Model-based super-resolution reconstruction of T<sub>2</sub> maps.
Details
Serval ID
serval:BIB_56A823225607
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Model-based super-resolution reconstruction of T<sub>2</sub> maps.
Journal
Magnetic resonance in medicine
ISSN
1522-2594 (Electronic)
ISSN-L
0740-3194
Publication state
Published
Issued date
03/2020
Peer-reviewed
Oui
Volume
83
Number
3
Pages
906-919
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Publication Status: ppublish
Abstract
High-resolution isotropic T <sub>2</sub> mapping of the human brain with multi-echo spin-echo (MESE) acquisitions is challenging. When using a 2D sequence, the resolution is limited by the slice thickness. If used as a 3D acquisition, specific absorption rate limits are easily exceeded due to the high power deposition of nonselective refocusing pulses. A method to reconstruct 1-mm <sup>3</sup> isotropic T <sub>2</sub> maps is proposed based on multiple 2D MESE acquisitions. Data were undersampled (10-fold) to compensate for the prolonged scan time stemming from the super-resolution acquisition.
The proposed method integrates a classical super-resolution with an iterative model-based approach to reconstruct quantitative maps from a set of undersampled low-resolution data. The method was tested on numerical and multipurpose phantoms, and in vivo data. T <sub>2</sub> values were assessed with a region-of-interest analysis using a single-slice spin-echo and a fully sampled MESE acquisition in a phantom, and a MESE acquisition in healthy volunteers.
Numerical simulations showed that the best trade-off between acceleration and number of low-resolution datasets is 10-fold acceleration with 4 acquisitions (acquisition time = 18 min). The proposed approach showed improved resolution over low-resolution images for both phantom and brain. Region-of-interest analysis of the phantom compartments revealed that at shorter T <sub>2</sub> , the proposed method was comparable with the fully sampled MESE. For the volunteer data, the T <sub>2</sub> values found in the brain structures were consistent across subjects (8.5-13.1 ms standard deviation).
The proposed method addresses the inherent limitations associated with high-resolution T <sub>2</sub> mapping and enables the reconstruction of 1 mm <sup>3</sup> isotropic relaxation maps with a 10 times faster acquisition.
The proposed method integrates a classical super-resolution with an iterative model-based approach to reconstruct quantitative maps from a set of undersampled low-resolution data. The method was tested on numerical and multipurpose phantoms, and in vivo data. T <sub>2</sub> values were assessed with a region-of-interest analysis using a single-slice spin-echo and a fully sampled MESE acquisition in a phantom, and a MESE acquisition in healthy volunteers.
Numerical simulations showed that the best trade-off between acceleration and number of low-resolution datasets is 10-fold acceleration with 4 acquisitions (acquisition time = 18 min). The proposed approach showed improved resolution over low-resolution images for both phantom and brain. Region-of-interest analysis of the phantom compartments revealed that at shorter T <sub>2</sub> , the proposed method was comparable with the fully sampled MESE. For the volunteer data, the T <sub>2</sub> values found in the brain structures were consistent across subjects (8.5-13.1 ms standard deviation).
The proposed method addresses the inherent limitations associated with high-resolution T <sub>2</sub> mapping and enables the reconstruction of 1 mm <sup>3</sup> isotropic relaxation maps with a 10 times faster acquisition.
Keywords
T2 mapping, model-based reconstruction, parallel Imaging, super-resolution
Pubmed
Web of science
Open Access
Yes
Create date
20/09/2019 22:41
Last modification date
05/02/2020 6:20