Journal of Imaging (Dec 2022)

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

DOI
https://doi.org/10.3390/jimaging9010002
Journal volume & issue
Vol. 9, no. 1
p. 2

Abstract

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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.

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