Dataset Information

XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing.

ABSTRACT:

Purpose

To develop a novel framework for free-breathing MRI called XD-GRASP, which sorts dynamic data into extra motion-state dimensions using the self-navigation properties of radial imaging and reconstructs the multidimensional dataset using compressed sensing.

Methods

Radial k-space data are continuously acquired using the golden-angle sampling scheme and sorted into multiple motion-states based on respiratory and/or cardiac motion signals derived directly from the data. The resulting undersampled multidimensional dataset is reconstructed using a compressed sensing approach that exploits sparsity along the new dynamic dimensions. The performance of XD-GRASP is demonstrated for free-breathing three-dimensional (3D) abdominal imaging, two-dimensional (2D) cardiac cine imaging and 3D dynamic contrast-enhanced (DCE) MRI of the liver, comparing against reconstructions without motion sorting in both healthy volunteers and patients.

Results

XD-GRASP separates respiratory motion from cardiac motion in cardiac imaging, and respiratory motion from contrast enhancement in liver DCE-MRI, which improves image quality and reduces motion-blurring artifacts.

Conclusion

XD-GRASP represents a new use of sparsity for motion compensation and a novel way to handle motions in the context of a continuous acquisition paradigm. Instead of removing or correcting motion, extra motion-state dimensions are reconstructed, which improves image quality and also offers new physiological information of potential clinical value.

SUBMITTER: Feng L

PROVIDER: S-EPMC4583338 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Publications

XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing.

Feng Li L Axel Leon L Chandarana Hersh H Block Kai Tobias KT Sodickson Daniel K DK Otazo Ricardo R

Magnetic resonance in medicine 20150325 2

<h4>Purpose</h4>To develop a novel framework for free-breathing MRI called XD-GRASP, which sorts dynamic data into extra motion-state dimensions using the self-navigation properties of radial imaging and reconstructs the multidimensional dataset using compressed sensing.<h4>Methods</h4>Radial k-space data are continuously acquired using the golden-angle sampling scheme and sorted into multiple motion-states based on respiratory and/or cardiac motion signals derived directly from the data. The re ...[more]

PMID: 25809847

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Project description:PurposeThe aim of this study was to demonstrate the value of DCE MRI with high spatiotemporal resolution (GRASP) for differentiating paragangliomas and schwannomas in the head and neck.MethodsIn a retrospective PACS search of in total 410 patients who had undergone head & neck GRASP-MRI, we identified 6 patients with biopsy proven cervical paragangliomas (n = 3) and schwannomas (n = 3). Conventional MRI features were evaluated, lesion size was determined. Postprocessing in 4D-GRASP datasets was performed (1) based on reconstructions with a temporal resolution (Tres) of 4.1 s, qualitative time-intensity curve classification and semiquantitative parameter (Tpeak, PH, ERmax and Slopemax) analysis, and (2) voxel-based mapping and qualitative and semiquantitative perfusion modeling based on reconstructions with a Tres of 1.6 s. Additionally, GRASP perfusion analysis was performed in another set of 5 patients with presumed cervical paragangliomas (n = 3) and schwannomas (n = 2) based on conventional imaging criteria and was correlated with conventional imaging findings. Due to the small sample size, both groups were compared qualitatively.ResultsIn the time intensity curve classification of 4D GRASP reconstructions (Tres 4.1 s), biopsy proven paragangliomas were consistently characterized by a type-III rapid inflow wash-out pattern, compared to a type-I inflow pattern in the schwannoma group. In both temporal resolutions, semiquantitative analysis of time intensity curves demonstrated rapid wash-in, wash-out, and higher peak signal intensities in paragangliomas compared to schwannomas. In 5 presumed (non-biopsy-proven) paragangliomas and schwannomas, time intensity curves improved diagnostic certainty.ConclusionsVisual time intensity curve classification and semi-quantitative analysis of GRASP-MRI were, in this small retrospective series, sufficient to differentiate cervical paragangliomas from schwannomas. Utilization of this technique may further improve diagnostic confidence in lesions lacking conventional imaging features.

Project description:Intraframe motion blurring, as a major challenge in free-breathing dynamic MRI, can be reduced if high temporal resolution can be achieved. To address this challenge, this work proposes a highly accelerated 4D (3D + time) dynamic MRI framework with subsecond temporal resolution that does not require explicit motion compensation. The method combines standard stack-of-stars golden-angle radial sampling and tailored GRASP-Pro (Golden-angle RAdial Sparse Parallel imaging with imProved performance) reconstruction. Specifically, 4D dynamic MRI acquisition is performed continuously without motion gating or sorting. The k-space centers in stack-of-stars radial data are organized to guide estimation of a temporal basis, with which GRASP-Pro reconstruction is employed to enforce joint low-rank subspace and sparsity constraints. This new basis estimation strategy is the new feature proposed for subspace-based reconstruction in this work to achieve high temporal resolution (e.g., subsecond/3D volume). It does not require sequence modification to acquire additional navigation data, it is compatible with commercially available stack-of-stars sequences, and it does not need an intermediate reconstruction step. The proposed 4D dynamic MRI approach was tested in abdominal motion phantom, free-breathing abdominal MRI, and dynamic contrast-enhanced MRI (DCE-MRI). Our results have shown that GRASP-Pro reconstruction with the new basis estimation strategy enables highly-accelerated 4D dynamic imaging at subsecond temporal resolution (with five spokes or less for each dynamic frame per image slice) for both free-breathing non-DCE-MRI and DCE-MRI. In the abdominal phantom, better image quality with lower root mean square error and higher structural similarity index was achieved using GRASP-Pro compared with standard GRASP. With the ability to acquire each 3D image in less than 1 s, intraframe respiratory blurring can be intrinsically reduced for body applications with our approach, which eliminates the need for explicit motion detection and motion compensation.

Dataset Information

XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing.

Purpose

Methods

Results

Conclusion

Publications

XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing.

Similar Datasets

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