title: Myocardial T2* mapping: influence of noise on accuracy and precision.
abstract: BACKGROUND
  Pixel-wise, parametric T2* mapping is emerging as a means of automatic measurement of iron content in tissues. It enables quick, intuitive interpretation and provides the potential benefit of spatial context between tissues. However, pixel-wise mapping uses much lower SNR data to estimate T2* when compared to region-based mapping thereby decreasing both its accuracy and precision. In this study, the effects that noise has on the precision and accuracy of pixel-wise T2* mapping were investigated and techniques to mitigate those effects are proposed.
  
  
  METHODS
  To study precision across T2* mapping techniques, a pipeline to estimate the pixel-wise standard deviation (SD) of the T2* based on the fit residuals is proposed. For validation, a Monte-Carlo analysis was performed in which T2* phantoms were scanned N = 64 times, the true SD was measured and compared to the estimated SD. To improve accuracy and precision, the automatic truncation method for mitigating noise bias was extended to pixel-wise fitting by using an SNR scaled image reconstruction and truncating low SNR measurements. Finally, the precision and accuracy of non-linear regression with and without automatic truncation, were investigated using Monte-Carlo simulations.
  
  
  RESULTS
  Measured and estimated SD's were >99.9% correlated for non-linear regression with and without truncation. Non-linear regression with automatic truncation was shown to be the best mapping technique for improving accuracy and precision in low T2* and low SNR measurements.
  
  
  CONCLUSIONS
  A method for applying an automatic truncation method to pixel-wise T2* mapping that reduces T2* overestimation due to noise bias was proposed. A formulation for estimating pixel-wise standard deviation (SD) maps for T2* that can serve as a quality map for interpreting images and for comparison of imaging protocols was also proposed and validated.
authors: Christopher M
authors: CM
authors: Sandino
authors: Peter
authors: P
authors: Kellman
authors: Andrew E
authors: AE
authors: Arai
authors: Michael S
authors: MS
authors: Hansen
authors: National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, 10 Center Drive MSC-1061, Bethesda 20892, MD, USA. hui.xue@nih.gov.
authors: Hui
authors: H
authors: Xue
mesh_terms: D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008955:Models, Cardiovascular; D009010:Monte Carlo Method; D009206:Myocardium / Q000473:pathology*; D019047:Phantoms, Imaging; D059629:Signal-To-Noise Ratio
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