title: A comparative simulation study of bayesian fitting approaches to intravoxel incoherent motion modeling in diffusion-weighted MRI.
abstract: OBJECTIVE
  To assess the performance of various least squares and Bayesian modeling approaches to parameter estimation in intravoxel incoherent motion (IVIM) modeling of diffusion-weighted MRI data.
  
  
  METHODS
  Simulated tissue models of different type (breast/liver) and morphology (discrete/continuous) were used to generate noisy data according to the IVIM model at several signal-to-noise ratios. IVIM parameter maps were generated using six different approaches, including full nonlinear least squares (LSQ), segmented least squares (SEG), Bayesian modeling with a Gaussian shrinkage prior (BSP) and Bayesian modeling with a spatial homogeneity prior (FBM), plus two modified approaches. Estimators were compared by calculating the median absolute percentage error and deviation, and median percentage bias.
  
  
  RESULTS
  The Bayesian modeling approaches consistently outperformed the least squares approaches, with lower relative error and deviation, and provided cleaner parameter maps with reduced erroneous heterogeneity. However, a weakness of the Bayesian approaches was exposed, whereby certain tissue features disappeared completely in regions of high parameter uncertainty. Lower error and deviation were generally afforded by FBM compared with BSP, at the cost of higher bias.
  
  
  CONCLUSIONS
  Bayesian modeling is capable of producing more visually pleasing IVIM parameter maps than least squares approaches, but their potential to mask certain tissue features demands caution during implementation. Magn Reson Med 78:2373-2387, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
authors.affiliation: Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway.
authors.forename: Peter T
authors.initials: PT
authors.lastname: While
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001499:Bayes Theorem; D001940:Breast / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D006801:Humans; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted; D016018:Least-Squares Analysis; D008099:Liver / Q000000981:diagnostic imaging*; D008297:Male; D009038:Motion; D016011:Normal Distribution; D015203:Reproducibility of Results; D059629:Signal-To-Noise Ratio
keywords: Bayesian analysis; diffusion MRI; estimation techniques; intravoxel incoherent motion; least squares