Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging.

Journal: NeuroImage
PMID: 39894238

Abstract

INTRODUCTION: Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonance Spectroscopic Imaging (MRSI). Advanced MRSI using non-cartesian compressed-sense acquisition enables fast high-resolution metabolic imaging but has lengthy reconstruction times that limits throughput and needs expert user interaction. Here, we present a robust and efficient Deep Learning reconstruction embedded in a physical model within an end-to-end automated processing pipeline to obtain high-quality metabolic maps.

Authors

  • Paul J Weiser
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Georg Langs
    Department of Biomedical Imaging and Image-guided Therapy Computational Imaging Research Lab, Medical University of Vienna Vienna Austria.
  • Wolfgang Bogner
    High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Stanislav Motyka
    High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Bernhard Strasser
    High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
  • Polina Golland
    CSAIL/EECS, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Nalini Singh
    Google Health, Palo Alto, CA, USA.
  • Jorg Dietrich
    Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Erik Uhlmann
    Department of Neurology, Beth-Israel Deaconess Medical Center, Boston, MA, USA.
  • Tracy Batchelor
    Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA.
  • Daniel Cahill
    Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA.
  • Malte Hoffmann
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Radiology Department, Boston, MA, USA.
  • Antoine Klauser
    Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
  • Ovidiu C Andronesi
    Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, USA.

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