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.
Original language | English (US) |
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Pages (from-to) | 1127-1136 |
Number of pages | 10 |
Journal | NMR in Biomedicine |
Volume | 23 |
Issue number | 10 |
DOIs | |
State | Published - Dec 2010 |
Keywords
- Multiple gradient-echo
- Noise bias
- Optimal B1-weighted image reconstruction
- Phase array coils
- R2* mapping
- Root sum-of-square
- Signal to noise ratios
- Truncation
ASJC Scopus subject areas
- Molecular Medicine
- Radiology Nuclear Medicine and imaging
- Spectroscopy