Evaluating the Hounsfield unit assignment and dose differences between CT-based standard and deep learning-based synthetic CT images for MRI-only radiation therapy of the head and neck.

Journal: Journal of applied clinical medical physics
Published Date: Dec 21, 2023

Abstract

BACKGROUND: Magnetic resonance image only (MRI-only) simulation for head and neck (H&N) radiotherapy (RT) could allow for single-image modality planning with excellent soft tissue contrast. In the MRI-only simulation workflow, synthetic computed tomography (sCT) is generated from MRI to provide electron density information for dose calculation. Bone/air regions produce little MRI signal which could lead to electron density misclassification in sCT. Establishing the dosimetric impact of this error could inform quality assurance (QA) procedures using MRI-only RT planning or compensatory methods for accurate dosimetric calculation.

Authors

  • Kamal Singhrao
    David Geffen School of Medicine, University of California, Los Angeles, 10833 Le Conte Ave, Los Angeles, 90095, CA, USA.
  • Catherine Lu Dugan
    Department of Radiation Oncology, University of California, San Francisco, San Francisco, California, USA.
  • Christina Calvin
    Department of Radiation Oncology, University of California, San Francisco, San Francisco, California, USA.
  • Luis Pelayo
    Department of Radiation Oncology, University of California, San Francisco, San Francisco, California, USA.
  • Sue Sun Yom
    Department of Radiation Oncology, University of California, San Francisco, San Francisco, California, USA.
  • Jason Wing-Hong Chan
    Department of Radiation Oncology, University of California, San Francisco, San Francisco, California, USA.
  • Jessica Elizabeth Scholey
    Department of Radiation Oncology, University of California, San Francisco, San Francisco, California, USA.
  • Lisa Singer
    Department of Radiation Oncology, University of California, San Francisco, San Francisco, California, USA.

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