title: Increased robustness in reference region model analysis of DCE MRI using two-step constrained approaches.
abstract: Reference region models (RRMs) can quantify tumor perfusion in dynamic contrast-enhanced MRI without an arterial input function. Inspection of the RRM reveals that one of the free parameters in the fit is uniquely linked to the reference region and is common to all voxels. A two-step approach is proposed that takes this constraint into account.
  
  
  
  Three constrained RRM (CRRM) approaches were devised and evaluated. Simulations were performed to compare their accuracy and precision over a range of noise and temporal resolutions. The CRRM was also applied on a virtual phantom that simulates different perfusion values. In vivo evaluation was performed on data from breast cancer and soft tissue sarcoma.
  
  
  
  In simulations, the CRRM consistently improved precision and had better accuracy at low signal-to-noise ratio (SNR). In virtual phantom, the CRRMs were able to fit voxels that had similar kinetics to the reference tissue, whereas the unconstrained models failed to accurately fit these voxels. In the in vivo data, the constrained approaches produced parameter maps that had less variability and were in better agreement with the Tofts model.
  
  
  
  These findings indicate that the two-step fitting approach of the CRRM can reduce the variability of perfusion estimates for quantifying perfusion with dynamic contrast-enhanced (DCE) MRI. Magn Reson Med 78:1547-1557, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
authors: Medical Physics Unit, McGill University, Montreal, QC, Canada.
authors: Zaki
authors: 0000-0001-5648-0590
authors: Z
authors: Ahmed
authors: Medical Physics Unit, McGill University, Montreal, QC, Canada.|Research Institute of the McGill University Health Centre, Montreal, QC, Canada.
authors: Ives R
authors: IR
authors: Levesque
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging / Q000378:metabolism; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007700:Kinetics; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D057054:Molecular Imaging; D019047:Phantoms, Imaging; D012509:Sarcoma / Q000000981:diagnostic imaging / Q000378:metabolism; D059629:Signal-To-Noise Ratio
keywords: cancer; dynamic contrast enhanced (DCE) MRI; perfusion; pharmacokinetics; reference region model; tracer kinetic modeling