Magnetic resonance fingerprinting

Purpose: The proposed reconstruction framework addresses the reconstruction accuracy, noise propagation and computation time for magnetic resonance fingerprinting. Methods: Based on a singular value decomposition of the signal evolution, magnetic resonance fingerprinting is formulated as a low rank (LR) inverse problem in which one image is reconstructed for each singular value under consideration. This LR approximation of the signal evolution reduces the computational burden by reducing the number of Fourier transformations. Also, the LR approximation improves the conditioning of the problem, which is further improved by extending the LR inverse problem to an augmented Lagrangian that is solved by the alternating direction method of multipliers. The root mean square error and the noise propagation are analyzed in simulations. For verification, in vivo examples are provided. Results: The proposed LR alternating direction method of multipliers approach shows a reduced root mean square error compared to the original fingerprinting reconstruction, to a LR approximation alone and to an alternating direction method of multipliers approach without a LR approximation. Incorporating sensitivity encoding allows for further artifact reduction. Conclusion:The proposed reconstruction provides robust convergence, reduced computational burden and improved image quality compared to other magnetic resonance fingerprinting reconstruction approaches evaluated in this study. Magn Reson Med 79:83-96,

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“…[6]) as proposed in Ref. 9, a filtered back-projection in the LR domain (Eq. [15]) as proposed in Ref.…”

Section: Image Reconstructionmentioning

confidence: 99%

Low rank alternating direction method of multipliers reconstruction for MR fingerprinting

Assländer

Cloos

Knoll

et al. 2017

Magnetic Resonance in Med

176

298

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“…For simplicity, hereafter we use a discrete image model in which (1) can be represented as (2) where I m and ρ are N × 1 complex vectors, T 1 , and T 2 are all N × 1 real vectors, and Φ m (·) ∈ ℂ N×N is a diagonal matrix with [Φ m ] n,n = ϕ m (T 1 [n], T 2 [n]). Moreover, under this setting, (3) for m = 1, ⋯, M, and c = 1, ⋯, N c , where d m,c ∈ ℂ P , and n m,c ∈ ℂ P respectively contain the measured k-space data and measurement noise from the cth receiver coil at TR m , F m ∈ ℂ P×N denotes the undersampled Fourier encoding matrix, S c ∈ ℂ N×N is a diagonal matrix with the diagonal entries containing the coil sensitivities associated with the cth receiver coil, and N c denotes the total number of receiver coils.…”

Section: A Formulationmentioning

confidence: 99%

“…In MR fingerprinting, the contrast-weighted image I m (x) can be parameterized as [6], [20], [21]: (1) for m = 1, ⋯, M, where ρ(x) denotes the spin density, T 1 (x) the longitudinal relaxation time, T 2 (x) the transverse relaxation time, and ϕ m (·) the contrast-weighting function associated with the mth acquisition parameter (e.g., the flip angle α m and repetition time TR m ). Note that ϕ m (·) in (1) is determined by the Bloch equation based magnetization dynamics, driven by the acquisition parameters .…”

Section: A Formulationmentioning

confidence: 99%

Maximum likelihood reconstruction for magnetic resonance fingerprinting

Zhao

Lam

Bilgic̦

et al. 2015

2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)

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This paper introduces a statistical estimation framework for magnetic resonance (MR) fingerprinting, a recently proposed quantitative imaging paradigm. Within this framework, we present a maximum likelihood (ML) formalism to estimate multiple parameter maps directly from highly undersampled, noisy k-space data. A novel algorithm, based on variable splitting, the alternating direction method of multipliers, and the variable projection method, is developed to solve the resulting optimization problem. Representative results from both simulations and in vivo experiments demonstrate that the proposed approach yields significantly improved accuracy in parameter estimation, compared to the conventional MR fingerprinting reconstruction. Moreover, Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org. HHS Public Access Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript the proposed framework provides new theoretical insights into the conventional approach. We show analytically that the conventional approach is an approximation to the ML reconstruction; more precisely, it is exactly equivalent to the first iteration of the proposed algorithm for the ML reconstruction, provided that a gridding reconstruction is used as an initialization.

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“…A fundamental component of the MRF reconstruction is the development of a large dictionary of signal evolution profiles that are subsequently "matched" to the acquired MRF signal evolution profile for each imaging voxel using vector-based inner product comparisons. The MRF dictionary was created as described previously 24 assuming a mono-exponential relaxation model. MRF image reconstruction as well as subsequent dictionary matching were performed on the Siemens Skyra 3 T MRI scanner.…”

Section: Methodsmentioning

confidence: 99%

“…MRF uses a unique acquisition and quantification strategy that combines a priori acquisition parameter variation with a dictionary-based pattern matching algorithm to obtain quantitative assessments of multiple imaging parameters simultaneously. Importantly, MRF has been shown to provide quantitative T1 and T2 maps in 10-50 seconds per imaging slice providing the opportunity to dynamically generate quantitative maps of these two important MRI parameters simultaneously [24][25][26][27] . In this study, we demonstrate that the framework for simultaneous T1 and T2 assessments provided by MRF can be used to analytically quantify the local concentration of two different MRI contrast agents present at the same time.…”

mentioning

confidence: 99%

Dual Contrast - Magnetic Resonance Fingerprinting (DC-MRF): A Platform for Simultaneous Quantification of Multiple MRI Contrast Agents

Anderson

Donnola

Jiang

et al. 2017

Sci Rep

Self Cite

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Injectable Magnetic Resonance Imaging (MRI) contrast agents have been widely used to provide critical assessments of disease for both clinical and basic science imaging research studies. The scope of available MRI contrast agents has expanded over the years with the emergence of molecular imaging contrast agents specifically targeted to biological markers. Unfortunately, synergistic application of more than a single molecular contrast agent has been limited by MRI's ability to only dynamically measure a single agent at a time. In this study, a new Dual Contrast -Magnetic Resonance Fingerprinting (DC -MRF) methodology is described that can detect and independently quantify the local concentration of multiple MRI contrast agents following simultaneous administration. This "multi-color" MRI methodology provides the opportunity to monitor multiple molecular species simultaneously and provides a practical, quantitative imaging framework for the eventual clinical translation of molecular imaging contrast agents.Over the past 3 decades, Magnetic Resonance Imaging (MRI) has become an essential medical imaging modality due to its exceptional soft tissue contrast and lack of ionizing radiation. Along with a wide variety of endogenous tissue contrast mechanisms, many MRI applications utilize an intravenous injection of an MRI contrast agent (e.g., gadolinium chelates or iron oxides) to enable sensitive identification of numerous pathologies such as tumors 1 , vascular abnormalities 2 , and cardiac infarcts 3 through local alterations in the tissue's magnetic properties (T1 and T2 relaxation times). Clinical use of these contrast-enhanced MRI scans has further expanded as multiple contrast agents have been approved for specific clinical imaging applications (e.g., blood pool contrast agents 4 , hepatobiliary contrast agents 5 ).With the emergence of the field of molecular imaging, there has been a dramatic increase in the number of MRI contrast agents targeted to proteins 6-8 , cell receptors 9, 10 , and other molecular species 11,12 . In addition, a number of activatable agents have been described that have different relaxivities based on the local tissue environment in vivo 13,14 . In a typical preclinical molecular MRI study, the T1 or T2 relaxation time (or MRI signal intensity) is

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Magnetic resonance fingerprinting

Cited by 1,300 publications

References 49 publications

Low rank alternating direction method of multipliers reconstruction for MR fingerprinting

Low rank alternating direction method of multipliers reconstruction for MR fingerprinting

Maximum likelihood reconstruction for magnetic resonance fingerprinting

Dual Contrast - Magnetic Resonance Fingerprinting (DC-MRF): A Platform for Simultaneous Quantification of Multiple MRI Contrast Agents

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