Attenuation Correction Using Template PET Registration for Brain PET: A Proof-of-Concept Study

  • Markus Jehl*
  • , Ekaterina Mikhaylova
  • , Valerie Treyer
  • , Marlena Hofbauer
  • , Martin Hüllner
  • , Philipp A. Kaufmann
  • , Alfred Buck
  • , Geoff Warnock
  • , Viet Dao
  • , Charalampos Tsoumpas
  • , Daniel Deidda
  • , Kris Thielemans
  • , Max Ludwig Ahnen
  • , Jannis Fischer
  • *Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    6 Citations (Scopus)
    91 Downloads (Pure)

    Abstract

    NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient’s head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [18F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET.

    Original languageEnglish
    Article number2
    Number of pages15
    JournalJournal of Imaging
    Volume9
    Issue number1
    DOIs
    Publication statusPublished - Jan-2023

    Keywords

    • attenuation correction
    • brain
    • image reconstruction
    • Nifty-Reg
    • PET
    • registration
    • STIR
    • tomography

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