Short-term test–retest reliability of resting state fMRI metrics in children with and without attention-deficit/hyperactivity disorder

Somandepalli, Krishna; Kelly, Clare; Reiss, Philip T.; Zuo, Xi; Craddock, R. Cameron; Yan, Chao‐Gan; Petkova, Eva; Castellanos, F. Xavier; Milham, Michael P.; Martino, Adriana Di

doi:10.1016/j.dcn.2015.08.003

Cited by 71 publications

(62 citation statements)

References 69 publications

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“…Second, this research was conducted in healthy, non-adolescent individuals. Variance between subjects may change slightly in different populations, e.g., clinical or adolescent populations, which can affect the calculation of reliability; for example, test-retest reliability has been shown to differ between ADHD and normal populations (Somandepalli et al, 2015). However, this is not expected to change the estimate of site effects.…”

Section: Discussionmentioning

confidence: 99%

Multisite reliability of MR-based functional connectivity

et al. 2017

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Recent years have witnessed an increasing number of multisite MRI functional connectivity (fcMRI) studies. While multisite studies are an efficient way to speed up data collection and increase sample sizes, especially for rare clinical populations, any effects of site or MRI scanner could ultimately limit power and weaken results. Little data exists on the stability of functional connectivity measurements across sites and sessions. In this study, we assess the influence of site and session on resting state functional connectivity measurements in a healthy cohort of traveling subjects (8 subjects scanned twice at each of 8 sites) scanned as part of the North American Prodrome Longitudinal Study (NAPLS). Reliability was investigated in three types of connectivity analyses: (1) seed-based connectivity with posterior cingulate cortex (PCC), right motor cortex (RMC), and left thalamus (LT) as seeds; (2) the intrinsic connectivity distribution (ICD), a voxel-wise connectivity measure; and (3) matrix connectivity, a whole-brain, atlas-based approach assessing connectivity between nodes. Contributions to variability in connectivity due to subject, site, and day-of-scan were quantified and used to assess between-session (test-retest) reliability in accordance with Generalizability Theory. Overall, no major site, scanner manufacturer, or day-of-scan effects were found for the univariate connectivity analyses; instead, subject effects dominated relative to the other measured factors. However, summaries of voxel-wise connectivity were found to be sensitive to site and scanner manufacturer effects. For all connectivity measures, although subject variance was three times the site variance, the residual represented 60–80% of the variance, indicating that connectivity differed greatly from scan to scan independent of any of the measured factors (i.e., subject, site, and day-of-scan). Thus, for a single 5 min scan, reliability across connectivity measures was poor (ICC=0.07–0.17), but increases with increasing scan duration (ICC=0.21–0.36 at 25 min). The limited effects of site and scanner manufacturer support the use of multisite studies, such as NAPLS, as a viable means of collecting data on rare populations and increasing power in univariate functional connectivity studies. However, the results indicate that aggregation of fcMRI data across longer scan durations is necessary to increase the reliability of connectivity estimates at the single-subject level.

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Section: Discussionmentioning

confidence: 99%

Multisite reliability of MR-based functional connectivity

et al. 2017

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“…There are many test‐retest reliability studies on the static FC. For example, it has been suggested that the test‐retest reliability of the static FC is fair‐to‐good when examined in both region‐ [Wang et al, ] and voxel‐wise manners [Shehzad et al, ; Somandepalli et al, ], and the static FC‐based brain network properties are still satisfactorily reliable [Andellinia et al, ]. However, there are few test‐retest reliability studies on dynamic FC or dynamic FCT.…”

Section: Discussionmentioning

confidence: 99%

Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification

Chen

Zhang

et al. 2017

Human Brain Mapping

163

123

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Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for diagnosing various neurodegenerative diseases, including Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Current studies mainly construct the FC networks between grey matter (GM) regions of the brain based on temporal co-variations of the blood oxygenation level-dependent (BOLD) signals, which reflects the synchronized neural activities. However, it was rarely investigated whether the FC detected within the white matter (WM) could provide useful information for diagnosis. Motivated by the recently proposed functional correlation tensors (FCT) computed from RS-fMRI and used to characterize the structured pattern of local FC in the WM, we propose in this paper a novel MCI classification method based on the information conveyed by both the FC between the GM regions and that within the WM regions. Specifically, in the WM, the tensor-based metrics (e.g., fractional anisotropy [FA], similar to the metric calculated based on diffusion tensor imaging [DTI]) are first calculated based on the FCT and then summarized along each of the major WM fiber tracts connecting each pair of the brain GM regions. This could capture the functional information in the WM, in a similar network structure as the FC network constructed for the GM, based only on the same RS-fMRI data. Moreover, a sliding window approach is further used to partition the voxel-wise BOLD signal into multiple short overlapping segments. Then, both the FC and FCT between each pair of the brain regions can be calculated based on the BOLD signal segments in the GM and WM, respectively. In such a way, our method can generate dynamic FC and dynamic FCT to better capture functional information in both GM and WM and further integrate them together by using our developed feature extraction, selection, and ensemble learning algorithms. The experimental results verify that the dynamic FCT can provide valuable functional information in the WM; by combining it with the dynamic FC in the GM, the diagnosis accuracy for MCI subjects can be significantly improved even using RS-fMRI data alone.

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“…These short-term best-case reliability estimates yielded moderate-to-high values. Still, for most indices, controls were significantly more reliable than patients in some brain regions (100). These preliminary findings highlight the importance of examining longer-term (i.e., one week) test-retest reliability across ages (beyond the one small study documenting test-retest reliability in children (101)), by sex, and in each clinical condition-of-interest as part of the foundational work required to build a scientific edifice.…”

Section: Principal Measures and Approachesmentioning

confidence: 92%

“…In this regard, R-fMRI has a ways to go (but see the Consortium on Reliability and Replicability dataset for a novel resource (99)). In ADHD, one study examined short-term (intra-session) test-retest reliability of four R-fMRI indices (ALFF and fractional ALFF, ReHo, and FC of posterior cingulate cortex (PCC), a core DMN node) (100). These short-term best-case reliability estimates yielded moderate-to-high values.…”

Section: Principal Measures and Approachesmentioning

confidence: 99%

Intrinsic Functional Connectivity in Attention-Deficit/Hyperactivity Disorder: A Science in Development

Castellanos

Aoki

2016

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

144

154

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Functional magnetic resonance imaging (fMRI) without an explicit task, i.e., resting state fMRI, of individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) is growing rapidly. Early studies were unaware of the vulnerability of this method to even minor degrees of head motion, a major concern in the field. Recent efforts are implementing various strategies to address this source of artifact along with a growing set of analytical tools. Availability of the ADHD-200 Consortium dataset, a large-scale multi-site repository, is facilitating increasingly sophisticated approaches. In parallel, investigators are beginning to explicitly test the replicability of published findings. In this narrative review, we sketch out broad, overarching hypotheses being entertained while noting methodological uncertainties. Current hypotheses implicate the interplay of default, cognitive control (frontoparietal) and attention (dorsal, ventral, salience) networks in ADHD; functional connectivities of reward-related and amygdala-related circuits are also supported as substrates for dimensional aspects of ADHD. Before these can be further specified and definitively tested, we assert the field must take on the challenge of mapping the “topography” of the analytical space, i.e., determining the sensitivities of results to variations in acquisition, analysis, demographic and phenotypic parameters. Doing so with openly available datasets will provide the needed foundation for delineating typical and atypical developmental trajectories of brain structure and function in neurodevelopmental disorders including ADHD when applied to large-scale multi-site prospective longitudinal studies such as the forthcoming Adolescent Brain Cognitive Development study.

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Short-term test–retest reliability of resting state fMRI metrics in children with and without attention-deficit/hyperactivity disorder

Cited by 71 publications

References 69 publications

Multisite reliability of MR-based functional connectivity

Multisite reliability of MR-based functional connectivity

Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification

Intrinsic Functional Connectivity in Attention-Deficit/Hyperactivity Disorder: A Science in Development

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