Clinical Assessment of Emission- and Segmentation-Based MR-Guided Attenuation Correction in Whole-Body Time-of-Flight PET/MR Imaging

J Nucl Med. 2015 Jun;56(6):877-83. doi: 10.2967/jnumed.115.154807. Epub 2015 Apr 9.


The joint maximum-likelihood reconstruction of activity and attenuation (MLAA) for emission-based attenuation correction has regained attention since the advent of time-of-flight PET/MR imaging. Recently, we improved the performance of the MLAA algorithm using an MR imaging-constrained gaussian mixture model (GMM). In this study, we compare the performance of our proposed algorithm with standard 4-class MR-based attenuation correction (MRAC) implemented on commercial systems.

Methods: Five head and neck (18)F-FDG patients were scanned on PET/MR imaging and PET/CT scanners. Dixon fat and water MR images were registered to CT images. MRAC maps were derived by segmenting the MR images into 4 tissue classes and assigning predefined attenuation coefficients. For MLAA-GMM, MR images were segmented into known tissue classes, including fat, soft tissue, lung, background air, and an unknown MR low-intensity class encompassing cortical bones, air cavities, and metal artifacts. A coregistered bone probability map was also included in the unknown tissue class. Finally, the GMM prior was constrained over known tissue classes of attenuation maps using unimodal gaussians parameterized over a patient population.

Results: The results showed that the MLAA-GMM algorithm outperformed the MRAC method by differentiating bones from air gaps and providing more accurate patient-specific attenuation coefficients of soft tissue and lungs. It was found that the MRAC and MLAA-GMM methods resulted in average standardized uptake value errors of -5.4% and -3.5% in the lungs, -7.4% and -5.0% in soft tissues/lesions, and -18.4% and -10.2% in bones, respectively.

Conclusion: The proposed MLAA algorithm is promising for accurate derivation of attenuation maps on time-of-flight PET/MR systems.

Keywords: PET/MRI; attenuation correction; quantification; time-of-flight; whole-body imaging.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Body Mass Index
  • Fluorodeoxyglucose F18*
  • Head and Neck Neoplasms / diagnostic imaging*
  • Head and Neck Neoplasms / radiotherapy
  • Humans
  • Image Processing, Computer-Assisted*
  • Likelihood Functions
  • Magnetic Resonance Imaging*
  • Middle Aged
  • Models, Statistical
  • Multimodal Imaging
  • Normal Distribution
  • Positron-Emission Tomography*
  • Retrospective Studies
  • Tomography, X-Ray Computed
  • Whole Body Imaging


  • Fluorodeoxyglucose F18