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3T 下基于导航的前瞻性运动校正在 MPRAGE 数据中的有效性。

Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T.

机构信息

NIH MRI Research Facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.

Functional MRI Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States of America.

出版信息

PLoS One. 2018 Jun 28;13(6):e0199372. doi: 10.1371/journal.pone.0199372. eCollection 2018.

Abstract

In MRI, subject motion results in image artifacts. High-resolution 3D scans, like MPRAGE, are particularly susceptible to motion because of long scan times and acquisition of data over multiple-shots. Such motion related artifacts have been shown to cause a bias in cortical measures extracted from segmentation of high-resolution MPRAGE images. Prospective motion correction (PMC) techniques have been developed to help mitigate artifacts due to subject motion. In this work, high-resolution MPRAGE images are acquired during intentional head motion to evaluate the effectiveness of navigator-based PMC techniques to improve both the accuracy and reproducibility of cortical morphometry measures obtained from image segmentation. The contribution of reacquiring segments of k-space affected by motion to the overall performance of PMC is assessed. Additionally, the effect of subject motion on subcortical structure volumes is investigated. In the presence of head motion, navigator-based PMC is shown to improve both the accuracy and reproducibility of cortical and subcortical measures. It is shown that reacquiring segments of k-space data that are corrupted by motion is an essential part of navigator-based PMC performance. Subcortical structure volumes are not affected by motion in the same way as cortical measures; there is not a consistent underestimation.

摘要

在 MRI 中,由于受试者的运动,会导致图像伪影。高分辨率 3D 扫描,如 MPRAGE,由于扫描时间长和多次采集数据,特别容易受到运动的影响。已经证明,这种与运动相关的伪影会导致从高分辨率 MPRAGE 图像分割中提取的皮质测量值产生偏差。已经开发了前瞻性运动校正 (PMC) 技术来帮助减轻由于受试者运动引起的伪影。在这项工作中,在故意头部运动期间采集高分辨率 MPRAGE 图像,以评估基于导航的 PMC 技术的有效性,以提高从图像分割获得的皮质形态测量的准确性和可重复性。评估了受运动影响的 k 空间片段的重新采集对 PMC 整体性能的影响。此外,还研究了受试者运动对皮质下结构体积的影响。在存在头部运动的情况下,基于导航的 PMC 被证明可以提高皮质和皮质下测量的准确性和可重复性。结果表明,重新采集受运动污染的 k 空间数据片段是基于导航的 PMC 性能的重要组成部分。皮质下结构体积不会像皮质测量值那样受到运动的影响,不会出现一致的低估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb04/6023162/e85a0a7ee760/pone.0199372.g001.jpg

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