MRI-based interpretable clinicoradiological and radiomics machine learning model for preoperative prediction of pituitary macroadenomas consistency: a dual-center study.

Journal: Neuroradiology
Published Date: Jul 9, 2025

Abstract

PURPOSE: To establish an interpretable and non-invasive machine learning (ML) model using clinicoradiological predictors and magnetic resonance imaging (MRI) radiomics features to predict the consistency of pituitary macroadenomas (PMAs) preoperatively.

Authors

  • Meiheng Liang
    Department of Radiology, Xinqiao Hospital, Army Medical University, Chongqing, China.
  • Fei Wang
    Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States.
  • Yan Yang
    Department of Endocrinology and Metabolism, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
  • Li Wen
  • Shunan Wang
    Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China.
  • Dong Zhang
    Institute of Acoustics, Nanjing University, Nanjing 210093, China.

Keywords

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