title: Accelerated T2*-compensated fat fraction quantification using a joint parallel imaging and compressed sensing framework.
abstract: OBJECTIVE
  To develop a T2*-compensated parallel imaging and compressed sensing framework for water-fat separation, and to demonstrate accelerated quantitative imaging of proton density fat fraction.
  
  
  METHODS
  The proposed method extends a previously developed framework for water-fat separation by additionally compensating for T2* decay. A two-stage estimation was formulated that first determines an approximation of the B0 field map and then jointly estimates and refines the R2* (=1/T2*) and B0 field maps, respectively. The method was tested using a set of water-fat phantoms as well as liver datasets that were acquired from seven asymptomatic adult volunteers. The fat fraction estimates were compared to those from a commonly used nonaccelerated water-fat imaging method and also to a sequential parallel imaging and water-fat imaging method.
  
  
  RESULTS
  The proposed method properly compensated for T2* decay to yield accurate fat fraction estimates in the water-fat phantoms. Further, linear regression analysis from the liver datasets showed that the proposed method accurately estimated fat fraction at acceleration factors that were higher than those achievable by the sequential parallel imaging and water-fat imaging method. Accurate fat fraction estimates were demonstrated at acceleration factors up to 4×, although some image artifacts were observed.
  
  
  CONCLUSIONS
  The proposed T2*-compensated parallel imaging and compressed sensing framework demonstrates the potential to further accelerate water-fat imaging while maintaining accurate estimates of proton density fat fraction.
authors: Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA; Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California, USA.
authors: Samir D
authors: SD
authors: Sharma
authors: Houchun H
authors: HH
authors: Hu
authors: Krishna S
authors: KS
authors: Nayak
mesh_terms: D000273:Adipose Tissue / Q000033:anatomy & histology*; D000465:Algorithms; D044962:Data Compression / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000033:anatomy & histology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: accelerated imaging; chemical shift encoding; water-fat imaging
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