- 著者
- Sanae Kato Epifanio Bagarinao Haruo Isoda Shuji Koyama Hirohisa Watanabe Satoshi Maesawa Daisuke Mori Kazuhiro Hara Masahisa Katsuno Minoru Hoshiyama Shinji Naganawa Norio Ozaki Gen Sobue
- 出版者
- Japanese Society for Magnetic Resonance in Medicine
- 雑誌
- Magnetic Resonance in Medical Sciences (ISSN:13473182)
- 巻号頁・発行日
- pp.mp.2020-0081, (Released:2020-10-27)
- 参考文献数
- 34
- 被引用文献数
- 4
Purpose: The estimation of functional connectivity (FC) measures using resting state functional MRI (fMRI) is often affected by head motion during functional imaging scans. Head motion is more common in the elderly than in young participants and could therefore affect the evaluation of age-related changes in brain networks. Thus, this study aimed to investigate the influence of head motion in FC estimation when evaluating age-related changes in brain networks.Methods: This study involved 132 healthy volunteers divided into 3 groups: elderly participants with high motion (OldHM, mean age (±SD) = 69.6 (±5.31), N = 44), elderly participants with low motion (OldLM, mean age (±SD) = 68.7 (±4.59), N = 43), and young adult participants with low motion (YugLM, mean age (±SD) = 27.6 (±5.26), N = 45). Head motion was quantified using the mean of the framewise displacement of resting state fMRI data. After preprocessing all resting state fMRI datasets, several resting state networks (RSNs) were extracted using independent component analysis (ICA). In addition, several network metrics were also calculated using network analysis. These FC measures were then compared among the 3 groups.Results: In ICA, the number of voxels with significant differences in RSNs was higher in YugLM vs. OldLM comparison than in YugLM vs. OldHM. In network analysis, all network metrics showed significant (P < 0.05) differences in comparisons involving low vs. high motion groups (OldHM vs. OldLM and OldHM vs. YugLM). However, there was no significant (P > 0.05) difference in the comparison involving the low motion groups (OldLM vs. YugLM).Conclusion: Our findings showed that head motion during functional imaging could significantly affect the evaluation of age-related brain network changes using resting state fMRI data.