On the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners
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Author(s)
Chen, Kevin T.
Izquierdo-Garcia, David
Poynton, Clare B.
Chonde, Daniel B.
Catana, Ciprian
Date Issued
August 2016
Journal
European Journal of Nuclear Medicine and Molecular Imaging
Publisher
Springer Berlin Heidelberg
Citation
Chen, Kevin T., David Izquierdo-Garcia, Clare B. Poynton, Daniel B. Chonde, and Ciprian Catana. “On the Accuracy and Reproducibility of a Novel Probabilistic Atlas-Based Generation for Calculation of Head Attenuation Maps on Integrated PET/MR Scanners.” European Journal of Nuclear Medicine and Molecular Imaging 44, no. 3 (August 29, 2016): 398–407.
Version
Author's final manuscript
Abstract
Purpose
To propose an MR-based method for generating continuous-valued head attenuation maps and to assess its accuracy and reproducibility. Demonstrating that novel MR-based photon attenuation correction methods are both accurate and reproducible is essential prior to using them routinely in research and clinical studies on integrated PET/MR scanners.
Methods
Continuous-valued linear attenuation coefficient maps (“μ-maps”) were generated by combining atlases that provided the prior probability of voxel positions belonging to a certain tissue class (air, soft tissue, or bone) and an MR intensity-based likelihood classifier to produce posterior probability maps of tissue classes. These probabilities were used as weights to generate the μ-maps. The accuracy of this probabilistic atlas-based continuous-valued μ-map (“PAC-map”) generation method was assessed by calculating the voxel-wise absolute relative change (RC) between the MR-based and scaled CT-based attenuation-corrected PET images. To assess reproducibility, we performed pair-wise comparisons of the RC values obtained from the PET images reconstructed using the μ-maps generated from the data acquired at three time points.
Results
The proposed method produced continuous-valued μ-maps that qualitatively reflected the variable anatomy in patients with brain tumor and agreed well with the scaled CT-based μ-maps. The absolute RC comparing the resulting PET volumes was 1.76 ± 2.33 %, quantitatively demonstrating that the method is accurate. Additionally, we also showed that the method is highly reproducible, the mean RC value for the PET images reconstructed using the μ-maps obtained at the three visits being 0.65 ± 0.95 %.
Conclusion
Accurate and highly reproducible continuous-valued head μ-maps can be generated from MR data using a probabilistic atlas-based approach.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/s00259-016-3489-z
