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Sequence-agnostic motion-correction leveraging efficiently calibrated Pilot Tone signals.
Brackenier, Yannick; Cordero-Grande, Lucilio; McElroy, Sarah; Tomi-Tricot, Raphael; Barbaroux, Hugo; Bridgen, Philippa; Malik, Shaihan J; Hajnal, Joseph V.
Afiliação
  • Brackenier Y; Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Cordero-Grande L; Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • McElroy S; Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Tomi-Tricot R; Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Barbaroux H; Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BNN, ISCIII, Madrid, Spain.
  • Bridgen P; Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Malik SJ; Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Hajnal JV; MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK.
Magn Reson Med ; 2024 Jun 11.
Article em En | MEDLINE | ID: mdl-38860530
ABSTRACT

PURPOSE:

This study leverages externally generated Pilot Tone (PT) signals to perform motion-corrected brain MRI for sequences with arbitrary k-space sampling and image contrast. THEORY AND

METHODS:

PT signals are promising external motion sensors due to their cost-effectiveness, easy workflow, and consistent performance across contrasts and sampling patterns. However, they lack robust calibration pipelines. This work calibrates PT signal to rigid motion parameters acquired during short blocks (˜4 s) of motion calibration (MC) acquisitions, which are short enough to unobstructively fit between acquisitions. MC acquisitions leverage self-navigated trajectories that enable state-of-the-art motion estimation methods for efficient calibration. To capture the range of patient motion occurring throughout the examination, distributed motion calibration (DMC) uses data acquired from MC scans distributed across the entire examination. After calibration, PT is used to retrospectively motion-correct sequences with arbitrary k-space sampling and image contrast. Additionally, a data-driven calibration refinement is proposed to tailor calibration models to individual acquisitions. In vivo experiments involving 12 healthy volunteers tested the DMC protocol's ability to robustly correct subject motion.

RESULTS:

The proposed calibration pipeline produces pose parameters consistent with reference values, even when distributing only six of these approximately 4-s MC blocks, resulting in a total acquisition time of 22 s. In vivo motion experiments reveal significant ( p < 0.05 $$ p<0.05 $$ ) improved motion correction with increased signal to residual ratio for both MPRAGE and SPACE sequences with standard k-space acquisition, especially when motion is large. Additionally, results highlight the benefits of using a distributed calibration approach.

CONCLUSIONS:

This study presents a framework for performing motion-corrected brain MRI in sequences with arbitrary k-space encoding and contrast, using externally generated PT signals. The DMC protocol is introduced, promoting observation of patient motion occurring throughout the examination and providing a calibration pipeline suitable for clinical deployment. The method's application is demonstrated in standard volumetric MPRAGE and SPACE sequences.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article