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使用FreeSurfer对结构MRI图像进行质量控制——一种评估运动伪影的实际操作流程

Quality Control of Structural MRI Images Applied Using FreeSurfer-A Hands-On Workflow to Rate Motion Artifacts.

作者信息

Backhausen Lea L, Herting Megan M, Buse Judith, Roessner Veit, Smolka Michael N, Vetter Nora C

机构信息

Department of Child and Adolescent Psychiatry, Faculty of Medicine of the Technische Universität Dresden Dresden, Germany.

Department of Preventive Medicine, University of Southern California, Los Angeles Los Angeles, CA, USA.

出版信息

Front Neurosci. 2016 Dec 6;10:558. doi: 10.3389/fnins.2016.00558. eCollection 2016.

Abstract

In structural magnetic resonance imaging motion artifacts are common, especially when not scanning healthy young adults. It has been shown that motion affects the analysis with automated image-processing techniques (e.g., FreeSurfer). This can bias results. Several developmental and adult studies have found reduced volume and thickness of gray matter due to motion artifacts. Thus, quality control is necessary in order to ensure an acceptable level of quality and to define exclusion criteria of images (i.e., determine participants with most severe artifacts). However, information about the quality control workflow and image exclusion procedure is largely lacking in the current literature and the existing rating systems differ. Here, we propose a stringent workflow of quality control steps during and after acquisition of T1-weighted images, which enables researchers dealing with populations that are typically affected by motion artifacts to enhance data quality and maximize sample sizes. As an underlying aim we established a thorough quality control rating system for T1-weighted images and applied it to the analysis of developmental clinical data using the automated processing pipeline FreeSurfer. This hands-on workflow and quality control rating system will aid researchers in minimizing motion artifacts in the final data set, and therefore enhance the quality of structural magnetic resonance imaging studies.

摘要

在结构磁共振成像中,运动伪影很常见,尤其是在扫描对象不是健康的年轻人时。研究表明,运动影响自动图像处理技术(如FreeSurfer)的分析,这可能会使结果产生偏差。多项针对发育阶段和成年人的研究发现,运动伪影会导致灰质体积和厚度减小。因此,为确保可接受的质量水平并定义图像的排除标准(即确定具有最严重伪影的参与者),质量控制是必要的。然而,目前的文献中很大程度上缺乏关于质量控制流程和图像排除程序的信息,并且现有的评级系统也各不相同。在此,我们提出了一个在采集T1加权图像期间及之后的严格质量控制步骤工作流程,这使研究人员在处理通常受运动伪影影响的人群时,能够提高数据质量并最大化样本量。作为一个基本目标,我们为T1加权图像建立了一个全面的质量控制评级系统,并将其应用于使用自动处理管道FreeSurfer对发育临床数据的分析中。这个实际操作的工作流程和质量控制评级系统将帮助研究人员最大限度地减少最终数据集中的运动伪影,从而提高结构磁共振成像研究的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f65/5138230/5aedcf4ce92c/fnins-10-00558-g0001.jpg

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