Assessment of lymph node area coverage with total marrow irradiation and implementation of total marrow and lymphoid irradiation using automated deep learning-based segmentation.

Journal: PloS one
Published Date: Mar 8, 2024

Abstract

BACKGROUND: Total marrow irradiation (TMI) and total marrow and lymphoid irradiation (TMLI) have the advantages. However, delineating target lesions according to TMI and TMLI plans is labor-intensive and time-consuming. In addition, although the delineation of target lesions between TMI and TMLI differs, the clinical distinction is not clear, and the lymph node (LN) area coverage during TMI remains uncertain. Accordingly, this study calculates the LN area coverage according to the TMI plan. Further, a deep learning-based model for delineating LN areas is trained and evaluated.

Authors

  • Hyeon Seok Choi
    Department of Radiation Oncology, Seoul National University Hospital, Seoul, South Korea.
  • Hyun-Cheol Kang
    Department of Radiation Oncology, Seoul National University Hospital, Seoul, South Korea.
  • Eui Kyu Chie
    Department of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea.
  • Kyung Hwan Shin
    Department of Radiation Oncology, Seoul National University College of Medicine, Seoul, Republic of Korea. Electronic address: radiat@snu.ac.kr.
  • Ji Hyun Chang
    Department of Radiation Oncology, SMG-SNU Boramae Medical Center, Seoul, Korea.
  • Bum-Sup Jang
    Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea.

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