Model‐based reconstruction for real‐time phase‐contrast flow MRI: Improved spatiotemporal accuracy

Tan, Zhengguo; Roeloffs, Volkert; Voit, Dirk; Joseph, Arun A.; Untenberger, Markus; Merboldt, Klaus‐Dietmar; Frahm, Jens

doi:10.1002/mrm.26192

Cited by 42 publications

(84 citation statements)

References 33 publications

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“…Finally, residual streaking artifacts in PC velocity maps may appear around high-flow arteries and eventually affect the phase information in neighboring veins. While no major complication was observed in the present study, the problem may be resolved by a more advanced reconstruction technique for real-time PC flow MRI which almost completely avoids such artifacts (33).…”

Section: Discussionmentioning

confidence: 65%

Real-time magnetic resonance imaging of deep venous flow during muscular exercise—preliminary experience

Joseph

Merboldt

Voit

et al. 2016

Cardiovasc. Diagn. Ther.

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Background: The accurate assessment of peripheral venous flow is important for the early diagnosis and treatment of disorders such as deep-vein thrombosis (DVT) which is a major cause of post-thrombotic syndrome or even death due to pulmonary embolism. The aim of this work is to quantitatively determine blood flow in deep veins during rest and muscular exercise using a novel real-time magnetic resonance imaging (MRI) method for velocity-encoded phase-contrast (PC) MRI at high spatiotemporal resolution.

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Section: Discussionmentioning

confidence: 65%

Real-time magnetic resonance imaging of deep venous flow during muscular exercise—preliminary experience

Joseph

Merboldt

Voit

et al. 2016

Cardiovasc. Diagn. Ther.

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“…Moreover, motion models, either rigid or non-rigid, can also be integrated to guide the image reconstruction and to determine motion fields for certain applications (73). Other examples include T 1 and T 2 encoding (101), diffusion encoding (102), and flow encoding (103). These models are expected to improve the sparsity conditions and the performance of sparsity-enforcing reconstructions.…”

Section: Sparse Body Mri: Challenges and Opportunitiesmentioning

confidence: 99%

Compressed sensing for body MRI

Feng

Benkert

Block

et al. 2016

Magnetic Resonance Imaging

236

180

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The introduction of compressed sensing for increasing imaging speed in MRI has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than that are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This paper presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and non-linear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the paper discusses current challenges and future opportunities.

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“…Recently, considerable progress in real‐time MRI based on regularized nonlinear inverse reconstructions (NLINV) of highly undersampled radial gradient‐echo acquisitions drastically increased the temporal resolution of cross‐sectional image series . The basic approach could be extended to real‐time PC flow MRI at 35 to 40 ms resolution for one‐directional velocity encoding (i.e., through‐plane flow), while the subsequent development of a model‐based reconstruction method achieved about 25 ms . At the same time the model‐based approach improves the spatial acuity because it results in velocity maps free of the usual phase noise in regions without signal support (e.g., the lungs).…”

Section: Introductionmentioning

confidence: 99%

Real‐time multi‐directional flow MRI using model‐based reconstructions of undersampled radial FLASH – A feasibility study

et al. 2019

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The purpose of this work was to develop an acquisition and reconstruction technique for two‐ and three‐directional (2d and 3d) phase‐contrast flow MRI in real time. A previous real‐time MRI technique for one‐directional (1d) through‐plane flow was extended to 2d and 3d flow MRI by introducing in‐plane flow sensitivity. The method employs highly undersampled radial FLASH sequences with sequential acquisitions of two or three flow‐encoding datasets and one flow‐compensated dataset. Echo times are minimized by merging the waveforms of flow‐encoding and radial imaging gradients. For each velocity direction individually, model‐based reconstructions by regularized nonlinear inversion jointly estimate an anatomical image, a set of coil sensitivities and a phase‐contrast velocity map directly. The reconstructions take advantage of a dynamic phase reference obtained by interpolating consecutive flow‐compensated acquisitions. Validations include pulsatile flow phantoms as well as in vivo studies of the human aorta at 3 T. The proposed method offers cross‐sectional 2d and 3d flow MRI of the human aortic arch at 53 and 67 ms resolution, respectively, without ECG synchronization and during free breathing. The in‐plane resolution was 1.5 × 1.5 mm2 and the slice thickness 6 mm. In conclusion, real‐time multi‐directional flow MRI offers new opportunities to study complex human blood flow without the risk of combining differential phase (i.e., velocity) information from multiple heartbeats as for ECG‐gated data. The method would benefit from a further reduction of acquisition time and accelerated computing to allow for extended clinical trials.

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Model‐based reconstruction for real‐time phase‐contrast flow MRI: Improved spatiotemporal accuracy

Abstract: This novel model-based reconstruction technique may become a new tool for clinical flow MRI in real time. Magn Reson Med 77:1082-1093, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Cited by 42 publications

References 33 publications

Real-time magnetic resonance imaging of deep venous flow during muscular exercise—preliminary experience

Real-time magnetic resonance imaging of deep venous flow during muscular exercise—preliminary experience

Compressed sensing for body MRI

Real‐time multi‐directional flow MRI using model‐based reconstructions of undersampled radial FLASH – A feasibility study

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