Literature DB >> 24425423

A comparison of CT- and MR-based attenuation correction in neurological PET.

John C Dickson1, Celia O'Meara, Anna Barnes.   

Abstract

PURPOSE: To assess the quantitative accuracy of current MR attenuation correction (AC) methods in neurological PET, in comparison to data derived using CT AC.
METHODS: This retrospective study included 25 patients who were referred for a neurological FDG PET examination and were imaged sequentially by PET/CT and simultaneous PET/MR. Differences between activity concentrations derived using Dixon and ultrashort echo time (UTE) MR-based AC and those derived from CT AC were compared using volume of interest and voxel-based approaches. The same comparisons were also made using PET data represented as SUV ratios (SUVr) using grey matter cerebellum as the reference region.
RESULTS: Extensive and statistically significant regional underestimations of activity concentrations were found with both Dixon AC (P < 0.001) and UTE AC (P < 0.001) in all brain regions when compared to CT AC. The greatest differences were found in the cortical grey matter (Dixon AC 21.3%, UTE AC 15.7%) and cerebellum (Dixon AC 19.8%, UTE AC 17.3%). The underestimation using UTE AC was significantly less than with Dixon AC (P < 0.001) in most regions. Voxel-based comparisons showed that all cortical grey matter and cerebellum uptake was underestimated with Dixon AC compared to CT AC. Using UTE AC the extent and significance of these differences were reduced. Inaccuracies in cerebellar activity concentrations led to a mixture of predominantly cortical underestimation and subcortical overestimation in SUVr PET data for both MR AC methodologies.
CONCLUSION: MR-based AC results in significant underestimation of activity concentrations throughout the brain, which makes the use of SUVr data difficult. These effects limit the quantitative accuracy of neurological PET/MR.

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Year:  2014        PMID: 24425423     DOI: 10.1007/s00259-013-2652-z

Source DB:  PubMed          Journal:  Eur J Nucl Med Mol Imaging        ISSN: 1619-7070            Impact factor:   9.236


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