Dynamic distortion correction for functional MRI using FID navigators.
Magn Reson Med
; 85(3): 1294-1307, 2021 03.
Article
em En
| MEDLINE
| ID: mdl-32970869
ABSTRACT
PURPOSE:
To develop a method for slice-wise dynamic distortion correction for EPI using rapid spatiotemporal B0 field measurements from FID navigators (FIDnavs) and to evaluate the efficacy of this new approach relative to an established data-driven technique.METHODS:
A low-resolution reference image was used to create a forward model of FIDnav signal changes to enable estimation of spatiotemporal B0 inhomogeneity variations up to second order from measured FIDnavs. Five volunteers were scanned at 3 T using a 64-channel coil with FID-navigated EPI. The accuracy of voxel shift measurements and geometric distortion correction was assessed for experimentally induced magnetic field perturbations. The temporal SNR was evaluated in EPI time-series acquired at rest and with a continuous nose-touching action, before and after image realignment.RESULTS:
Field inhomogeneity coefficients and voxel shift maps measured using FIDnavs were in excellent agreement with multi-echo EPI measurements. The FID-navigated distortion correction accurately corrected image geometry in the presence of induced magnetic field perturbations, outperforming the data-driven approach in regions with large field offsets. In functional MRI scans with nose touching, FIDnav-based correction yielded temporal SNR gains of 30% in gray matter. Following image realignment, which accounted for global image shifts, temporal SNR gains of 3% were achieved.CONCLUSIONS:
Our proposed application of FIDnavs enables slice-wise dynamic distortion correction with high temporal efficiency. We achieved improved signal stability by leveraging the encoding information from multichannel coils. This approach can be easily adapted to other EPI-based sequences to improve temporal SNR for a variety of clinical and research applications.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Imagem Ecoplanar
Limite:
Humans
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article