Synthetic CT generation from CBCT and MRI using StarGAN in the Pelvic Region.

Radiology Genetics Oncology/Hematology
Journal: Radiation oncology (London, England)
Published Date: Feb 4, 2025

Abstract

RATIONALE AND OBJECTIVES: This study evaluated StarGAN, a deep learning model designed to generate synthetic computed tomography (sCT) images from magnetic resonance imaging (MRI) and cone-beam computed tomography (CBCT) data using a single model. The goal was to provide accurate Hounsfield unit (HU) data for dose calculation to enable MRI simulation and adaptive radiation therapy (ART) using CBCT or MRI. We also compared the performance and benefits of StarGAN to the commonly used CycleGAN.

Authors

  • Paritt Wongtrakool
    Master of Science Program in Medical Physics, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Chanon Puttanawarut
    Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan, Thailand.
  • Pimolpun Changkaew
    Division of Radiation and Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Supakiet Piasanthia
    Division of Radiation and Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Pareena Earwong
    Master of Science Program in Medical Physics, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Nauljun Stansook
    Division of Radiation and Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
  • Suphalak Khachonkham
    Division of Radiation and Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand. [email protected].

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