Improved R2* measurement accuracy with absolute SNR truncation and optimal coil combination

Xiaoming Yin, Saurabh Shah, Aggelos K. Katsaggelos, Andrew C. Larson*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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 languageEnglish (US)
Pages (from-to)1127-1136
Number of pages10
JournalNMR in Biomedicine
Volume23
Issue number10
DOIs
StatePublished - 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

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