Thin-Slice Pituitary MRI with Deep Learning-Based Reconstruction for Preoperative Prediction of Cavernous Sinus Invasion by Pituitary Adenoma: A Prospective Study.

Journal: AJNR. American journal of neuroradiology
Published Date: Feb 1, 2022

Abstract

BACKGROUND AND PURPOSE: Accurate radiologic prediction of cavernous sinus invasion by pituitary adenoma remains challenging. We aimed to assess whether 1-mm-slice-thickness MRI with deep learning-based reconstruction can better predict cavernous sinus invasion by pituitary adenoma preoperatively and to estimate the depth of invasion and degree of contact in relation to the carotid artery, compared with 3-mm-slice-thickness MRI.

Authors

  • M Kim
    From the Department of Radiology and Research Institute of Radiology (M.K., H.S.K., J.E.P., S.J.K.).
  • H S Kim
    Department of Pharmacology, Pharmacogenomic Research Center for Membrane Transporters, Brain Korea 21 PLUS Project for Medical Sciences; Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul.
  • J E Park
    Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K.), Asan Medical Center, University of Ulsan College of Medicine.
  • S Y Park
    Colorectal Cancer Center, Kyungpook National University Chilgok Hospital, School of Medicine, Kyungpook National University , 807 Hogukro, Buk-gu, Daegu, 41404, South Korea.
  • Y-H Kim
    Division of Thoracic Surgery, Department of Thoracic & Cardiovascular Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • S J Kim
    From the Department of Radiology and Research Institute of Radiology (C.H.S., W.H.S., S.J.K.) sjkimjb5@gmail.com.
  • J Lee
  • M R Lebel
    GE Healthcare (M.R.L.), Calgary, Alberta, Canada.

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