Correction of respiratory artifacts in MRI head motion estimates
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 fie...
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| Veröffentlicht in: | NeuroImage (Orlando, Fla.) Jg. 208; S. 116400 |
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
Elsevier Inc
01.03.2020
Elsevier Limited Elsevier |
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| ISSN: | 1053-8119, 1095-9572, 1095-9572 |
| Online-Zugang: | Volltext |
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| 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.
•Respiratory perturbations of the main field inflate fMRI head motion estimates.•Breathing-related head motion artifacts compromise functional connectivity quality.•Notch filtering motion estimates (respiratory frequency band) improves data quality.•Motion estimate filtering can be achieved in real-time with FIRMM software. |
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| AbstractList | 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. 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. •Respiratory perturbations of the main field inflate fMRI head motion estimates.•Breathing-related head motion artifacts compromise functional connectivity quality.•Notch filtering motion estimates (respiratory frequency band) improves data quality.•Motion estimate filtering can be achieved in real-time with FIRMM software. 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.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. |
| ArticleNumber | 116400 |
| Author | Fair, Damien A. van der Kouwe, Andre Garavan, Hugh Laumann, Timothy O. Gratton, Caterina Feldstein-Ewing, Sarah W. Earl, Eric A. Dosenbach, Nico U.F. Perrone, Anders Klein, Rachel L. Mirro, Amy E. Hampton, Jacqueline M. Petersen, Steven E. Adeyemo, Babatunde Watts, Richard Van, Andrew N. Schlaggar, Bradley L. Nigg, Joel T. Feczko, Eric Koller, Jonathan M. Miranda-Dominguez, Oscar Barch, Deanna M. Snyder, Abraham Z. Dale, Anders M. Tisdall, M. Dylan Nagel, Bonnie J. Greene, Deanna J. Hagler, Donald J. |
| AuthorAffiliation | 7 Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA 8 Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Sciences University, Portland OR, USA 2 Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA 10 Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA USA 13 Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neurology; Johns Hopkins University; Baltimore; MD; USA Department of Pediatrics; Johns Hopkins University 4 Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA 11 Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA 17 Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA 16 Department of Psychiatry, University of Vermont, Burlington, VT, USA 20 Program in Occupational Therapy, Washington University School of Medicine, St |
| AuthorAffiliation_xml | – name: 12 Department of Psychology & Neurology, Northwestern University, Chicago, IL, USA – name: 15 FAS Brain Imaging Center, Yale University, New Haven, CT, USA – name: 2 Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA – name: 18 Department of Neuroscience, Washington University, St. Louis, MO, USA – name: 8 Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Sciences University, Portland OR, USA – name: 11 Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA – name: 6 Department of Biomedical Engineering, Washington University, St. Louis, MO, USA – name: 14 Department of Radiology, University of California San Diego, La Jolla, CA, USA – name: 10 Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA USA – name: 17 Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA – name: 20 Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA – name: 13 Kennedy Krieger Institute, Baltimore, MD, USA; Department of Neurology; Johns Hopkins University; Baltimore; MD; USA Department of Pediatrics; Johns Hopkins University – name: 16 Department of Psychiatry, University of Vermont, Burlington, VT, USA – name: 19 Department of Neurosciences, University of California San Diego, La Jolla, CA, USA – name: 1 Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA – name: 3 Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA – name: 5 Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA – name: 9 Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – name: 4 Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA – name: 7 Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA |
| Author_xml | – sequence: 1 givenname: Damien A. surname: Fair fullname: Fair, Damien A. email: faird@umn.edu organization: Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA – sequence: 2 givenname: Oscar surname: Miranda-Dominguez fullname: Miranda-Dominguez, Oscar organization: Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA – sequence: 3 givenname: Abraham Z. surname: Snyder fullname: Snyder, Abraham Z. organization: Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA – sequence: 4 givenname: Anders surname: Perrone fullname: Perrone, Anders organization: Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA – sequence: 5 givenname: Eric A. surname: Earl fullname: Earl, Eric A. organization: Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA – sequence: 6 givenname: Andrew N. surname: Van fullname: Van, Andrew N. organization: Department of Biomedical Engineering, Washington University, St. Louis, MO, USA – sequence: 7 givenname: Jonathan M. surname: Koller fullname: Koller, Jonathan M. organization: Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA – sequence: 8 givenname: Eric surname: Feczko fullname: Feczko, Eric organization: Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA – sequence: 9 givenname: M. Dylan surname: Tisdall fullname: Tisdall, M. Dylan organization: Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA – sequence: 10 givenname: Andre surname: van der Kouwe fullname: van der Kouwe, Andre organization: Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA – sequence: 11 givenname: Rachel L. surname: Klein fullname: Klein, Rachel L. organization: Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA – sequence: 12 givenname: Amy E. surname: Mirro fullname: Mirro, Amy E. organization: Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA – sequence: 13 givenname: Jacqueline M. surname: Hampton fullname: Hampton, Jacqueline M. organization: Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA – sequence: 14 givenname: Babatunde surname: Adeyemo fullname: Adeyemo, Babatunde organization: Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA – sequence: 15 givenname: Timothy O. surname: Laumann fullname: Laumann, Timothy O. organization: Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA – sequence: 16 givenname: Caterina surname: Gratton fullname: Gratton, Caterina organization: Department of Psychology & Neurology, Northwestern University, Chicago, IL, USA – sequence: 17 givenname: Deanna J. surname: Greene fullname: Greene, Deanna J. organization: Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA – sequence: 18 givenname: Bradley L. surname: Schlaggar fullname: Schlaggar, Bradley L. organization: Kennedy Krieger Institute, Baltimore, MD, USA – sequence: 19 givenname: Donald J. surname: Hagler fullname: Hagler, Donald J. organization: Department of Radiology, University of California San Diego, La Jolla, CA, USA – sequence: 20 givenname: Richard surname: Watts fullname: Watts, Richard organization: Department of Psychology, Yale University, New Haven, CT, USA – sequence: 21 givenname: Hugh surname: Garavan fullname: Garavan, Hugh organization: Department of Psychiatry, University of Vermont, Burlington, VT, USA – sequence: 22 givenname: Deanna M. surname: Barch fullname: Barch, Deanna M. organization: Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA – sequence: 23 givenname: Joel T. surname: Nigg fullname: Nigg, Joel T. organization: Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA – sequence: 24 givenname: Steven E. surname: Petersen fullname: Petersen, Steven E. organization: Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA – sequence: 25 givenname: Anders M. surname: Dale fullname: Dale, Anders M. organization: Department of Radiology, University of California San Diego, La Jolla, CA, USA – sequence: 26 givenname: Sarah W. surname: Feldstein-Ewing fullname: Feldstein-Ewing, Sarah W. organization: Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, USA – sequence: 27 givenname: Bonnie J. surname: Nagel fullname: Nagel, Bonnie J. organization: Department of Behavioral Neuroscience, Oregon Health & Sciences University, Portland, OR, USA – sequence: 28 givenname: Nico U.F. surname: Dosenbach fullname: Dosenbach, Nico U.F. email: ndosenbach@wustl.edu organization: Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31778819$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | 2019 The Authors Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved. 2019. The Authors |
| Copyright_xml | – notice: 2019 The Authors – notice: Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved. – notice: 2019. The Authors |
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| DOI | 10.1016/j.neuroimage.2019.116400 |
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