Background: In PET/MRI, linear photon attenuation coefficients for attenuation correction (AC) cannot be directly derived, and cortical bone is, so far, usually not considered. This results in an underestimation of the average PET signal in PET/MRI. Recently introduced MR-AC methods predicting bone information from anatomic MRI or proton density weighted zero-time imaging may solve this problem in the future. However, there is an ongoing debate if the current error is acceptable for clinical use and/or research. Methods: We examined this feature for [18F] fluorodeoxyglucose (FDG) brain PET in 13 patients with clinical signs of dementia or movement disorders who subsequently underwent PET/CT and PET/MRI on the same day. Multiple MR-AC approaches including a CT-derived AC were applied. Results: The resulting PET data was compared to the CT-derived standard regarding the quantification error and its clinical impact. On a quantitative level, −11.9 to +2 % deviations from the CT-AC standard were found. These deviations, however, did not translate into a systematic diagnostic error. This, as overall patterns of hypometabolism (which are decisive for clinical diagnostics), remained largely unchanged. Conclusions: Despite a quantitative error by the omission of bone in MR-AC, clinical quality of brain [18F]FDG is not relevantly affected. Thus, brain [18F]FDG PET can already, even now with suboptimal MR-AC, be utilized for clinical routine purposes, even though the MR-AC warrants improvement.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa.de:bsz:15-qucosa-205215 |
Date | 20 June 2016 |
Creators | Werner, Peter, Rullmann, Michael, Bresch, Anke, Tiepolt, Solveig, Lobsien, Donald, Schröter, Matthias, Sabri, Osama, Barthel, Henryk |
Contributors | Universität Leipzig, Medizinische Fakultät, Universität Leipzig, Medizinische Fakultät, Max-Planck-Institut für Kognitions- und Neurowissenschaften, Abteilung Neurologie, Universität Leipzig, Medizinische Fakultät, Springer, |
Publisher | Universitätsbibliothek Leipzig |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | doc-type:article |
Format | application/pdf |
Source | EJNMMI research (2016)6:47 doi: 10.1186/s13550-016-0200-0 |
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