title: Analysis of the influence of 4D MR angiography temporal resolution on time-to-peak estimation error for different cerebral vessel structures.
abstract: OBJECTIVE
  Time-resolved MRA imaging is a promising technique for blood flow evaluation in case of cerebrovascular malformations. Unfortunately, 4D MRA imaging is a trade-off between spatial and temporal resolution. The aim of this study was to investigate the influence of temporal resolution on the error associated with TTP estimation from indicator dilution curves derived from different vascular structures.
  
  
  METHODS
  Monte Carlo simulation was performed to compute indicator dilution curves with known criterion standard TTP at temporal resolutions between 0.1 and 5 seconds. TTPs were estimated directly and by using 4 hemodynamic models for each curve and were compared with criterion standard TTP. Furthermore, clinical evaluation was performed by using 226 indicator dilution curves from different vessel structures obtained from clinical datasets. The temporal resolution was artificially decreased, and TTPs were estimated and compared with those obtained at the original temporal resolutions. The results of the clinical evaluations were further stratified for different vessel structures.
  
  
  RESULTS
  The results of both evaluations show that the TTP estimation error increases exponentially when one lowers the temporal resolution. TTP estimation by using hemodynamic model curves leads to lower estimation errors compared with direct estimation. A temporal resolution of 1.5 seconds for arteries and 2.5 seconds for venous and arteriovenous malformation vessel structures appears to be reasonable to achieve TTP estimations adequate for clinical application.
  
  
  CONCLUSIONS
  Different vessel structures require different temporal resolutions to enable comparable TTP estimation errors, which should be considered for achieving a case-optimal temporal and spatial resolution.
authors.affiliation: Departments of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. n.forkert@uke.uni-hamburg.de
authors.forename: N D
authors.initials: ND
authors.lastname: Forkert
authors.forename: T
authors.initials: T
authors.lastname: Illies
authors.forename: D
authors.initials: D
authors.lastname: Möller
authors.forename: H
authors.initials: H
authors.lastname: Handels
authors.forename: D
authors.initials: D
authors.lastname: Säring
authors.forename: J
authors.initials: J
authors.lastname: Fiehler
mesh_terms: D000465:Algorithms; D001783:Blood Flow Velocity; D002560:Cerebrovascular Circulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D002538:Intracranial Arteriovenous Malformations / Q000473:pathology* / Q000503:physiopathology*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity