Multi-parametric MRI Habitat Radiomics Based on Interpretable Machine Learning for Preoperative Assessment of Microsatellite Instability in Rectal Cancer.

Journal: Academic radiology
Published Date: Feb 26, 2025

Abstract

RATIONALE AND OBJECTIVES: This study constructed an interpretable machine learning model based on multi-parameter MRI sub-region habitat radiomics and clinicopathological features, aiming to preoperatively evaluate the microsatellite instability (MSI) status of rectal cancer (RC) patients.

Authors

  • Yueyan Wang
    Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, 233000, China.
  • Bo Xie
    Department of Orthodontics, The Affiliated Stomatological Hospital of Southwest Medical University, Luzhou, China.
  • Kai Wang
    Department of Rheumatology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, China.
  • Wentao Zou
    Department of Radiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu 233000, China (Y.W., B.X., K.W., W.Z., Y.M.); Graduate School of Bengbu Medical University, Bengbu 233000, China (Y.W., B.X., K.W., W.Z.).
  • Aie Liu
    Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China (mainland).
  • Zhong Xue
    Shanghai United Imaging Intelligence Co Ltd., Shanghai, China.
  • Mengxiao Liu
    MR Research Collaboration Team, Diagnostic Imaging, Siemens Healthineers Ltd, Shanghai 200126, China (M.L.).
  • Yichuan Ma
    The First Affiliated Hospital of Bengbu Medical College, No. 287 Changhuai Road, Bengbu Anhui, 233004, China.

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