Multiresolution imaging using golden angle stack-of-stars and compressed sensing for dynamic MR urography.
To develop a novel multiresolution MRI methodology for accurate estimation of glomerular filtration rate (GFR) in vivo.



A three-dimensional golden-angle radial stack-of-stars (SoS) trajectory was used for data acquisition on a 3 Tesla MRI scanner. Multiresolution reconstruction and analysis was performed using arterial input function reconstructed at 1-s. temporal resolution and renal dynamic data reconstructed using compressed sensing (CS) with 4-s temporal resolution. The method was first validated using simulations and the clinical utility of the technique was evaluated by comparing the GFR estimates from the proposed method to the estimated GFR (eGFR) obtained from serum creatinine for 10 subjects.



The 4-s temporal resolution CS images minimized streaking artifacts and noise while the 1-s temporal resolution AIF minimized errors in GFR estimates. A paired t-test showed that there was no statistically significant difference between MRI based total GFR values and serum creatinine based eGFR estimates (P = 0.92).



We have demonstrated the feasibility of multiresolution MRI using a golden angle radial stack-of-stars scheme to accurately estimate GFR as well as produce diagnostic quality dynamic images in vivo.



1 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:303-311.
Electrical & Computer Engineering, University of Arizona, Tucson, Arizona, USA.|Medical Imaging, University of Arizona, Tucson, Arizona, USA.
Abhishek
A
Pandey
Radiology, Stanford University, Stanford, California, USA.
Umit
U
Yoruk
Electrical & Computer Engineering, University of Arizona, Tucson, Arizona, USA.|Medical Imaging, University of Arizona, Tucson, Arizona, USA.
Mahesh
M
Keerthivasan
Medical Imaging, University of Arizona, Tucson, Arizona, USA.
Jean-Philippe
JP
Galons
Medical Imaging, University of Arizona, Tucson, Arizona, USA.
Puneet
P
Sharma
Siemens Medical Solution USA, Inc, Malvern, Pennsylvania, USA.
Kevin
K
Johnson
Medical Imaging, University of Arizona, Tucson, Arizona, USA.
Diego R
DR
Martin
Medical Imaging, University of Arizona, Tucson, Arizona, USA.
Maria I
MI
Altbach
Electrical & Computer Engineering, University of Arizona, Tucson, Arizona, USA.|Medical Imaging, University of Arizona, Tucson, Arizona, USA.|Biomedical Engineering, University of Arizona, Tucson, Arizona, USA.
Ali
A
Bilgin
Medical Imaging, University of Arizona, Tucson, Arizona, USA.|Biomedical Engineering, University of Arizona, Tucson, Arizona, USA.
Manojkumar
M
Saranathan
D000465:Algorithms; D044962:Data Compression / Q000379:methods*; D005919:Glomerular Filtration Rate; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007668:Kidney / Q000000981:diagnostic imaging* / Q000502:physiology*; D007677:Kidney Function Tests / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D014567:Urography / Q000379:methods
compressed sensing; dynamic contrast enhanced MRI; glomerular filtration rate; multiresolution MRI; pharmacokinetic modeling