Literature DB >> 27200499

Optimization of saturation-recovery dynamic contrast-enhanced MRI acquisition protocol: monte carlo simulation approach demonstrated with gadolinium MR renography.

Jeff L Zhang1, Chris C Conlin1, Kristi Carlston1, Luke Xie1, Daniel Kim1, Glen Morrell1, Kathryn Morton1, Vivian S Lee1.   

Abstract

Dynamic contrast-enhanced (DCE) MRI is widely used for the measurement of tissue perfusion and to assess organ function. MR renography, which is acquired using a DCE sequence, can measure renal perfusion, filtration and concentrating ability. Optimization of the DCE acquisition protocol is important for the minimization of the error propagation from the acquired signals to the estimated parameters, thus improving the precision of the parameters. Critical to the optimization of contrast-enhanced T1 -weighted protocols is the balance of the T1 -shortening effect across the range of gadolinium (Gd) contrast concentration in the tissue of interest. In this study, we demonstrate a Monte Carlo simulation approach for the optimization of DCE MRI, in which a saturation-recovery T1 -weighted gradient echo sequence is simulated and the impact of injected dose (D) and time delay (TD, for saturation recovery) is tested. The results show that high D and/or high TD cause saturation of the peak arterial signals and lead to an overestimation of renal plasma flow (RPF) and glomerular filtration rate (GFR). However, the use of low TD (e.g. 100 ms) and low D leads to similar errors in RPF and GFR, because of the Rician bias in the pre-contrast arterial signals. Our patient study including 22 human subjects compared TD values of 100 and 300 ms after the injection of 4 mL of Gd contrast for MR renography. At TD = 100 ms, we computed an RPF value of 157.2 ± 51.7 mL/min and a GFR of 33.3 ± 11.6 mL/min. These results were all significantly higher than the parameter estimates at TD = 300 ms: RPF = 143.4 ± 48.8 mL/min (p = 0.0006) and GFR = 30.2 ± 11.5 mL/min (p = 0.0015). In conclusion, appropriate optimization of the DCE MRI protocol using simulation can effectively improve the precision and, potentially, the accuracy of the measured parameters.
Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Entities:  

Keywords:  MR renography; dynamic contrast-enhanced imaging; glomerular filtration rate; renal plasma flow; tracer kinetic modeling

Mesh:

Substances:

Year:  2016        PMID: 27200499      PMCID: PMC5206992          DOI: 10.1002/nbm.3553

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  36 in total

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2.  Determining the longitudinal relaxation time (T1) of blood at 3.0 Tesla.

Authors:  Hanzhang Lu; Chekesha Clingman; Xavier Golay; Peter C M van Zijl
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3.  Renal function measurements from MR renography and a simplified multicompartmental model.

Authors:  Vivian S Lee; Henry Rusinek; Louisa Bokacheva; Ambrose J Huang; Niels Oesingmann; Qun Chen; Manmeen Kaur; Keyma Prince; Ting Song; Elissa L Kramer; Edward F Leonard
Journal:  Am J Physiol Renal Physiol       Date:  2007-01-09

4.  Gadolinium--a specific trigger for the development of nephrogenic fibrosing dermopathy and nephrogenic systemic fibrosis?

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Journal:  Nephrol Dial Transplant       Date:  2006-01-23       Impact factor: 5.992

5.  Quantification of cerebral blood flow, cerebral blood volume, and blood-brain-barrier leakage with DCE-MRI.

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Journal:  Magn Reson Med       Date:  2009-07       Impact factor: 4.668

6.  Performance of an efficient image-registration algorithm in processing MR renography data.

Authors:  Christopher C Conlin; Jeff L Zhang; Florian Rousset; Clement Vachet; Yangyang Zhao; Kathryn A Morton; Kristi Carlston; Guido Gerig; Vivian S Lee
Journal:  J Magn Reson Imaging       Date:  2015-07-14       Impact factor: 4.813

Review 7.  Modeling tracer kinetics in dynamic Gd-DTPA MR imaging.

Authors:  P S Tofts
Journal:  J Magn Reson Imaging       Date:  1997 Jan-Feb       Impact factor: 4.813

8.  Optimizing functional parameter accuracy for breath-hold DCE-MRI of liver tumours.

Authors:  Matthew R Orton; Keiko Miyazaki; Dow-Mu Koh; David J Collins; David J Hawkes; David Atkinson; Martin O Leach
Journal:  Phys Med Biol       Date:  2009-03-17       Impact factor: 3.609

9.  MRI-measurement of perfusion and glomerular filtration in the human kidney with a separable compartment model.

Authors:  Steven P Sourbron; Henrik J Michaely; Maximilian F Reiser; Stefan O Schoenberg
Journal:  Invest Radiol       Date:  2008-01       Impact factor: 6.016

Review 10.  DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents.

Authors:  J P B O'Connor; A Jackson; G J M Parker; G C Jayson
Journal:  Br J Cancer       Date:  2007-01-09       Impact factor: 7.640

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1.  Exercise-induced calf muscle hyperemia: quantitative mapping with low-dose dynamic contrast enhanced magnetic resonance imaging.

Authors:  Jeff L Zhang; Gwenael Layec; Christopher Hanrahan; Christopher C Conlin; Corey Hart; Nan Hu; Lillian Khor; Michelle Mueller; Vivian S Lee
Journal:  Am J Physiol Heart Circ Physiol       Date:  2018-11-02       Impact factor: 4.733

2.  Value of Magnetic Resonance Urography Versus Computerized Tomography Urography (CTU) in Evaluation of Obstructive Uropathy: An Observational Study.

Authors:  Saeed M Bafaraj
Journal:  Curr Med Imaging Rev       Date:  2018-02
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