Functional assessment of the kidney from magnetic resonance and computed tomography renography: Impulse retention approach to a multicompartment model

Jeff L. Zhang, Henry Rusinek, Louisa Bokacheva, Lilach O. Lerman, Qun Chen, Chekema Prince, Niels Oesingmann, Ting Song, Vivian S. Lee

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

Abstract

A three-compartment model is proposed for analyzing magnetic resonance renography (MRR) and computed tomography renography (CTR) data to derive clinically useful parameters such as glomerular filtration rate (GFR) and renal plasma flow (RPF). The model fits the convolution of the measured input and the predefined impulse retention functions to the measured tissue curves. A MRR study of 10 patients showed that relative root mean square errors by the model were significantly lower than errors for a previously reported three-compartmental model (11.6% ± 4.9 vs 15.5% ± 4.1; P < 0.001). GFR estimates correlated well with reference values by 99mTc-DTPA scintigraphy (correlation coefficient r = 0.82), and for RPF, r = 0.80. Parameter-sensitivity analysis and Monte Carlo simulation indicated that model parameters could be reliably identified. When the model was applied to CTR in five pigs, expected increases in RPF and GFR due to acetylcholine were detected with greater consistency than with the previous model. These results support the reliability and validity of the new model in computing GFR, RPF, and renal mean transit times from MR and CT data.

Original languageEnglish (US)
Pages (from-to)278-288
Number of pages11
JournalMagnetic Resonance in Medicine
Volume59
Issue number2
DOIs
StatePublished - Feb 2008

Keywords

  • Computed tomography
  • Glomerular filtration rate
  • Impulse retention function
  • Magnetic resonance renography
  • Renal plasma flow

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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