A Co-Plane Machine Learning Model Based on Ultrasound Radiomics for the Evaluation of Diabetic Peripheral Neuropathy.

Journal: Academic radiology
Published Date: Aug 8, 2025

Abstract

RATIONALE AND OBJECTIVES: Detection of diabetic peripheral neuropathy (DPN) is critical for preventing severe complications. Machine learning (ML) and radiomics offer promising approaches for the diagnosis of DPN; however, their application in ultrasound-based detection of DPN remains limited. Moreover, there is no consensus on whether longitudinal or transverse ultrasound planes provide more robust radiomic features for nerve evaluation. This study aimed to analyze and compare radiomic features from different ultrasound planes of the tibial nerve and to develop a co-plane fusion ML model to enhance the diagnostic accuracy of DPN.

Authors

  • Yanfeng Jiang
    State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai, China.
  • Rongli Peng
    Department of Ultrasound, Shaoxing People's Hospital (The First Affiliated Hospital, Shaoxing University), Shaoxing, China (Y.J., R.P., X.L., H.S., Z.Y., Z.J.).
  • Xiatian Liu
    Department of Ultrasound, Shaoxing People's Hospital (The First Affiliated Hospital, Shaoxing University), Shaoxing, China (Y.J., R.P., X.L., H.S., Z.Y., Z.J.).
  • Meina Xu
    Department of Ultrasound, Xiamen Hospital of Traditional Chinese Medicine, Xiamen, China (M.X.).
  • Hualiang Shen
    Department of Ultrasound, Shaoxing People's Hospital (The First Affiliated Hospital, Shaoxing University), Shaoxing, China (Y.J., R.P., X.L., H.S., Z.Y., Z.J.).
  • Zhelin Yu
    Department of Ultrasound, Shaoxing People's Hospital (The First Affiliated Hospital, Shaoxing University), Shaoxing, China (Y.J., R.P., X.L., H.S., Z.Y., Z.J.).
  • Zhenzhen Jiang
    Department of Ultrasound, Shaoxing People's Hospital (The First Affiliated Hospital, Shaoxing University), Shaoxing, China (Y.J., R.P., X.L., H.S., Z.Y., Z.J.). Electronic address: fjzzjzz@usx.edu.cn.

Keywords

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