Real-time motion monitoring improves functional MRI data quality in infants

Carolina Badke D'Andrea, Jeanette K. Kenley, David F. Montez, Amy E. Mirro, Ryland L. Miller, Eric A. Earl, Jonathan M. Koller, Sooyeon Sung, Essa Yacoub, Jed T. Elison, Damien A. Fair, Nico U.F. Dosenbach, Cynthia E. Rogers, Christopher D. Smyser, Deanna J. Greene

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Imaging the infant brain with MRI has improved our understanding of early neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are typically scanned while asleep, they commonly exhibit motion during scanning causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Here, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD ≤ 0.2 mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging.

Original languageEnglish (US)
Article number101116
JournalDevelopmental Cognitive Neuroscience
Volume55
DOIs
StatePublished - Jun 2022

Bibliographical note

Publisher Copyright:
© 2022 The Authors

Keywords

  • Functional MRI
  • Head motion
  • Infant brain
  • Neurodevelopment
  • Neuroimaging

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