AI-Assisted Post Contrast Brain MRI: Eighty Percent Reduction in Contrast Dose.

Journal: Academic radiology
Published Date: Nov 26, 2024

Abstract

OBJECTIVES: In the context of growing safety concerns regarding the use of gadolinium-based contrast agents in contrast-enhanced MRI, there is a need for dose reduction without compromising diagnostic accuracy. A deep learning (DL) method is proposed and evaluated in this study for predicting full-dose contrast-enhanced T1w images from multiparametric MRI acquired with 20% of the standard dose of gadolinium-based contrast agents.

Authors

  • Mohadese Ahmadzade
    Department of Radiology, Section of Vascular and Interventional Radiology, Baylor College of Medicine, Houston, TX (M.A., M.G.R.).
  • Fanny Emilia Morón
    Department of Radiology, Section of Neuroradiology, Baylor College of Medicine, Houston, TX (F.E.M.).
  • Ravi Shastri
    Department of radiology, Section of Interventional Neuroradiology, Baylor College of Medicine, Houston, TX (R.S.).
  • Christie M Lincoln
    Department of Radiology, Section of Neuroradiology, MD Anderson Cancer center, UT McGovern, Houston, TX (C.M.L.).
  • Mohammad Ghasemi Rad
    Department of Radiology, Section of Vascular and Interventional Radiology, Baylor College of Medicine, Houston, TX (M.A., M.G.R.). Electronic address: mdghrad@gmail.com.

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