MRI-based 2.5D deep learning radiomics nomogram for the differentiation of benign versus malignant vertebral compression fractures.

Journal: Frontiers in oncology
Published Date: Jan 1, 2025

Abstract

OBJECTIVE: Vertebral compression fractures (VCFs) represent a prevalent clinical problem, yet distinguishing acute benign variants from malignant pathological fractures constitutes a persistent diagnostic dilemma. To develop and validate a MRI-based nomogram combining clinical and deep learning radiomics (DLR) signatures for the differentiation of benign versus malignant vertebral compression fractures (VCFs).

Authors

  • Wenhua Liang
    Department of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Hong Yu
    University of Massachusetts Medical School, Worcester, MA.
  • Lisha Duan
    Department of Radiology, The Third Hospital of Hebei Medical University, Shijiazhuang, 050051, Hebei, China.
  • Xiaona Li
    Department of Radiology, Third Hospital of Hebei Medical University, Shijiangzhuang, China.
  • Ming Wang
    Brain center, Zhejiang Hospital, Hangzhou, China.
  • Bing Wang
    Computer Science & Engineering Department at the University of Connecticut.
  • Jianling Cui
    Department of Radiology, Third Hospital of Hebei Medical University, Shijiangzhuang, China.

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