NeuroImage (Mar 2020)
Correction of respiratory artifacts in MRI head motion estimates
- Damien A. Fair,
- Oscar Miranda-Dominguez,
- Abraham Z. Snyder,
- Anders Perrone,
- Eric A. Earl,
- Andrew N. Van,
- Jonathan M. Koller,
- Eric Feczko,
- M. Dylan Tisdall,
- Andre van der Kouwe,
- Rachel L. Klein,
- Amy E. Mirro,
- Jacqueline M. Hampton,
- Babatunde Adeyemo,
- Timothy O. Laumann,
- Caterina Gratton,
- Deanna J. Greene,
- Bradley L. Schlaggar,
- Donald J. Hagler, Jr.,
- Richard Watts,
- Hugh Garavan,
- Deanna M. Barch,
- Joel T. Nigg,
- Steven E. Petersen,
- Anders M. Dale,
- Sarah W. Feldstein-Ewing,
- Bonnie J. Nagel,
- Nico U.F. Dosenbach
Affiliations
- Damien A. Fair
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA; Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA; Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA; Corresponding author. Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA.
- Oscar Miranda-Dominguez
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA
- Abraham Z. Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Anders Perrone
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA
- Eric A. Earl
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA
- Andrew N. Van
- Department of Biomedical Engineering, Washington University, St. Louis, MO, USA
- Jonathan M. Koller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Eric Feczko
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Sciences University, Portland, OR, USA
- M. Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
- Rachel L. Klein
- Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA
- Amy E. Mirro
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
- Jacqueline M. Hampton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Timothy O. Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Caterina Gratton
- Department of Psychology & Neurology, Northwestern University, Chicago, IL, USA
- Deanna J. Greene
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Bradley L. Schlaggar
- Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University, Baltimore, MD, USA; Department of Pediatrics, Johns Hopkins University, Baltimore, MD, USA
- Donald J. Hagler, Jr.
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
- Richard Watts
- Department of Psychology, Yale University, New Haven, CT, USA
- Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
- Deanna M. Barch
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA; Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
- Joel T. Nigg
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA; Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA
- Steven E. Petersen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Department of Biomedical Engineering, Washington University, St. Louis, MO, USA; Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA; Department of Neuroscience, Washington University, St. Louis, MO, USA
- Anders M. Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Sarah W. Feldstein-Ewing
- Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA
- Bonnie J. Nagel
- Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA; Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA
- Nico U.F. Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA; Department of Biomedical Engineering, Washington University, St. Louis, MO, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA; Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA; Corresponding author. Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
- Journal volume & issue
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Vol. 208
p. 116400
Abstract
Head motion represents one of the greatest technical obstacles in magnetic resonance imaging (MRI) of the human brain. Accurate detection of artifacts induced by head motion requires precise estimation of movement. However, head motion estimates may be corrupted by artifacts due to magnetic main field fluctuations generated by body motion. In the current report, we examine head motion estimation in multiband resting state functional connectivity MRI (rs-fcMRI) data from the Adolescent Brain and Cognitive Development (ABCD) Study and comparison ‘single-shot’ datasets. We show that respirations contaminate movement estimates in functional MRI and that respiration generates apparent head motion not associated with functional MRI quality reductions. We have developed a novel approach using a band-stop filter that accurately removes these respiratory effects from motion estimates. Subsequently, we demonstrate that utilizing a band-stop filter improves post-processing fMRI data quality. Lastly, we demonstrate the real-time implementation of motion estimate filtering in our FIRMM (Framewise Integrated Real-Time MRI Monitoring) software package.
