title: Quantitative estimation of renal function with dynamic contrast-enhanced MRI using a modified two-compartment model.
abstract: OBJECTIVE
  To establish a simple two-compartment model for glomerular filtration rate (GFR) and renal plasma flow (RPF) estimations by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).
  
  
  METHODS
  A total of eight New Zealand white rabbits were included in DCE-MRI. The two-compartment model was modified with the impulse residue function in this study. First, the reliability of GFR measurement of the proposed model was compared with other published models in Monte Carlo simulation at different noise levels. Then, functional parameters were estimated in six healthy rabbits to test the feasibility of the new model. Moreover, in order to investigate its validity of GFR estimation, two rabbits underwent acute ischemia surgical procedure in unilateral kidney before DCE-MRI, and pixel-wise measurements were implemented to detect the cortical GFR alterations between normal and abnormal kidneys.
  
  
  RESULTS
  The lowest variability of GFR and RPF measurements were found in the proposed model in the comparison. Mean GFR was 3.03±1.1 ml/min and mean RPF was 2.64±0.5 ml/g/min in normal animals, which were in good agreement with the published values. Moreover, large GFR decline was found in dysfunction kidneys comparing to the contralateral control group.
  
  
  CONCLUSIONS
  Results in our study demonstrate that measurement of renal kinetic parameters based on the proposed model is feasible and it has the ability to discriminate GFR changes in healthy and diseased kidneys.
authors.affiliation: Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Chen
authors.affiliation: Department of Radiology, Peking University First Hospital, Beijing, China.
authors.forename: Yudong
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; Department of Electrical Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China.
authors.forename: Xiaojian
authors.initials: X
authors.lastname: Song
authors.affiliation: Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; Department of Radiology, Peking University First Hospital, Beijing, China.
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Wang
authors.affiliation: Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; College of Engineering, Peking University, Beijing, China.
authors.forename: Jue
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; College of Engineering, Peking University, Beijing, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Fang
mesh_terms: D000818:Animals; D003287:Contrast Media / Q000008:administration & dosage*; D005919:Glomerular Filtration Rate / Q000502:physiology*; D007089:Image Enhancement / Q000379:methods*; D007668:Kidney / Q000502:physiology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D011817:Rabbits; D012079:Renal Circulation / Q000502:physiology*; D015203:Reproducibility of Results
chemical_list: D003287:Contrast Media