Abstract

BackgroundMisalignment between positron emission tomography (PET) and computed tomography (CT) data is known to generate artifactual defects in cardiac PET images due to imprecise attenuation correction (AC). In this work, the use of a maximum likelihood attenuation and activity (MLAA) algorithm is proposed to avoid such artifacts in time-of-flight (TOF) PET. MethodsMLAA was implemented and tested using a thorax/heart phantom and retrospectively on fourteen 13N-ammonia PET/CT perfusion studies. Global and local misalignments between PET and CT data were generated by shifting matched CT images or using CT data representative of the end-inspiration phase. PET images were reconstructed with MLAA and a 3D-ordered-subsets-expectation-maximization (OSEM)-TOF algorithm. Images obtained with 3D-OSEM-TOF and matched CT were used as references. These images were compared (qualitatively and semi-quantitatively) with those reconstructed with 3D-OSEM-TOF and MLAA for which a misaligned CT was used, respectively, for AC and initialization. ResultsPhantom experiment proved the capability of MLAA to converge toward the correct emission and attenuation distributions using, as input, only PET emission data, but convergence was very slow. Initializing MLAA with phantom CT images markedly improved convergence speed. In patient studies, when shifted or end-inspiration CT images were used for AC, 3D-OSEM-TOF reconstructions showed artifacts of increasing severity, size, and frequency with increasing mismatch. Such artifacts were absent in the corresponding MLAA images. ConclusionThe proposed implementation of the MLAA algorithm is a feasible and robust technique to avoid AC mismatch artifacts in cardiac PET studies provided that a CT of the source is available, even if poorly aligned.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call