Multiresolution imaging using golden angle stack‐of‐stars and compressed sensing for dynamic MR urography
Purpose To develop a novel multiresolution MRI methodology for accurate estimation of glomerular filtration rate (GFR) in vivo. Materials and Methods A three‐dimensional golden‐angle radial stack‐of‐stars (SoS) trajectory was used for data acquisition on a 3 Tesla MRI scanner. Multiresolution recons...
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Published in | Journal of magnetic resonance imaging Vol. 46; no. 1; pp. 303 - 311 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Wiley Subscription Services, Inc
01.07.2017
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Subjects | |
Online Access | Get full text |
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Summary: | Purpose
To develop a novel multiresolution MRI methodology for accurate estimation of glomerular filtration rate (GFR) in vivo.
Materials and Methods
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.
Results
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).
Conclusion
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.
Level of Evidence: 1
Technical Efficacy: Stage 3
J. MAGN. RESON. IMAGING 2017;46:303–311 |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23 ObjectType-Undefined-3 |
ISSN: | 1053-1807 1522-2586 1522-2586 |
DOI: | 10.1002/jmri.25576 |