Respiratory motion prediction and prospective correction for free-breathing arterial spin-labeled perfusion MRI of the kidneys.

Journal: Medical physics
Published Date: Mar 1, 2017

Abstract

PURPOSE: Respiratory motion prediction using an artificial neural network (ANN) was integrated with pseudocontinuous arterial spin labeling (pCASL) MRI to allow free-breathing perfusion measurements in the kidney. In this study, we evaluated the performance of the ANN to accurately predict the location of the kidneys during image acquisition.

Authors

  • Hao Song
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
  • Dan Ruan
    Departments of Radiation Oncology, Biomedical Physics and Bioengineering, UCLA, Los Angeles, CA, 90095, USA.
  • Wenyang Liu
    Departments of Radiation Oncology, Biomedical Physics and Bioengineering, UCLA, Los Angeles, CA, 90095, USA.
  • V Andrew Stenger
    Department of Medicine, University of Hawai'i at Manoa, Honolulu, HI, 96813, USA.
  • Rolf Pohmann
    High-Field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, 72076, Tubingen, Germany.
  • Maria A Fernández-Seara
    Department of Radiology, University of Navarra Hospital, 31008, Pamplona, Spain.
  • Tejas Nair
    DMC R&D Center, Samsung Electronics Inc., Seocho-gu, 06765, Seoul, Korea.
  • Sungkyu Jung
    Department of Statistics, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
  • Jingqin Luo
    Department of Surgery, Washington University in St. Louis, St. Louis, MO, 63110, USA.
  • Yuichi Motai
  • Jingfei Ma
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
  • John D Hazle
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030.
  • H Michael Gach
    Departments of Radiation Oncology and Radiology, Washington University, St. Louis, MO, 63110, USA.

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