Machine Learning and MRI-Based Whole-Organ Magnetic Resonance Imaging Score (WORMS): A Novel Approach to Enhancing Genicular Artery Embolization Outcomes in Knee Osteoarthritis.

Journal: Cardiovascular and interventional radiology
Published Date: Aug 4, 2025

Abstract

PURPOSE: To evaluate the feasibility of machine learning (ML) models using preprocedural MRI-based Whole-Organ Magnetic Resonance Imaging Score (WORMS) and clinical parameters to predict treatment response after genicular artery embolization in patients with knee osteoarthritis.

Authors

  • Ali Dablan
    Department of Interventional Radiology, Basaksehir Cam and Sakura City Hospital, 34480, Istanbul, Turkey. alidablan@hotmail.com.
  • Hamit Özgül
    Department of Interventional Radiology, Basaksehir Cam and Sakura City Hospital, 34480, Istanbul, Turkey.
  • Mustafa Fatih Arslan
    Department of Interventional Radiology, Basaksehir Cam and Sakura City Hospital, 34480, Istanbul, Turkey.
  • Oğuzhan Türksayar
    Department of Interventional Radiology, Basaksehir Cam and Sakura City Hospital, 34480, Istanbul, Turkey.
  • Mehmet Cingöz
    Department of Radiology, Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.
  • Ilhan Nahit Mutlu
    Department of Interventional Radiology, Basaksehir Cam and Sakura City Hospital, 34480, Istanbul, Turkey.
  • Cagri Erdim
    Department of Radiology, Istanbul Training and Research Hospital, Istanbul, Turkey.
  • Tevfik Guzelbey
    Department of Interventional Radiology, Basaksehir Cam and Sakura City Hospital, 34480, Istanbul, Turkey.
  • Ozgur Kılıckesmez
    Department of Interventional Radiology, Basaksehir Cam and Sakura City Hospital, 34480, Istanbul, Turkey.

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