title: A multicomponent T2 relaxometry algorithm for myelin water imaging of the brain.
abstract: OBJECTIVE
  Models based on a sum of damped exponentials occur in many applications, particularly in multicomponent T2 relaxometry. The problem of estimating the relaxation parameters and the corresponding amplitudes is known to be difficult, especially as the number of components increases. In this article, the commonly used non-negative least squares spectrum approach is compared to a recently published estimation algorithm abbreviated as Exponential Analysis via System Identification using Steiglitz-McBride.
  
  
  METHODS
  The two algorithms are evaluated via simulation, and their performance is compared to a statistical benchmark on precision given by the Cramér-Rao bound. By applying the algorithms to an in vivo brain multi-echo spin-echo dataset, containing 32 images, estimates of the myelin water fraction are computed.
  
  
  RESULTS
  Exponential Analysis via System Identification using Steiglitz-McBride is shown to have superior performance when applied to simulated T2 relaxation data. For the in vivo brain, Exponential Analysis via System Identification using Steiglitz-McBride gives an myelin water fraction map with a more concentrated distribution of myelin water and less noise, compared to non-negative least squares.
  
  
  CONCLUSIONS
  The Exponential Analysis via System Identification using Steiglitz-McBride algorithm provides an efficient and user-parameter-free alternative to non-negative least squares for estimating the parameters of multiple relaxation components and gives a new way of estimating the spatial variations of myelin in the brain.
authors.affiliation: Department of Information Technology, Uppsala University, Uppsala, Sweden.
authors.forename: Marcus
authors.initials: M
authors.lastname: Björk
authors.affiliation: Department of Information Technology, Uppsala University, Uppsala, Sweden.
authors.forename: Dave
authors.initials: D
authors.lastname: Zachariah
authors.affiliation: Department of Radiology, Uppsala University, Uppsala, Sweden.
authors.forename: Joel
authors.initials: J
authors.lastname: Kullberg
authors.affiliation: Department of Information Technology, Uppsala University, Uppsala, Sweden.
authors.forename: Petre
authors.initials: P
authors.lastname: Stoica
mesh_terms: D000328:Adult; D000465:Algorithms; D001834:Body Water / Q000378:metabolism*; D001921:Brain / Q000378:metabolism* / Q000648:ultrastructure; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009186:Myelin Sheath / Q000378:metabolism* / Q000648:ultrastructure; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: estimation algorithm; in vivo brain; multicomponent T2 relaxometry; myelin water fraction