Machine learning based radiomics approach for outcome prediction of meningioma - a systematic review.

Journal: F1000Research
PMID: 40206662

Abstract

INTRODUCTION: Meningioma is the most common brain tumor in adults. Magnetic resonance imaging (MRI) is the preferred imaging modality for assessing tumor outcomes. Radiomics, an advanced imaging technique, assesses tumor heterogeneity and identifies predictive markers, offering a non-invasive alternative to biopsies. Machine learning (ML) based radiomics models enhances diagnostic and prognostic accuracy of tumors. Comprehensive review on ML-based radiomics models for predicting meningioma recurrence and survival are lacking. Hence, the aim of the study is to summarize the performance measures of ML based radiomics models in the prediction of outcomes such as progression/recurrence (P/R) and overall survival analysis of meningioma.

Authors

  • Saroh S
    Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
  • Saikiran Pendem
    Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Karnataka, Manipal, 576104, India.
  • Prakashini K
    Department of Radio Diagnosis and Imaging, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
  • Shailesh Nayak S
    Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
  • Girish R Menon
    Department of Neurosurgery, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
  • Priyanka -
    Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
  • Divya B
    Department of Electronics and Communication Engineering, Manipal institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.

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