Brain PET Partial-Volume Compensation Using Blurred Anatomical Labels

Clinical use of positron emission tomography (PET) for brain imaging is limited by the partial-volume effect (PVE) induced by the limited spatial resolution of most scanners. Correction for this effect is usually performed using a post-reconstruction processing framework involving external information provided by an MRI acquisition. This approach has the major drawback of being very sensitive to the unavoidable MRI segmentation and PET MRI registration mismatches. Under the assumption that these effects are better compensated when they are modeled in the reconstruction process, we developed in this work a different approach based on the combined usage of a realistic system response function and of a Bayesian framework allowing the incorporation of the external information in the reconstruction process through the blurred anatomical labels method. PVE compensation performance of the proposed methodology was validated on a phantom double-isotope acquisition, in comparison with the classical post-reconstruction correction method of the Geometric Transfer Matrix (GTM). A Monte-Carlo simulation of a realistic brain L-Dopa acquisition allowed us to show the robustness of our method relative to the residual mismatches mentioned above.