Prediction of the treatment response and local failure of patients with brain metastasis treated with stereotactic radiosurgery using machine learning: A systematic review and meta-analysis.

Journal: Neurosurgical review
PMID: 38684566

Abstract

BACKGROUND: Stereotactic radiosurgery (SRS) effectively treats brain metastases. It can provide local control, symptom relief, and improved survival rates, but it poses challenges in selecting optimal candidates, determining dose and fractionation, monitoring for toxicity, and integrating with other modalities. Practical tools to predict patient outcomes are also needed. Machine learning (ML) is currently used to predict treatment outcomes. We aim to investigate the accuracy of ML in predicting treatment response and local failure of brain metastasis treated with SRS.

Authors

  • Mohammad Amin Habibi
    Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
  • Farhang Rashidi
    School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • Adriana Habibzadeh
    Student Research Committee, Fasa University of Medical Sciences, Fasa, Iran.
  • Ehsan Mehrtabar
    Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran.
  • Mohammad Reza Arshadi
    Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran.
  • Mohammad Sina Mirjani
    Student Research Committee, Faculty of Medicine, Qom University of Medical Sciences, Qom, Iran.

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