DOI: 10.1007/s00259-016-3489-zPages: 398-407

On the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners

1. Massachusetts General Hospital and Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology

2. Massachusetts Institute of Technology, Division of Health Sciences and Technology

3. Massachusetts General Hospital, Department of Psychiatry

4. University of California, San Francisco, Department of Radiology and Biomedical Imaging

5. Harvard University, Program in Biophysics

Correspondence to:
Ciprian Catana
Tel: +1(617)643-4885
Email: ccatana@nmr.mgh.harvard.edu

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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.

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  • Accepted: Aug 7, 2016
  • Online: Aug 29, 2016

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