L Presotto1,2, E Busnardo3, D Perani4,5,3, L Gianolli3, M C Gilardi6, V Bettinardi3. 1. Università Vita-Salute San Raffaele, Milan, Italy. presotto.luca@hsr.it. 2. In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS, San Raffaele Scientific Institute, Milan, Italy. presotto.luca@hsr.it. 3. Nuclear Medicine Department, IRCCS, San Raffaele Scientific Institute, Milan, Italy. 4. Università Vita-Salute San Raffaele, Milan, Italy. 5. In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS, San Raffaele Scientific Institute, Milan, Italy. 6. IBFM-CNR, Institute for Molecular Bioimaging and Physiology, Segrate, Italy.
Abstract
BACKGROUND: Misalignment 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. METHODS: MLAA was implemented and tested using a thorax/heart phantom and retrospectively on fourteen (13)N-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. RESULTS: Phantom 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. CONCLUSION: The 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.
BACKGROUND: Misalignment 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. METHODS:MLAA was implemented and tested using a thorax/heart phantom and retrospectively on fourteen (13)N-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. RESULTS: Phantom 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. CONCLUSION: The 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.
Entities:
Keywords:
Image artifacts; PET imaging; attenuation and scatter correction; image reconstruction; myocardial perfusion imaging: PET
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