Machine learning-based MRI radiomics predict IL18 expression and overall survival of low-grade glioma patients.

Journal: NPJ precision oncology
Published Date: Jun 19, 2025

Abstract

Interleukin-18 has broad immune regulatory functions. Genomic data and enhanced Magnetic Resonance Imaging data related to LGG patients were downloaded from The Cancer Genome Atlas and Cancer Imaging Archive, and the constructed model was externally validated using hospital MRI enhanced images and clinical pathological features. Radiomic feature extraction was performed using "PyRadiomics", feature selection was conducted using Maximum Relevance Minimum Redundancy and Recursive Feature Elimination methods, and a model was built using the Gradient Boosting Machine algorithm to predict the expression status of IL18. The constructed radiomics model achieved areas under the receiver operating characteristic curve of 0.861, 0.788, and 0.762 in the TCIA training dataset (n = 98), TCIA validation dataset (n = 41), and external validation dataset (n = 50). Calibration curves and decision curve analysis demonstrated the calibration and high clinical utility of the model. The radiomics model based on enhanced MRI can effectively predict the expression status of IL18 and the prognosis of LGG.

Authors

  • Zhe Zhang
    Department of Urology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.
  • Yao Xiao
    School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin 300401, China; Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Engineering Center of Environmental Diagnosis and Contamination Remediation, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
  • Jun Liu
    Department of Radiology, Second Xiangya Hospital, Changsha, Hunan, China.
  • Feng Xiao
    Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
  • Jie Zeng
    Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, 530021, China.
  • Hong Zhu
    Co-Innovation Center for the Sustainable Forestry in Southern China; Cerasus Research Center; College of Biology and the Environment, Nanjing Forestry University, Nanjing, China.
  • Wei Tu
    Department of Rheumatology and Immunology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
  • Hua Guo
    Zhumadian Psychiatric Hospital, Zhumadian 463000, Henan, China.

Keywords

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