Dosimetric assessment of patient dose calculation on a deep learning-based synthesized computed tomography image for adaptive radiotherapy.

Journal: Journal of applied clinical medical physics
Published Date: Mar 25, 2022

Abstract

PURPOSE: Dose computation using cone beam computed tomography (CBCT) images is inaccurate for the purpose of adaptive treatment planning. The main goal of this study is to assess the dosimetric accuracy of synthetic computed tomography (CT)-based calculation for adaptive planning in the upper abdominal region. We hypothesized that deep learning-based synthetically generated CT images will produce comparable results to a deformed CT (CTdef) in terms of dose calculation, while displaying a more accurate representation of the daily anatomy and therefore superior dosimetric accuracy.

Authors

  • Olga M Dona Lemus
    Department of Radiation Oncology, Columbia University Irving Medical Center, New York City, New York, USA.
  • Yi-Fang Wang
    Department of Radiation Oncology, New York-Presbyterian Columbia University Irving Medical Center.
  • Fiona Li
    Department of Radiation Oncology, Columbia University Irving Medical Center, New York City, New York, USA.
  • Sachin Jambawalikar
    Department of Radiology, Columbia University Medical Center, New York, NY.
  • David P Horowitz
    Department of Radiation Oncology, New York-Presbyterian Columbia University Irving Medical Center.
  • Yuanguang Xu
    Department of Radiation Oncology, Columbia University Irving Medical Center, New York City, New York, USA.
  • Cheng-Shie Wuu
    Department of Radiation Oncology, Columbia University Irving Medical Center, New York City, New York, USA.

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