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; 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

doi:10.1016/j.neuroimage.2019.116400

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, Richard WattsHugh Garavan, Deanna M. Barch, Joel T. Nigg, Steven E. Petersen, Anders M. Dale, Sarah W. Feldstein-Ewing, Bonnie J. Nagel, Nico U.F. Dosenbach

Research output: Contribution to journal › Article › peer-review

104 Scopus citations

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.

Original language	English (US)
Article number	116400
Journal	NeuroImage
Volume	208
DOIs	https://doi.org/10.1016/j.neuroimage.2019.116400
State	Published - Mar 2020

ASJC Scopus subject areas

Neurology
Cognitive Neuroscience

Access to Document

10.1016/j.neuroimage.2019.116400

Cite this

Fair, D. A., Miranda-Dominguez, O., Snyder, A. Z., Perrone, A., Earl, E. A., Van, A. N., Koller, J. M., Feczko, E., Tisdall, M. D., van der Kouwe, A., Klein, R. L., Mirro, A. E., Hampton, J. M., Adeyemo, B., Laumann, T. O., Gratton, C., Greene, D. J., Schlaggar, B. L., Hagler, D. J., ... Dosenbach, N. U. F. (2020). Correction of respiratory artifacts in MRI head motion estimates. NeuroImage, 208, Article 116400. https://doi.org/10.1016/j.neuroimage.2019.116400

Fair, DA, Miranda-Dominguez, O, Snyder, AZ, Perrone, A, Earl, EA, Van, AN, Koller, JM, Feczko, E, Tisdall, MD, van der Kouwe, A, Klein, RL, Mirro, AE, Hampton, JM, Adeyemo, B, Laumann, TO, Gratton, C, Greene, DJ, Schlaggar, BL, Hagler, DJ, Watts, R, Garavan, H, Barch, DM, Nigg, JT, Petersen, SE, Dale, AM, Feldstein-Ewing, SW, Nagel, BJ & Dosenbach, NUF 2020, 'Correction of respiratory artifacts in MRI head motion estimates', NeuroImage, vol. 208, 116400. https://doi.org/10.1016/j.neuroimage.2019.116400

@article{1b96ed42fb864e7084437a680d88d262,

title = "Correction of respiratory artifacts in MRI head motion estimates",

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 {\textquoteleft}single-shot{\textquoteright} 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.",

author = "Fair, {Damien A.} and Oscar Miranda-Dominguez and Snyder, {Abraham Z.} and Anders Perrone and Earl, {Eric A.} and Van, {Andrew N.} and Koller, {Jonathan M.} and Eric Feczko and Tisdall, {M. Dylan} and {van der Kouwe}, Andre and Klein, {Rachel L.} and Mirro, {Amy E.} and Hampton, {Jacqueline M.} and Babatunde Adeyemo and Laumann, {Timothy O.} and Caterina Gratton and Greene, {Deanna J.} and Schlaggar, {Bradley L.} and Hagler, {Donald J.} and Richard Watts and Hugh Garavan and Barch, {Deanna M.} and Nigg, {Joel T.} and Petersen, {Steven E.} and Dale, {Anders M.} and Feldstein-Ewing, {Sarah W.} and Nagel, {Bonnie J.} and Dosenbach, {Nico U.F.}",

note = "Publisher Copyright: {\textcopyright} 2019 The Authors",

year = "2020",

month = mar,

doi = "10.1016/j.neuroimage.2019.116400",

language = "English (US)",

volume = "208",

journal = "NeuroImage",

issn = "1053-8119",

publisher = "Academic Press Inc.",

}

TY - JOUR

T1 - Correction of respiratory artifacts in MRI head motion estimates

AU - Fair, Damien A.

AU - Miranda-Dominguez, Oscar

AU - Snyder, Abraham Z.

AU - Perrone, Anders

AU - Earl, Eric A.

AU - Van, Andrew N.

AU - Koller, Jonathan M.

AU - Feczko, Eric

AU - Tisdall, M. Dylan

AU - van der Kouwe, Andre

AU - Klein, Rachel L.

AU - Mirro, Amy E.

AU - Hampton, Jacqueline M.

AU - Adeyemo, Babatunde

AU - Laumann, Timothy O.

AU - Gratton, Caterina

AU - Greene, Deanna J.

AU - Schlaggar, Bradley L.

AU - Hagler, Donald J.

AU - Watts, Richard

AU - Garavan, Hugh

AU - Barch, Deanna M.

AU - Nigg, Joel T.

AU - Petersen, Steven E.

AU - Dale, Anders M.

AU - Feldstein-Ewing, Sarah W.

AU - Nagel, Bonnie J.

AU - Dosenbach, Nico U.F.

PY - 2020/3

Y1 - 2020/3

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85076429735&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85076429735&partnerID=8YFLogxK

U2 - 10.1016/j.neuroimage.2019.116400

DO - 10.1016/j.neuroimage.2019.116400

M3 - Article

C2 - 31778819

AN - SCOPUS:85076429735

SN - 1053-8119

VL - 208

JO - NeuroImage

JF - NeuroImage

M1 - 116400

ER -

Correction of respiratory artifacts in MRI head motion estimates

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this