Performance of an Efficient Image-registration Algorithm in Processing MR Renography Data

Overview

Journal J Magn Reson Imaging

Date 2015 Jul 16

PMID 26174884

Citations 5

Authors

Christopher C Conlin

Jeff L Zhang

Florian Rousset

Clement Vachet

Yangyang Zhao

Kathryn A Morton

Kristi Carlston

Guido Gerig

Vivian S Lee

Affiliations

Soon will be listed here.

Abstract

Purpose: To evaluate the performance of an edge-based registration technique in correcting for respiratory motion artifacts in magnetic resonance renographic (MRR) data and to examine the efficiency of a semiautomatic software package in processing renographic data from a cohort of clinical patients.

Materials And Methods: The developed software incorporates an image-registration algorithm based on the generalized Hough transform of edge maps. It was used to estimate glomerular filtration rate (GFR), renal plasma flow (RPF), and mean transit time (MTT) from 36 patients who underwent free-breathing MRR at 3T using saturation-recovery turbo-FLASH. The processing time required for each patient was recorded. Renal parameter estimates and model-fitting residues from the software were compared to those from a previously reported technique. Interreader variability in the software was quantified by the standard deviation of parameter estimates among three readers. GFR estimates from our software were also compared to a reference standard from nuclear medicine.

Results: The time taken to process one patient's data with the software averaged 12 ± 4 minutes. The applied image registration effectively reduced motion artifacts in dynamic images by providing renal tracer-retention curves with significantly smaller fitting residues (P < 0.01) than unregistered data or data registered by the previously reported technique. Interreader variability was less than 10% for all parameters. GFR estimates from the proposed method showed greater concordance with reference values (P < 0.05).

Conclusion: These results suggest that the proposed software can process MRR data efficiently and accurately. Its incorporated registration technique based on the generalized Hough transform effectively reduces respiratory motion artifacts in free-breathing renographic acquisitions.

Citing Articles

Motion correction of free-breathing magnetic resonance renography using model-driven registration.

Flouri D, Lesnic D, Chrysochou C, Parikh J, Thelwall P, Sheerin N MAGMA. 2021; 34(6):805-822.

PMID: 34160718 PMC: 8578117. DOI: 10.1007/s10334-021-00936-x.

Image registration in dynamic renal MRI-current status and prospects.

Zollner F, Serifovic-Trbalic A, Kabelitz G, Kocinski M, Materka A, Rogelj P MAGMA. 2019; 33(1):33-48.

PMID: 31598799 PMC: 7210245. DOI: 10.1007/s10334-019-00782-y.

Performance of U-net based pyramidal lucas-kanade registration on free-breathing multi-b-value diffusion MRI of the kidney.

Lv J, Huang W, Zhang J, Wang X Br J Radiol. 2018; 91(1086):20170813.

PMID: 29528241 PMC: 6223285. DOI: 10.1259/bjr.20170813.

Renal plasma flow (RPF) measured with multiple-inversion-time arterial spin labeling (ASL) and tracer kinetic analysis: Validation against a dynamic contrast-enhancement method.

Conlin C, Oesingmann N, Bolster Jr B, Huang Y, Lee V, Zhang J Magn Reson Imaging. 2016; 37:51-55.

PMID: 27864008 PMC: 5316347. DOI: 10.1016/j.mri.2016.11.010.

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

Zhang J, Conlin C, Carlston K, Xie L, Kim D, Morrell G NMR Biomed. 2016; 29(7):969-77.

PMID: 27200499 PMC: 5206992. DOI: 10.1002/nbm.3553.

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