Reproducibility of functional connectivity metrics estimated from resting-state functional MRI with differences in days, coils, and global signal regression

Sanae Kato, Epifanio Bagarinao, Haruo Isoda, Shuji Koyama, Hirohisa Watanabe, Satoshi Maesawa, Kazuhiro Hara, Masahisa Katsuno, Shinji Naganawa, Norio Ozaki, Gen Sobue

Research output: Contribution to journalArticlepeer-review

Abstract

In multisite studies, differences in imaging acquisition systems could affect the reproducibility of the results when examining changes in brain function using resting-state functional magnetic resonance imaging (rs-fMRI). This is also important for longitudinal studies, in which changes in equipment settings can occur. This study examined the reproducibility of functional connectivity (FC) metrics estimated from rs-fMRI data acquired using scanner receiver coils with different numbers of channels. This study involved 80 rs-fMRI datasets from 20 healthy volunteers scanned in two independent imaging sessions using both 12- and 32-channel coils for each session. We used independent component analysis (ICA) to evaluate the FC of canonical resting-state networks (RSNs) and graph theory to calculate several whole-brain network metrics. The effect of global signal regression (GSR) as a preprocessing step was also considered. Comparisons within and between receiver coils were performed. Irrespective of the GSR, RSNs derived from rs-fMRI data acquired using the same receiver coil were reproducible, but not from different receiver coils. However, both the GSR and the channel count of the receiver coil have discernible effects on the reproducibility of network metrics estimated using whole-brain network analysis. The data acquired using the 32-channel coil tended to have better reproducibility than those acquired using the 12-channel coil. Our findings suggest that the reproducibility of FC metrics estimated from rs-fMRI data acquired using different receiver coils showed some level of dependence on the preprocessing method and the type of analysis performed.

Original languageEnglish
Pages (from-to)298-310
Number of pages13
JournalRadiological Physics and Technology
Volume15
Issue number4
DOIs
Publication statusPublished - 12-2022

All Science Journal Classification (ASJC) codes

  • Radiation
  • Physical Therapy, Sports Therapy and Rehabilitation
  • Radiology Nuclear Medicine and imaging

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