title: Optimized MLAA for quantitative non-TOF PET/MR of the brain.
abstract: For quantitative tracer distribution in positron emission tomography, attenuation correction is essential. In a hybrid PET/CT system the CT images serve as a basis for generation of the attenuation map, but in PET/MR, the MR images do not have a similarly simple relationship with the attenuation map. Hence attenuation correction in PET/MR systems is more challenging. Typically either of two MR sequences are used: the Dixon or the ultra-short time echo (UTE) techniques. However these sequences have some well-known limitations. In this study, a reconstruction technique based on a modified and optimized non-TOF MLAA is proposed for PET/MR brain imaging. The idea is to tune the parameters of the MLTR applying some information from an attenuation image computed from the UTE sequences and a T1w MR image. In this MLTR algorithm, an [Formula: see text] parameter is introduced and optimized in order to drive the algorithm to a final attenuation map most consistent with the emission data. Because the non-TOF MLAA is used, a technique to reduce the cross-talk effect is proposed. In this study, the proposed algorithm is compared to the common reconstruction methods such as OSEM using a CT attenuation map, considered as the reference, and OSEM using the Dixon and UTE attenuation maps. To show the robustness and the reproducibility of the proposed algorithm, a set of 204 [18F]FDG patients, 35 [11C]PiB patients and 1 [18F]FET patient are used. The results show that by choosing an optimized value of [Formula: see text] in MLTR, the proposed algorithm improves the results compared to the standard MR-based attenuation correction methods (i.e. OSEM using the Dixon or the UTE attenuation maps), and the cross-talk and the scale problem are limited.
authors.affiliation: Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Blegdamsvej 9, 2100, Copenhagen, Denmark.
authors.forename: Didier
authors.initials: D
authors.lastname: Benoit
authors.forename: Claes N
authors.initials: CN
authors.lastname: Ladefoged
authors.forename: Ahmadreza
authors.initials: A
authors.lastname: Rezaei
authors.forename: Sune H
authors.initials: SH
authors.lastname: Keller
authors.forename: Flemming L
authors.initials: FL
authors.lastname: Andersen
authors.forename: Liselotte
authors.initials: L
authors.lastname: Højgaard
authors.forename: Adam E
authors.initials: AE
authors.lastname: Hansen
authors.forename: Søren
authors.initials: S
authors.lastname: Holm
authors.forename: Johan
authors.initials: J
authors.lastname: Nuyts
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D064847:Multimodal Imaging; D049268:Positron-Emission Tomography; D015203:Reproducibility of Results; D013997:Time Factors
chemical_list: D019788:Fluorodeoxyglucose F18