Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Dec 6:10:558.
doi: 10.3389/fnins.2016.00558. eCollection 2016.

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

Affiliations

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

Lea L Backhausen et al. Front Neurosci. .

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.

Keywords: attention-deficit/hyperactivity disorder (ADHD); head motion; quality control; rating system; structural MRI; volumetry.

PubMed Disclaimer

Figures

Figure 1
Figure 1
QC workflow. Boxes in light blue represent QC steps using T1-weighted images and boxes in dark blue represent QC steps using processed images via automated processing pipeline. Exclude/Include: exclusion/inclusion of data set in further preprocessing and analysis.
Figure 2
Figure 2
Examples of the quality of T1-images according to rating categories. The images in category C1 (pass) are clear, no motion artifacts or ringing can be seen and subcortical structures as well as gray matter/white matter can be well differentiated. In category C2 (check) ringing can be seen but the contrast of the structures themselves is good and they can be differentiated. In category C3 (fail) ringing as well as motion artifacts (distortion) are present. The contrast is very poor and structures blend into each other.
Figure 3
Figure 3
Structural volume differences across QC rating categories for total gray matter (A), cortex (B), left amygdala (C), and white matter hypointensities (D). Significance values refer to post-hoc t-tests. **p < 0.01, *p < 0.05. Error bars denote SEM.

References

    1. Alexander-Bloch A., Clasen L., Stockman M., Ronan L., Lalonde F., Giedd J., et al. . (2016). Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI. Hum. Brain Mapp. 37, 2385–2397. 10.1002/hbm.23180 - DOI - PMC - PubMed
    1. Bellon E. M., Haacke E. M., Coleman P. E., Sacco D. C., Steiger D. A., Gangarosa R. E. (1986). MR artifacts: a review. Am. J. Roentgenol. 147, 1271–1281. 10.2214/ajr.147.6.1271 - DOI - PubMed
    1. Blumenthal J. D., Zijdenbos A., Molloy E., Giedd J. N. (2002). Motion artifact in magnetic resonance imaging: implications for automated analysis. Neuroimage 16, 89–92. 10.1006/nimg.2002.1076 - DOI - PubMed
    1. Brown T. T., Kuperman J. M., Erhart M., White N. S., Roddey J. C., Shankaranarayanan A., et al. . (2010). Prospective motion correction of high-resolution magnetic resonance imaging data in children. Neuroimage 53, 139–145. 10.1016/j.neuroimage.2010.06.017 - DOI - PMC - PubMed
    1. Buse J., Beste C., Herrmann E., Roessner V. (2016). Neural correlates of altered sensorimotor gating in boys with Tourette Syndrome: a combined EMG/fMRI study. World J. Biol. Psychiatry 17, 187–197. 10.3109/15622975.2015.1112033 - DOI - PubMed