On the Accuracy and Reproducibility of a Novel Probabilistic Atlas-based Generation for Calculation of Head Attenuation Maps in Integrated PET/MR Scanners - Chen, Kevin T. (Eur J Nucl Med Mol Imaging, 2016)
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 (AC) 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 (LAC) 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- 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 brain tumor patients 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 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 the MR data using a probabilistic atlas-based approach.