Virtual Monochromatic Imaging of Half-Iodine-Load, Contrast-Enhanced Computed Tomography with Deep Learning Image Reconstruction in Patients with Renal Insufficiency: A Clinical Pilot Study.

Journal: Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
PMID: 40058838

Abstract

BACKGROUND: We retrospectively examined image quality (IQ) of thin-slice virtual monochromatic imaging (VMI) of half-iodine-load, abdominopelvic, contrast-enhanced CT (CECT) by dual-energy CT (DECT) with deep learning image reconstruction (DLIR).

Authors

  • Shingo Harashima
    Department of Radiology, Tokyo Women's Medical University Medical Center East, Tokyo, Japan.
  • Rika Fukui
    Department of Radiology, Tokyo Women's Medical University Medical Center East, Arakawa-ku.
  • Wakana Samejima
    Department of Radiology, Tokyo Women's Medical University Medical Center East, Tokyo, Japan.
  • Yuta Hirose
    Graduate School of Medical and Care Technology, Teikyo University, Tokyo, Japan.
  • Toshiya Kariyasu
    Department of Radiology, Kyorin University School of Medicine, Tokyo, Japan.
  • Makiko Nishikawa
    Department of Radiology, Faculty of Medicine, Kyorin University, 6-20-2 Shinkawa, Mitaka-shi, Tokyo, 181-8611, Japan.
  • Hidenori Yamaguchi
    Department of Radiology, Tokyo Women's Medical University Adachi Medical Center.
  • Haruhiko Machida
    Department of Radiology, Kyorin University School of Medicine, Tokyo, Japan.

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