Deep Learning for Automated Ventricle and Periventricular Space Segmentation on CT and T1CE MRI in Neuro-Oncology Patients.

Journal: Cancers
Published Date: May 8, 2025

Abstract

PURPOSE: This study aims to create a deep learning (DL) model capable of accurately delineating the ventricles, and by extension, the periventricular space (PVS), following the 2021 EPTN Neuro-Oncology Atlas guidelines on T1-weighted contrast-enhanced MRI scans (T1CE). The performance of this DL model was quantitatively and qualitatively compared with an off-the-shelf model.

Authors

  • Mart Wubbels
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, 6229 ET Maastricht, The Netherlands.
  • Marvin Ribeiro
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, 6229 ET Maastricht, The Netherlands.
  • Jelmer M Wolterink
    Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands.
  • Wouter van Elmpt
    Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, The Netherlands. Electronic address: wouter.vanelmpt@maastro.nl.
  • Inge Compter
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, 6229 ET Maastricht, The Netherlands.
  • David Hofstede
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, 6229 ET Maastricht, The Netherlands.
  • Nikolina E Birimac
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, 6229 ET Maastricht, The Netherlands.
  • Femke Vaassen
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, 6229 ET Maastricht, The Netherlands.
  • Kati Palmgren
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, 6229 ET Maastricht, The Netherlands.
  • Hendrik H G Hansen
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, 6229 ET Maastricht, The Netherlands.
  • Hiska L van der Weide
    Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, 9713 AP Groningen, The Netherlands.
  • Charlotte L Brouwer
    Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands.
  • Miranda C A Kramer
    Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, 9713 AP Groningen, The Netherlands.
  • Daniëlle B P Eekers
    Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, Netherlands.
  • Catharina M L Zegers
    Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, P.O. Box 616, Maastricht, 6200 MD, Netherlands, 31 43 38 81863.

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