title: Perfusion quantification by model-free arterial spin labeling using nonlinear stochastic regularization deconvolution.
abstract: OBJECTIVE
  Quantification of cerebral blood flow can be accomplished by model-free arterial spin labeling using the quantitative STAR labeling of arterial regions (QUASAR) sequence. The required deconvolution is normally based on block-circulant singular value decomposition (cSVD)/oscillation SVD (oSVD), an algorithm associated with nonphysiological residue functions and potential effects of arterial dispersion. The aim of this work was to amend this by implementing nonlinear stochastic regularization (NSR) deconvolution, previously used to retrieve realistic residue functions in dynamic susceptibility contrast MRI.
  
  
  METHODS
  To characterize the residue function in model-free arterial spin labeling, and possibly to improve absolute cerebral blood flow quantification, NSR was applied to deconvolution of QUASAR data. For comparison, SVD-based deconvolution was also employed. Residue function characteristics and cerebral blood flow values from 10 volunteers were obtained. Simulations were performed to support the in vivo results.
  
  
  RESULTS
  NSR was able to resolve realistic residue functions in contrast to the SVD-based methods. Mean cerebral blood flow estimates in gray matter were 36.6 ± 2.6, 28.6 ± 3.3, 40.9 ± 3.6, and 42.9 ± 3.9 mL/100 g/min for cSVD, oSVD, NSR, and NSR with correction for arterial dispersion, respectively. In simulations, the NSR-based perfusion estimates showed better accuracy than the SVD-based approaches.
  
  
  CONCLUSIONS
  Perfusion quantification by model-free arterial spin labeling is evidently dependent on the selected deconvolution method, and NSR is a feasible alternative to SVD-based methods.
authors.affiliation: Department of Medical Radiation Physics, Lund University, Lund, Sweden.
authors.forename: André
authors.initials: A
authors.lastname: Ahlgren
authors.forename: Ronnie
authors.initials: R
authors.lastname: Wirestam
authors.forename: Esben Thade
authors.initials: ET
authors.lastname: Petersen
authors.forename: Freddy
authors.initials: F
authors.lastname: Ståhlberg
authors.forename: Linda
authors.initials: L
authors.lastname: Knutsson
mesh_terms: D000328:Adult; D000368:Aged; D001783:Blood Flow Velocity / Q000502:physiology; D001921:Brain / Q000502:physiology*; D002536:Cerebral Arteries / Q000502:physiology*; D002560:Cerebrovascular Circulation / Q000502:physiology*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013113:Spin Labels; D013269:Stochastic Processes; D055815:Young Adult
chemical_list: D013113:Spin Labels
keywords: arterial spin labeling; cerebral blood flow; deconvolution