Dosimetric impact of contour editing on CT and MRI deep-learning autosegmentation for brain OARs.

Journal: Journal of applied clinical medical physics
PMID: 38664894

Abstract

PURPOSE: To establish the clinical applicability of deep-learning organ-at-risk autocontouring models (DL-AC) for brain radiotherapy. The dosimetric impact of contour editing, prior to model training, on performance was evaluated for both CT and MRI-based models. The correlation between geometric and dosimetric measures was also investigated to establish whether dosimetric assessment is required for clinical validation.

Authors

  • Nouf M Alzahrani
    Information Technology Department, Collage of Computer Science and Information Technology, Al Baha University, Al Bahah 65731, Saudi Arabia.
  • Ann M Henry
    Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, United Kingdom; Radiotherapy Research Group, Leeds Institute of Medical Research, University of Leeds, United Kingdom.
  • Anna K Clark
    Department of Medical Physics and Engineering, St James's University Hospital, Leeds, UK.
  • Bashar M Al-Qaisieh
    Department of Medical Physics and Engineering, St James's University Hospital, Leeds, UK.
  • Louise J Murray
    School of Medicine, University of Leeds, Leeds, UK.
  • Michael G Nix
    Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, United Kingdom.

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