An artificial intelligence interpretable tool to predict risk of deep vein thrombosis after endovenous thermal ablation.

Journal: Journal of vascular surgery. Venous and lymphatic disorders
Published Date: Apr 30, 2025

Abstract

OBJECTIVE: Endovenous thermal ablation (EVTA) stands as one of the primary treatments for superficial venous insufficiency. Concern exists about the potential for thromboembolic complications following this procedure. Although rare, those complications can be severe, necessitating early identification of patients prone to increased thrombotic risks. This study aims to leverage artificial intelligence-based algorithms to forecast patients' likelihood of developing deep vein thrombosis (DVT) within 30 days following EVTA.

Authors

  • Azadeh Tabari
    Department of Radiology, Massachusetts General Hospital, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States.
  • Yu Ma
    Department of Electronic Engineering, Fudan University, Shanghai, China.
  • Jesus Alfonso
    Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA.
  • Anthony Gebran
    - University of Pittsburgh Medical Center, Department of Surgery - Pittsburgh - PA - Estados Unidos.
  • Haytham Kaafarani
    - Harvard Medical School, Trauma, Emergency Surgery and Surgical Critical Care, Massachusetts General Hospital - Boston - MA - Estados Unidos.
  • Dimitris Bertsimas
    Dimitris Bertsimas, Jack Dunn, Colin Pawlowski, John Silberholz, Alexander Weinstein, and Ying Daisy Zhuo, Massachusetts Institute of Technology, Cambridge; Eddy Chen, Massachusetts General Hospital Cancer Center; Harvard Medical School; Aymen A. Elfiky, Dana-Farber Cancer Institute; Brigham and Women's Hospital; Harvard Medical School, Boston, MA.
  • Dania Daye
    Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA. Electronic address: ddaye@mgh.harvard.edu.

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