2016
DOI: 10.1186/s13550-016-0200-0
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Impact of attenuation correction on clinical [18F]FDG brain PET in combined PET/MRI

Abstract: BackgroundIn 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.… Show more

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Cited by 14 publications
(17 citation statements)
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“…Furthermore, as observed by Mong et al, 28 we also found that PET uptake could help in accurate classification of suspicious ADC lesions. In the present study, we used an ultrashort TE sequence for MR imaging-based attenuation correction for brain PET, which is reported to result in accurate quantification of PET parameters, 29 more importantly offering comparable accuracy of CT-based attenuation correction.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, as observed by Mong et al, 28 we also found that PET uptake could help in accurate classification of suspicious ADC lesions. In the present study, we used an ultrashort TE sequence for MR imaging-based attenuation correction for brain PET, which is reported to result in accurate quantification of PET parameters, 29 more importantly offering comparable accuracy of CT-based attenuation correction.…”
Section: Discussionmentioning
confidence: 99%
“…Dies führte regelhaft zu einer Überschätzung des PET-Signals von 11-25 % in Schädelnähe, was als ernsthafter Kritikpunkt insbesondere bei quantitativen Messungen zu werten ist. Hinsicht-lich der klinischen Anwendung besteht noch keine eindeutige Einigkeit, ob diese Größenordnung des Messfehlers tolerabel ist [4, 59,67]. Mittlerweile existieren Schwächungskorrektur-Algorithmen der neuesten Generation, welche entweder aus einer Kombination verschiedener MR-Sequenzen sämtliche Gewebstypen und ihre Schwächungskoeffizienten prädizieren [35] und/ oder die individuelle Anatomie auf Hirn-Atlas-Datensätze überführen und so die Lage von knochen-und lufthaltigen Strukturen trennen [11,55].…”
Section: Hintergrund ▼unclassified
“…Der Fehler zwischen MRT-Schwächungskorrektur und CT-basierter Schwächungskorrektur ist dabei minimal (c oben). Diese Abbildung wurde im Original in EJNMMI Research veröffentlicht [67]. EJNMMI Research Res.…”
Section: Arbeitsablaufunclassified
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