Distinguishing True Progression From Radionecrosis After Stereotactic Radiation Therapy for Brain Metastases With Machine Learning and Radiomics.

Journal: International journal of radiation oncology, biology, physics
Published Date: May 24, 2018

Abstract

PURPOSE: Treatment effect or radiation necrosis after stereotactic radiosurgery (SRS) for brain metastases is a common phenomenon often indistinguishable from true progression. Radiomics is an emerging field that promises to improve on conventional imaging. In this study, we sought to apply a radiomics-based prediction model to the problem of diagnosing treatment effect after SRS.

Authors

  • Luke Peng
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Vishwa Parekh
    The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Peng Huang
    College of Food Science, Sichuan Agricultural University, Ya'an 625014, China.
  • Doris D Lin
    The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Khadija Sheikh
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Brock Baker
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Talia Kirschbaum
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Francesca Silvestri
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Jessica Son
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Adam Robinson
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Ellen Huang
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Heather Ames
    Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Jimm Grimm
  • Linda Chen
    Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America.
  • Colette Shen
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Michael Soike
    Department of Radiation Oncology, Wake Forest Baptist Health, Winston-Salem, NC.
  • Emory McTyre
    Department of Radiation Oncology, Wake Forest Baptist Health, Winston-Salem, NC.
  • Kristin Redmond
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Michael Lim
    Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Junghoon Lee
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Michael A Jacobs
    The Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Lawrence Kleinberg
    Department of Radiation Oncology, Johns Hopkins University School of Medicine, Baltimore, MD. Electronic address: kleinla@jhmi.edu.

Keywords

External Resources

Popular Topics
Recent Journals