Low energy virtual monochromatic CT with deep learning image reconstruction to improve delineation of endoleaks.

Journal: Clinical radiology
PMID: 39079807

Abstract

AIM: This study aimed to investigate the utility of low-energy virtual monochromatic imaging (VMI) combined with deep-learning image reconstruction (DLIR) in improving the delineation of endoleaks (ELs) after endovascular aortic repair (EVAR) in contrast-enhanced dual-energy CT (DECT).

Authors

  • T Higashigawa
    Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan. Electronic address: higashikawat@med.mie-u.ac.jp.
  • Y Ichikawa
    Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan.
  • K Nakajima
    The Hakubi Center for Advanced Research, Kyoto University, 606-8501 Kyoto, Japan. Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics, Kyoto University, 606-8501 Kyoto, Japan.
  • T Kobayashi
    Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Yamadaoka 1-7, Suita, Osaka 565-0871, Japan.
  • K Domae
    Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan.
  • A Yamazaki
    Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan.
  • N Kato
    Tokorozawa Loyal Hospital.
  • T Ouchi
    Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie 514-8507, Japan.
  • H Kato
    Department of Transfusion Medicine, Aichi Medical University, Nagakute, Aichi 480-1195, Japan.
  • H Sakuma
    Department of Radiology, Mie University Graduate School of Medicine, Tsu, Japan.

Keywords

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