Volume 2 Supplement 1

Proceedings of the 4th PSMR Conference on PET/MR and SPECT/MR

Open Access

PET/MR attenuation correction in brain imaging using a continuous bone signal derived from UTE

  • Claes Ladefoged1,
  • Didier Benoit1,
  • Ian Law1,
  • Soren Holm1,
  • Liselotte Hojgaard1,
  • Adam Espe Hansen1 and
  • Flemming Littrup Andersen1
EJNMMI Physics20152(Suppl 1):A39

https://doi.org/10.1186/2197-7364-2-S1-A39

Published: 18 May 2015

In the absence of transmission sources in combined clinical PET/MR systems, MR images are used for MR-based attenuation correction (MRAC). The main challenge in MR-AC is to separate the bone and air, as neither have a signal in the MR images. In the attenuation maps supplied by the vendor, a single value is assigned to bone using an ultra-short echo time (UTE) MR sequence. The purpose of this study was to develop a new multi-class segmentation-based MR-AC method, employing Continuous-Bone-using-R2* (MRAC_CBuR2*), and evaluate it on a large patient cohort. 53 [18F]-FDG PET/MR brain patients were included in this study. MRAC was based on an aligned CT (MRAC_CT, used as reference), standard MRAC_UTE and MRAC_CBuR2*. Our method segments the air, brain, CSF and soft tissue voxels on the UTE images, and uses a mapping of R2* values to HU to measure the density in bone voxels. Aligned anatomical masks are used to improve accuracy in noisy regions. Region-based analysis was performed using ICBM 2009a brain atlas with anatomical labels pre-defined. Using CBuR2*, 82% of the voxels in the brain are within ±5% of PET_CT, compared to 27% when using UTE. Using our method, there are clear improvements over UTE. The average error over the full brain is 0.8% (±1.7%), compared to -7.1% (±2.4%) in UTE. Of note, the maximum error in the cerebellum is -15% and 7% in UTE and CBuR2*, respectively. The proposed method uses the available UTE images to segment tissue classes, and uses the R2* map to measure a continuous bone signal. The improvement over the vendor provided UTE reduces both the global and local error on the reconstructed PET images.

Authors’ Affiliations

(1)
Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet Copenhagen

Copyright

© Ladefoged et al; licensee Springer. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.