Prediction of Chemotherapy Response of Osteosarcoma Using Baseline F-FDG Textural Features Machine Learning Approaches with PCA.

Journal: Contrast media & molecular imaging
Published Date: Jan 1, 2019

Abstract

PURPOSE: Patients with high-grade osteosarcoma undergo several chemotherapy cycles before surgical intervention. Response to chemotherapy, however, is affected by intratumor heterogeneity. In this study, we assessed the ability of a machine learning approach using baseline F-fluorodeoxyglucose (F-FDG) positron emitted tomography (PET) textural features to predict response to chemotherapy in osteosarcoma patients.

Authors

  • Su Young Jeong
    Samsung Sotong Clinic, Namyangju, Kyeonggi-do, Republic of Korea.
  • Wook Kim
    Division of RI-Convergence Research, Korea Institute of Radiological and Medical Sciences, Seoul 01812, Republic of Korea.
  • Byung Hyun Byun
    Department of Nuclear Medicine, Korea Institute of Radiological and Medical Sciences, Seoul 01812, Republic of Korea.
  • Chang-Bae Kong
    Department of Orthopedic Surgery, Korea Institute of Radiological and Medical Sciences, Seoul 01812, Republic of Korea.
  • Won Seok Song
    Department of Orthopedic Surgery, Korea Institute of Radiological and Medical Sciences, Seoul 01812, Republic of Korea.
  • Ilhan Lim
    Department of Nuclear Medicine, Korea Institute of Radiological and Medical Sciences, Seoul 01812, Republic of Korea.
  • Sang Moo Lim
    Department of Nuclear Medicine, Korea Institute of Radiological and Medical Sciences, Seoul 01812, Republic of Korea.
  • Sang-Keun Woo
    Division of RI-Convergence Research, Korea Institute of Radiological and Medical Sciences, Seoul 01812, Republic of Korea.

Keywords

External Resources

Popular Topics
Recent Journals