Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging.
J Magn Reson Imaging
; 36(4): 961-71, 2012 Oct.
Article
em En
| MEDLINE
| ID: mdl-22689498
ABSTRACT
PURPOSE:
To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high-quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts. MATERIALS ANDMETHODS:
We implemented an in-house built generalized autocalibrating partially parallel acquisitions (GRAPPA)-accelerated diffusion tensor (DT) echo-planar imaging (EPI) sequence at 1.5T and 3T on 1600 patients between 1 month and 18 years old. To reconstruct the data, we developed a fully automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid-body realignment with importance weighting; and employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b-matrix correction for large motion.RESULTS:
The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only three subjects, while providing the radiologists high-quality data for routine evaluation.CONCLUSION:
This work suggests that, apart from the rare instance of continuous motion throughout the scan, high-quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging, which reduces the Rician noise that biases noisy data.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
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Encéfalo
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Reconhecimento Automatizado de Padrão
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Interpretação de Imagem Assistida por Computador
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Aumento da Imagem
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Artefatos
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Imagem de Difusão por Ressonância Magnética
Tipo de estudo:
Diagnostic_studies
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Observational_studies
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Prognostic_studies
Limite:
Adolescent
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Child
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Child, preschool
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Humans
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Infant
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Male
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Newborn
Idioma:
En
Ano de publicação:
2012
Tipo de documento:
Article