Multi-contrast multi-shot EPI for accelerated diffusion MRI

Shafieizargar, Banafshe; Jeurissen, Ben; Poot, Dirk H. J.; Dekker, Arnold J. den; Sijbers, Jan

doi:10.1109/embc46164.2021.9630069

Cited by 2 publications

(2 citation statements)

References 16 publications

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“…Developing novel models that parameterize the model jointly for auxiliary parameters. For instance: the joint estimation of off‐resonance frequency in

{\mathrm{T}}_2^{\ast }

mapping, 279 the joint estimation of

{\mathrm{T}}_2^{\ast }

and field maps in water and fat parameter estimation, 272,280,281 the joint estimation of flip angles and proton density maps in

{\mathrm{T}}_2

mapping, 282 the joint estimation of steady‐state signal, equilibrium signal, and effective relaxation rate in

{\mathrm{T}}_1

mapping, 283‐285 the joint estimation of tracer kinetic model parameters in

{\mathrm{T}}_1

mapping, 286 and the joint estimation of phase parameters in multishot diffusion imaging 287,288 …”

Section: Resultsmentioning

confidence: 99%

“…For instance: the joint estimation of off-resonance frequency in T * 2 mapping, 279 the joint estimation of T * 2 and field maps in water and fat parameter estimation, 272,280,281 the joint estimation of flip angles and proton density maps in T 2 mapping, 282 the joint estimation of steady-state signal, equilibrium signal, and effective relaxation rate in T 1 mapping, [283][284][285] the joint estimation of tracer kinetic model parameters in T 1 mapping, 286 and the joint estimation of phase parameters in multishot diffusion imaging. 287,288 Regularized direct reconstruction. To improve the performance of direct reconstruction, prior information about the qMRI parameters to be estimated can be incorporated by adding regularization terms, such as Tikhonov regularizer, 274 l 1 norm regularizer, 289 and weighted l 1 ball regularizer 268,290 to the cost function described by Equation (24).…”

Section: Direct Model-based Reconstructionmentioning

confidence: 99%

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Systematic review of reconstruction techniques for accelerated quantitative MRI

Shafieizargar

Byanju

Sijbers

et al. 2023

Magnetic Resonance in Med

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To systematically review the techniques that address undersampling artifacts in accelerated quantitative magnetic resonance imaging (qMRI). Methods: A literature search was conducted using the Embase, Medline, Web of Science Core Collection, Coherence Central Register of Controlled Trials, and Google Scholar databases for studies, published before July 2022 proposing reconstruction techniques for accelerated qMRI. Studies are reviewed according to inclusion criteria, and included studies are categorized based on the methodology used. Results: A total of 292 studies included in the review are categorized. A technical overview of each category is provided, and the categories are described in a unified mathematical framework. The distribution of the reviewed studies over time, application domain, and parameters of interest is illustrated. Conclusion: An increasing trend in the number of articles that propose new techniques for accelerated qMRI reconstruction indicates the importance of acceleration in qMRI. The techniques are mostly validated for relaxometry parameters and brain scans. The categories of techniques are compared based on theoretical grounds, highlighting existing trends and potential gaps in the field.

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“…Developing novel models that parameterize the model jointly for auxiliary parameters. For instance: the joint estimation of off‐resonance frequency in

{\mathrm{T}}_2^{\ast }

mapping, 279 the joint estimation of

{\mathrm{T}}_2^{\ast }

and field maps in water and fat parameter estimation, 272,280,281 the joint estimation of flip angles and proton density maps in

{\mathrm{T}}_2

mapping, 282 the joint estimation of steady‐state signal, equilibrium signal, and effective relaxation rate in

{\mathrm{T}}_1

mapping, 283‐285 the joint estimation of tracer kinetic model parameters in

{\mathrm{T}}_1

mapping, 286 and the joint estimation of phase parameters in multishot diffusion imaging 287,288 …”

Section: Resultsmentioning

confidence: 99%

Section: Direct Model-based Reconstructionmentioning

confidence: 99%

Systematic review of reconstruction techniques for accelerated quantitative MRI

Shafieizargar

Byanju

Sijbers

et al. 2023

Magnetic Resonance in Med

Self Cite

View full text Add to dashboard Cite

show abstract

ADEPT: Accurate Diffusion Echo‐Planar imaging with multi‐contrast shoTs

Shafieizargar

Jeurissen

Poot

et al. 2022

Magnetic Resonance in Med

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Theory and Methods:We propose a new framework called ADEPT (Accurate Diffusion Echo-Planar imaging with multi-contrast shoTs) that enables fast diffusion MRI by allowing diffusion contrast settings to change between shots in a multi-shot EPI acquisition (i.e., intra-scan modulation). The framework estimates diffusion parameter maps directly from the acquired intra-scan modulated k-space data, while simultaneously accounting for shot-to-shot phase inconsistencies. The performance of the estimation framework is evaluated using Monte Carlo simulation studies and in-vivo experiments and compared to that of reference methods that rely on parallel imaging for shot-to-shot phase correction.Results: Simulation and real-data experiments show that ADEPT yields more accurate and more precise estimates of the diffusion metrics in multi-shot EPI data in comparison with the reference methods. Conclusion: ADEPT allows fast multi-shot EPI diffusion MRI without significantly degrading the accuracy and precision of the estimated diffusion maps.

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Multi-contrast multi-shot EPI for accelerated diffusion MRI

Cited by 2 publications

References 16 publications

Systematic review of reconstruction techniques for accelerated quantitative MRI

Systematic review of reconstruction techniques for accelerated quantitative MRI

ADEPT: Accurate Diffusion Echo‐Planar imaging with multi‐contrast shoTs

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