms, we automatically extracted 92 body composition parameters from computed tomography images. The AI-based segmentation system demonstrated high consistency with manual measurements (intraclass correlation coefficient >0.87) with significantly improved efficiency. In male patients, higher intermuscular fat volume (IMFV) and 14 other indicators were independent predictors of overall survival; in female patients, T12 subcutaneous fat density and 6 other indicators showed potential associations with survival. Male patients with high IMFV exhibited significant upregulation of interferon-related pathways in CD8ā+āT cells and NK cells, along with lower exhaustion scores, while female patients with high T12 subcutaneous fat density showed macrophage polarization toward the M1 phenotype. This study underscores the importance of multidimensional body composition in NSCLC patient management, demonstrating that specific parameters are not only closely related to survival outcomes but also exhibit unique gender differences and location variations, providing new insights for optimizing immunotherapy strategies.