title: Shape-based motion correction in dynamic contrast-enhanced MRI for quantitative assessment of renal function.
abstract: OBJECTIVE
  To incorporate a newly developed shape-based motion estimation scheme into magnetic resonance urography (MRU) and verify its efficacy in facilitating quantitative functional analysis.
  
  
  METHODS
  The authors propose a motion compensation scheme in MRU that consists of three sequential modules: MRU image acquisition, motion compensation, and quantitative functional analysis. They designed two sets of complementary experiments to evaluate the performance of the proposed method. In the first experiment, dynamic contrast enhanced (DCE) MR images were acquired from three sedated subjects, from which clinically valid estimates were derived and served as the "ground truth." Physiologically sound motion was then simulated to synthesize image sequences influenced by respiratory motion. Quantitative assessment and comparison were performed on functional estimates of Patlak number, glomerular filtration rate, and Patlak differential renal function without and with motion compensation against the ground truth. In the second experiment, the authors acquired a temporal series of noncontrast MR images under free breathing from a healthy adult subject. The performance of the proposed method on compensating real motion was evaluated by comparing the standard deviation of the obtained temporal intensity curves before and after motion compensation.
  
  
  RESULTS
  On DCE-MR images with simulated motion, the generated relative enhancement curves exhibited large perturbations and the Patlak numbers of the left and right kidney were significantly underestimated up to 35% and 34%, respectively, compared with the ground truth. After motion compensation, the relative enhancement curves exhibited much less perturbations and Patlak estimation errors reduced within 3% and 4% for the left and right kidneys, respectively. On clinical free-breathing MR images, the temporal intensity curves exhibited significantly reduced variations after motion compensation, with standard deviation decreased from 30.3 and 38.2 to 8.3 and 11.7 within two manually selected regions of interest, respectively.
  
  
  CONCLUSIONS
  The developed motion compensation method has demonstrated its ability to facilitate quantitative MRU functional analysis, with improved accuracy of pharmacokinetic modeling and quantitative parameter estimations. Future work will consider performing more intensive clinical verifications with sophisticated pharmacokinetic models and generalizing the proposed method to other quantitative DCE analysis, such as on liver or prostate function.
authors.affiliation: Department of Bioengineering, University of California, Los Angeles 90095.
authors.forename: Wenyang
authors.initials: W
authors.lastname: Liu
authors.affiliation: Department of Bioengineering, University of California, Los Angeles 90095 and Department of Radiological Sciences, University of California, Los Angeles 90095.
authors.forename: Kyunghyun
authors.initials: K
authors.lastname: Sung
authors.affiliation: Department of Bioengineering, University of California, Los Angeles 90095 and Department of Radiation Oncology, University of California, Los Angeles 90095.
authors.forename: Dan
authors.initials: D
authors.lastname: Ruan
mesh_terms: D000328:Adult; D055592:Biophysical Phenomena; D003287:Contrast Media; D019786:Gadolinium DTPA; D005919:Glomerular Filtration Rate; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007668:Kidney / Q000033:anatomy & histology / Q000502:physiology; D007677:Kidney Function Tests / Q000379:methods* / Q000706:statistics & numerical data; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male; D009038:Motion
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA