title: Improved R2* measurement accuracy with absolute SNR truncation and optimal coil combination.
abstract: Accurate R2* measurements are critical for many abdominal imaging applications. Conventionally, R2* maps are derived via the monoexponential fitting of signal decay within a series of gradient-echo (GRE) images reconstructed from multichannel datasets combined using a root sum-of-squares (RSS) approach. However, the noise bias at low-SNR TEs from RSS-reconstructed data often causes the underestimation of R2* values. In phantom, ex vivo animal model and normal volunteer studies, we investigated the accuracy of low-SNR R2* measurement when combining truncation and coil combination methods. The accuracy for R2* estimations was shown to be affected by the intrinsic R2* value, SNR level and the chosen reconstruction method. The R2* estimation error was found to decrease with increasing SNR level, decreasing R2* value and the use of the optimal B1-weighted combined (OBC) image reconstruction method. Data truncation based on rigorous voxel-wise SNR estimates can reduce R2* measurement error in the setting of low SNR with fast signal decay. When optimal SNR truncation thresholds are unknown, the OBC method can provide optimal R2* measurements given the minimal truncation requirements.
authors.affiliation: Xiaoming Yin, Andrew C. Larson Department of Radiology, Northwestern University, Chicago, IL, USA.
authors.forename: Xiaoming
authors.initials: X
authors.lastname: Yin
authors.forename: Saurabh
authors.initials: S
authors.lastname: Shah
authors.forename: Aggelos K
authors.initials: AK
authors.lastname: Katsaggelos
authors.forename: Andrew C
authors.initials: AC
authors.lastname: Larson
mesh_terms: D000818:Animals; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019047:Phantoms, Imaging; D011817:Rabbits