Deep learning for automated segmentation of radiation-induced changes in cerebral arteriovenous malformations following radiosurgery.

Journal: BMC medical imaging
Published Date: Jul 1, 2025

Abstract

BACKGROUND: Despite the widespread use of stereotactic radiosurgery (SRS) to treat cerebral arteriovenous malformations (AVMs), this procedure can lead to radiation-induced changes (RICs) in the surrounding brain tissue. Volumetric assessment of RICs is crucial for therapy planning and monitoring. RICs that appear as hyper-dense areas in magnetic resonance T2-weighted (T2w) images are clearly identifiable; however, physicians lack tools for the segmentation and quantification of these areas. This paper presents an algorithm to calculate the volume of RICs in patients with AVMs following SRS. The algorithm could be used to predict the course of RICs and facilitate clinical management.

Authors

  • Hsing-Hao Ho
    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Huai-Che Yang
    Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang-Ming University, Taipei, Taiwan.
  • Wen-Xiang Yang
    Department of Computer Science & Information Engineering, National United University, Miaoli, Taiwan.
  • Cheng-Chia Lee
    Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang-Ming University, Taipei, Taiwan; Brain Research Center, National Yang-Ming University, Taipei, Taiwan.
  • Hsiu-Mei Wu
    Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang-Ming University, Taipei, Taiwan.
  • I-Chun Lai
    School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
  • Ching-Jen Chen
    Department of Neurological Surgery, University of Virginia Health System, Charlottesville, Virginia, USA.
  • Syu-Jyun Peng
    Biomedical Electronics Translational Research Center, National Chiao Tung University, Hsin-Chu, Taiwan; Institute of Electronics, National Chiao Tung University, Hsin-Chu, Taiwan. Electronic address: blue.year@msa.hinet.net.

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