Self-gated Radial MRI for Respiratory Motion Compensation on Hybrid PET/MR Systems

  • Robert Grimm
  • Sebastian Fürst
  • Isabel Dregely
  • Christoph Forman
  • Jana Maria Hutter
  • Sibylle I. Ziegler
  • Stephan Nekolla
  • Berthold Kiefer
  • Markus Schwaiger
  • Joachim Hornegger
  • Tobias Block
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8151)

Abstract

Accurate localization and uptake quantification of lesions in the chest and abdomen using PET imaging is challenging due to the respiratory motion during the exam. The advent of hybrid PET/MR systems offers new ways to compensate for respiratory motion without exposing the patient to additional radiation. The use of self-gated reconstructions of a 3D radial stack-of-stars GRE acquisition is proposed to derive a high-resolution MRI motion model. The self-gating signal is used to perform respiratory binning of the simultaneously acquired PET raw data. Matching μ-maps are generated for every bin, and post-reconstruction registration is performed in order to obtain a motion-compensated PET volume from the individual gates. The proposed method is demonstrated in-vivo for three clinical patients. Motion-corrected reconstructions are compared against ungated and gated PET reconstructions. In all cases, motion-induced blurring of lesions in the liver and lung was substantially reduced, without compromising SNR as it is the case for gated reconstructions.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Robert Grimm
    • 1
  • Sebastian Fürst
    • 2
  • Isabel Dregely
    • 2
  • Christoph Forman
    • 1
  • Jana Maria Hutter
    • 1
  • Sibylle I. Ziegler
    • 2
  • Stephan Nekolla
    • 2
  • Berthold Kiefer
    • 3
  • Markus Schwaiger
    • 2
  • Joachim Hornegger
    • 1
  • Tobias Block
    • 4
  1. 1.Pattern Recognition LabFAU ErlangenErlangenGermany
  2. 2.Department of Nuclear MedicineTU MunichMunichGermany
  3. 3.Siemens Healthcare MRErlangenGermany
  4. 4.Department of RadiologyNYU Langone Medical CenterNew York CityUSA

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