title: Semi-quantitative parameter analysis of DCE-MRI revisited: monte-carlo simulation, clinical comparisons, and clinical validation of measurement errors in patients with type 2 neurofibromatosis.
abstract: OBJECTIVE
  To compare semi-quantitative (SQ) and pharmacokinetic (PK) parameters for analysis of dynamic contrast enhanced MR data (DCE-MRI) and investigate error-propagation in SQ parameters.
  
  
  METHODS
  Clinical data was collected from five patients with type 2-neurofibromatosis (NF2) receiving anti-angiogenic therapy for rapidly growing vestibular schwannoma (VS). There were 7 VS and 5 meningiomas. Patients were scanned prior to therapy and at days 3 and 90 of treatment. Data was collected using a dual injection technique to permit direct comparison of SQ and PK parameters. Monte Carlo modeling was performed to assess potential measurement errors in SQ parameters in persistent, washout, and weakly enhancing tissues. The simulation predictions for five semi-quantitative parameters were tested using the clinical DCE-MRI data.
  
  
  RESULTS
  In VS, SQ parameters and Ktrans showed close correlation and demonstrated similar therapy induced reductions. In meningioma, only the denoised Signal Enhancement Ratio (Rse1/se2(DN)) showed a significant therapy induced reduction (p<0.05). Simulation demonstrated: 1) Precision of SQ metrics normalized to the pre-contrast-baseline values (MSErel and ∑MSErel) is improved by use of an averaged value from multiple baseline scans; 2) signal enhancement ratio Rmse1/mse2 shows considerable susceptibility to noise; 3) removal of outlier values to produce a new parameter, Rmse1/mse2(DN), improves precision and sensitivity to therapy induced changes. Direct comparison of in-vivo analysis with Monte Carlo simulation supported the simulation predicted error distributions of semi-quantitative metrics.
  
  
  CONCLUSIONS
  PK and SQ parameters showed similar sensitivity to anti-angiogenic therapy induced changes in VS. Modeling studies confirmed the benefits of averaging baseline signal from multiple images for normalized SQ metrics and demonstrated poor noise tolerance in the widely used signal enhancement ratio, which is corrected by removal of outlier values.
authors.affiliation: Wolfson Molecular Imaging Centre, The University of Manchester, Manchester, United Kingdom.
authors.forename: Alan
authors.initials: A
authors.lastname: Jackson
authors.affiliation: Wolfson Molecular Imaging Centre, The University of Manchester, Manchester, United Kingdom.
authors.forename: Ka-Loh
authors.initials: KL
authors.lastname: Li
authors.affiliation: Wolfson Molecular Imaging Centre, The University of Manchester, Manchester, United Kingdom.
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Zhu
mesh_terms: D003198:Computer Simulation; D003287:Contrast Media; D006801:Humans; D007700:Kinetics; D008279:Magnetic Resonance Imaging; D009010:Monte Carlo Method; D016518:Neurofibromatosis 2 / Q000175:diagnosis*; D015203:Reproducibility of Results; D018709:Statistics, Nonparametric
chemical_list: D003287:Contrast Media