Visual QC Protocol for FreeSurfer Cortical Parcellations from Anatomical MRI-Reference-Cited by-同舟云学术

Visual QC Protocol for FreeSurfer Cortical Parcellations from Anatomical MRI

Published:2022-12-14 Issue: Volume: Page:
ISSN:
Container-title:Aperture Neuro
language:
Short-container-title:Aperture Neuro

Author:

Raamana Pradeep Reddy¹,Theyers Athena²,Selliah Tharushan²,Bhati Piali²,Arnott Stephen R.²,Hassel Stefanie³,Nanayakkara Nuwan D.⁴,M. Scott Christopher J.⁵,Harris Jacqueline⁶,Zamyadi Mojdeh²,Lam Raymond W.⁷,Milev Roumen⁸,Müller Daniel J.⁹,Rotzinger Susan¹⁰,Frey Benicio N.¹¹,Kennedy Sidney H.¹²,Black Sandra E.¹³,Lang Anthony¹⁴,Masellis Mario¹³,Symons Sean¹⁵,Bartha Robert⁴,MacQueen Glenda M.³,C. Strother Stephen¹⁶

Affiliation:

1. Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada; Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA

2. Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada

3. Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada

4. Centre for Functional and Metabolic Mapping, Robarts Research Institute, Department of Medical Biophysics, University of Western Ontario, London, ON, Canada

5. LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences, Toronto, ON, Canada

6. Department of Computing Science, University of Alberta, Edmonton, AB, Canada

7. Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada

8. Departments of Psychiatry and Psychology, Queen’s University and Providence Care Hospital, Kingston, ON, Canada

9. Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada

10. Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, Krembil Research Centre, University Health Network, Toronto, ON, Canada; Department of Psychiatry, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada

11. Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Program, St. Joseph’s Healthcare Hamilton, ON, Canada

12. Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, Krembil Research Centre, University Health Network, Toronto, ON, Canada; Department of Psychiatry, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada; Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON, Canada

13. LC Campbell Cognitive Neurology Research, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences, Toronto, ON, Canada; Department of Medicine (Neurology), University of Toronto, ON, Canada

14. Department of Medicine (Neurology), University of Toronto, ON, Canada; Edmond J Safra Program in Parkinson’s Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, ON, Canada

15. Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

16. Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada

Abstract

Quality control of morphometric neuroimaging data is essential to improve reproducibility. Owing to the complexity of neuroimaging data and subsequently the interpretation of their results, visual inspection by trained raters is the most reliable way to perform quality control. Here, we present a protocol for visual quality control of the anatomical accuracy of FreeSurfer parcellations, based on an easy-to-use open-source tool called VisualQC. We comprehensively evaluate its utility in terms of error detection rate and inter-rater reliability on two large multi-site datasets and discuss site differences in error patterns. This evaluation shows that VisualQC is a practically viable protocol for community adoption.

Publisher

Organization for Human Brain Mapping

Subject

Rheumatology,Leadership and Management,General Medicine,Rehabilitation,Orthopedics and Sports Medicine,Surgery,General Earth and Planetary Sciences,General Engineering,General Materials Science,Law,Health Policy,General Medicine,Issues, ethics and legal aspects,Orthopedics and Sports Medicine,Literature and Literary Theory,Linguistics and Language,Language and Linguistics,General Physics and Astronomy

Reference28 articles.

1. 1. Fischl, Bruce. 2012. “FreeSurfer.” NeuroImage 62 (2): 774–81. https://doi.org/10.1016/j.neuroimage.2012.01.021.

2. 2. Backhausen, Lea L., Megan M. Herting, Judith Buse, Veit Roessner, Michael N. Smolka, and Nora C. Vetter. 2016. “Quality Control of Structural MRI Images Applied Using FreeSurfer—A Hands-On Workflow to Rate Motion Artifacts.” Frontiers in Neuroscience 10 (January): 2385. https://doi.org/10.3389/fnins.2016.00558.

3. 3. Marcus, Daniel S., Michael P. Harms, Abraham Z. Snyder, Mark Jenkinson, J. Anthony Wilson, Matthew F. Glasser, Deanna M. Barch, et al. 2013. “Human Connectome Project Informatics: Quality Control, Database Services, and Data Visualization.” NeuroImage 80 (October): 202–19. https://doi.org/10.1016/j.neuroimage.2013.05.077.

4. 4. Raamana, Pradeep Reddy. 2018. “VisualQC: Assistive Tools for Easy aAnd Rigorous Quality Control of Neuroimaging Data.” April. https://doi.org/10.5281/ZENODO.1211365.

5. 5. SIG, niQC. 2019. “Neuroimaging Quality Control (NiQC) Special Interest Group at the INCF.” https://incf.github.io/niQC/tools.