title: Optimal acquisition and modeling parameters for accurate assessment of low Ktrans blood-brain barrier permeability using dynamic contrast-enhanced MRI.
abstract: OBJECTIVE
  To determine optimal parameters for acquisition and processing of dynamic contrast-enhanced MRI (DCE-MRI) to detect small changes in near normal low blood-brain barrier (BBB) permeability.
  
  
  METHODS
  Using a contrast-to-noise ratio metric (K-CNR) for Ktrans precision and accuracy, the effects of kinetic model selection, scan duration, temporal resolution, signal drift, and length of baseline on the estimation of low permeability values was evaluated with simulations.
  
  
  RESULTS
  The Patlak model was shown to give the highest K-CNR at low Ktrans . The Ktrans transition point, above which other models yielded superior results, was highly dependent on scan duration and tissue extravascular extracellular volume fraction (ve ). The highest K-CNR for low Ktrans was obtained when Patlak model analysis was combined with long scan times (10-30 min), modest temporal resolution (<60 s/image), and long baseline scans (1-4 min). Signal drift as low as 3% was shown to affect the accuracy of Ktrans estimation with Patlak analysis.
  
  
  CONCLUSIONS
  DCE acquisition and modeling parameters are interdependent and should be optimized together for the tissue being imaged. Appropriately optimized protocols can detect even the subtlest changes in BBB integrity and may be used to probe the earliest changes in neurodegenerative diseases such as Alzheimer's disease and multiple sclerosis.
authors.affiliation: Beckman Institute, Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA.
authors.forename: Samuel R
authors.initials: SR
authors.lastname: Barnes
authors.affiliation: Beckman Institute, Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA.|Department of Medicine, University of California, Irvine Medical Center, Orange, California, USA.
authors.forename: Thomas S C
authors.initials: TS
authors.lastname: Ng
authors.affiliation: Zilkha Neurogenetic Institute and Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
authors.forename: Axel
authors.initials: A
authors.lastname: Montagne
authors.affiliation: Division of Neuroradiology, Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
authors.forename: Meng
authors.initials: M
authors.lastname: Law
authors.affiliation: Zilkha Neurogenetic Institute and Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
authors.forename: Berislav V
authors.initials: BV
authors.lastname: Zlokovic
authors.affiliation: Beckman Institute, Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA.
authors.forename: Russell E
authors.initials: RE
authors.lastname: Jacobs
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000000981:diagnostic imaging; D001812:Blood-Brain Barrier; D003198:Computer Simulation; D003287:Contrast Media / Q000737:chemistry*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007700:Kinetics; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000000981:diagnostic imaging; D019636:Neurodegenerative Diseases / Q000000981:diagnostic imaging; D016011:Normal Distribution; D010539:Permeability; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
chemical_list: D003287:Contrast Media
keywords: DCE-MRI; Ktrans estimation; blood-brain barrier; parameter optimization; permeability