Deep Learning Reconstruction of Prospectively Accelerated MRI of the Pancreas: Clinical Evaluation of Shortened Breath-Hold Examinations With Dixon Fat Suppression.

Journal: Investigative radiology
Published Date: Jul 23, 2024

Abstract

OBJECTIVE: Deep learning (DL)-enabled magnetic resonance imaging (MRI) reconstructions can enable shortening of breath-hold examinations and improve image quality by reducing motion artifacts. Prospective studies with DL reconstructions of accelerated MRI of the upper abdomen in the context of pancreatic pathologies are lacking. In a clinical setting, the purpose of this study is to investigate the performance of a novel DL-based reconstruction algorithm in T1-weighted volumetric interpolated breath-hold examinations with partial Fourier sampling and Dixon fat suppression (hereafter, VIBE-Dixon DL ). The objective is to analyze its impact on acquisition time, image sharpness and quality, diagnostic confidence, pancreatic lesion conspicuity, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR).

Authors

  • Marianna Chaika
    Department of Diagnostic and Interventional Radiology, Eberhard-Karls University, Hoppe-Seyler-Str. 3, 72076 Tuebingen, Germany.
  • Jan M Brendel
    Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany.
  • Stephan Ursprung
    Department of Radiology and Cancer Research UK Cambridge Centre, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England.
  • Judith Herrmann
    Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany.
  • Sebastian Gassenmaier
    Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.
  • Andreas Brendlin
    Department of Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, Hoppe-Seyler-Strasse 3, 72076 Tuebingen, Germany.
  • Sebastian Werner
  • Marcel Dominik Nickel
    MR Application Predevelopment, Siemens Healthineers AG, Erlangen, Germany.
  • Konstantin Nikolaou
    Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076 Tübingen, Germany.
  • Saif Afat
    Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany.
  • Haidara Almansour
    From the Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen.

Keywords

External Resources

Popular Topics
Recent Journals