Precision individual difference with multi-echo functional MRI
Poster No:
2317
Submission Type:
Abstract Submission
Authors:
Li-Xia Yuan1, Ziyang Chen2, Bing-Chen Shao1, Zhu-Qing Gong3, YiCheng Hsu4, Xi-Nian Zuo3, Hongjian He1
Institutions:
1MIAO Lab, School of Physics, Zhejiang University, Hangzhou, China, 2Research Center for Healthcare Data Science, Hangzhou, China, 3State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China, 4MR Research Collaboration Team, Siemens Healthineers Ltd., Shanghai, China
First Author:
Co-Author(s):
Zhu-Qing Gong
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, China
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, China
Xi-Nian Zuo
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, China
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, China
Introduction:
Depicting multifaced individual differences of spontaneous brain activity has become a central focus in the brain-imaging community, playing an essential role for understanding the human brain in health and disease (Dubois et al., 2016; Elliott et al., 2021; Raichle 2015; Xu et al., 2023). Estimates of individual differences are commonly contaminated by within-subject variation especially in fMRI, leading to unreliable findings (Elliott et al., 2021; Noble et al., 2019; Xing et al., 2018). Multi-echo fMRI (ME-fMRI) is potential for enhancing neural signals and removing non-neural signals relative to traditional sing-echo fMRI (SE-fMRI) (Kundu et al., 2012, 2013, 2017; Lynch et al., 2020; Posse et al., 1999; Power et al., 2018). However, the benefit of ME-fMRI for precision individual difference in spontaneous brain activity has not been systematically investigated yet, which is vital for both neuroscience and clinical application.
Methods:
We explicitly identified the true individual difference (i.e., between-subject variation) and within-subject variation and comprehensively explored the reliability of ME-fMRI for mapping individual difference based on test-retest design. With both the short- and long-term test-retest dataset, we first detected within-subject difference, between-subject difference, and reliability of three fMRI intrinsic metrics (i.e., amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC)) across the whole-brain and seven subnetworks. Second, we explored the experimental implications of enhanced reliability on saving samples by investigating the interplay between reliability, sample size, and effect size. Then, we obtained the methodological implications of enhanced reliability by assessing the shortened scanning duration. Finally, we probed the benefit of enhanced reliability for validity improvement with a well-studied within-subject rfMRI design, i.e., the difference between statuses of eyes open and eyes close. To provide a benchmark for ME-fMRI, SE-fMRI dataset with almost the same scanning parameters except for TE was also acquired for both vertex-level and network-level analysis.
Results:
For both short- and long-term test-retest design, ME-fMRI suppresses random and non-neural noise to smaller within-subject variability and enhances neural signal to larger between-subject variability across almost whole-brain, leading to reliable and precision individual differences for all the intrinsic metrics compared with SE-fMRI (Fig. 1 and Fig. 2a). Notably, the individual differences of auditory and somatosensory network were greatly underestimated in SE-fMRI. To achieve a certain reliability with ME-fMRI, the sample size and experimental costs can be reduced for 14%, 17%, and 29%, or the scan duration can be shortened for 54%, 42%, and 43% for ALFF, ReHo, and VMHC, respectively, relative to SE-fMRI. Furthermore, the validity to capture the individual difference between status of eyes open and eyes close are remarkably promoted with ME-fMRI for ALFF, ReHo, and VMHC (Fig. 2b).
·Fig.1 Comparison of reliability (ICC), between-subject variance (Vb), and with-subject variance (Vw) of ALFF, ReHo, and VMHC between SE- and ME-fMRI in short- (a) and long- (b) test-retest design.
·Fig.2 Reliability enhancement by decreasing with-subject variance (Vw) and increasing between-subject variance (Vb) and promoted validity for differentiating eyes open and eyes close with ME-fMRI.
Conclusions:
Our study comprehensively investigated the benefit of ME-fMRI for reliable individual difference by decreasing within-subject variability and increasing between-subject variability and explored its advantages on reducing sample size, shortening scan duration, and enhancing validity, which facilitates detailed characterization of individual brain organization and the translation of ME-fMRI to clinical applications.
Modeling and Analysis Methods:
Task-Independent and Resting-State Analysis 2
Novel Imaging Acquisition Methods:
BOLD fMRI 1
Keywords:
FUNCTIONAL MRI
Other - Individual Difference; Reliability; Multi-echo fMRI; Spontaneous Brain Activity; Sample Size; Scan Duration; Validity
1|2Indicates the priority used for review
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