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:10.3390/jimaging9010002

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

J Imaging. 2022 Dec 21;9(1):2. doi: 10.3390/jimaging9010002.

Authors

Markus Jehl¹, Ekaterina Mikhaylova¹, Valerie Treyer^{2

3}, Marlena Hofbauer², Martin Hüllner², Philipp A Kaufmann², Alfred Buck¹, Geoff Warnock⁴, Viet Dao⁵, Charalampos Tsoumpas^{5

6}, Daniel Deidda⁷, Kris Thielemans^{8

9

10}, Max Ludwig Ahnen¹, Jannis Fischer¹

Affiliations

¹ Positrigo AG, 8005 Zurich, Switzerland.
² Department of Nuclear Medicine, University Hospital Zurich, 8091 Zurich, Switzerland.
³ Institute for Regenerative Medicine, University of Zurich, 8006 Zurich, Switzerland.
⁴ PMOD Technologies LLC, 8117 Faellanden, Switzerland.
⁵ Department of Statistics, School of Mathematics, University of Leeds, Leeds LS2 9JT, UK.
⁶ Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.
⁷ National Physical Laboratory, Teddington TW11 0LW, UK.
⁸ Institute of Nuclear Medicine, University College London, London NW1 2BU, UK.
⁹ Centre for Medical Image Computing, UCL, Gower Street, London WC1E 6BT, UK.
¹⁰ Algorithms Software Consulting Ltd., London SW15 5HX, UK.

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.

Keywords: Nifty-Reg; PET; STIR; attenuation correction; brain; image reconstruction; registration; tomography.

Grants and funding

This work was performed by Positrigo and was supported by Markus Rauh/ETH Zurich Foundation Pioneer Fellowship PIO-07 16-2, Innosuisse Grant 27785.1 PFLS-LS, Stephan Schmidheiny and Viktoria Schmidheiny and the ETH Zurich Foundation 2018-HE-311, European Union’s Horizon 2020 research and innovation program: 855292 and European Union’s Horizon 2020 research and innovation program: 953844.