Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis.

Journal: Clinical imaging
Published Date: Jul 1, 2025

Abstract

BACKGROUND AND AIMS: Osteosarcoma (OS) is the most common primary bone malignancy, and neoadjuvant chemotherapy (NAC) improves survival rates. However, OS heterogeneity results in variable treatment responses, highlighting the need for reliable, non-invasive tools to predict NAC response. Radiomics-based machine learning (ML) offers potential for identifying imaging biomarkers to predict treatment outcomes. This systematic review and meta-analysis evaluated the accuracy and reliability of radiomics models for predicting NAC response in OS.

Authors

  • Mohsen Salimi
    Research Center of Thoracic Oncology (RCTO), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Shakiba Houshi
    Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Ali Gholamrezanezhad
    Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA.
  • Pouria Vadipour
    Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, USA.
  • Sharareh Seifi
    Research Center of Thoracic Oncology (RCTO), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address: sh_seifi@yahoo.com.

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