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Test-Retest Reliability of Graph Theoretic Metrics in Adolescent Brains.

ABSTRACT: Graph theory analysis of structural brain networks derived from diffusion tensor imaging (DTI) has become a popular analytical method in neuroscience, enabling advanced investigations of neurological and psychiatric disorders. The purpose of this study was to investigate (1) the effects of edge weighting schemes and (2) the effects of varying interscan periods on graph metrics within the adolescent brain. We compared a binary (B) network definition with three weighting schemes: fractional anisotropy (FA), streamline count, and streamline count with density and length correction (SDL). Two commonly used global and two local graph metrics were examined. The analysis was conducted with two groups of adolescent volunteers who received DTI scans either 12 weeks apart (16.62?±?1.10 years) or within the same scanning session (30?min apart) (16.65?±?1.14 years). The intraclass correlation coefficient was used to assess test-retest reliability and the coefficient of variation (CV) was used to assess precision. On average, each edge scheme produced reliable results at both time intervals. Weighted measures outperformed binary measures, with SDL weights producing the most reliable metrics. All edge schemes except FA displayed high CV values, leaving FA as the only edge scheme that consistently showed high precision while also producing reliable results. Overall findings suggest that FA weights are more suited for DTI connectome studies in adolescents.

SUBMITTER: Yuan JP

PROVIDER: S-EPMC6444894 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Test-Retest Reliability of Graph Theoretic Metrics in Adolescent Brains.

Yuan Justin P JP Henje Blom Eva E Flynn Trevor T Chen Yiran Y Ho Tiffany C TC Connolly Colm G CG Dumont Walter Rebecca A RA Yang Tony T TT Xu Duan D Tymofiyeva Olga O

Brain connectivity 20181226 2

Graph theory analysis of structural brain networks derived from diffusion tensor imaging (DTI) has become a popular analytical method in neuroscience, enabling advanced investigations of neurological and psychiatric disorders. The purpose of this study was to investigate (1) the effects of edge weighting schemes and (2) the effects of varying interscan periods on graph metrics within the adolescent brain. We compared a binary (B) network definition with three weighting schemes: fractional anisot ...[more]

PMID: 30398373

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Project description:Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ?20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (?90%) exhibited good reliability (0.6< ICC <0.74). For global and nodal measures, reliability was generally threshold-sensitive and varied among both network metrics and hemoglobin concentration signals. Specifically, the majority of global metrics exhibited fair to excellent reliability, with notably higher ICC values for the clustering coefficient (HbO: 0.76; HbR: 0.78; HbT: 0.53) and global efficiency (HbO: 0.76; HbR: 0.70; HbT: 0.78). Similarly, both nodal degree and efficiency measures also showed fair to excellent reliability across nodes (degree: 0.52?0.84; efficiency: 0.50?0.84); reliability was concordant across HbO, HbR and HbT and was significantly higher than that of nodal betweenness (0.28?0.68). Together, our results suggest that most graph-theoretical network metrics derived from fNIRS are TRT reliable and can be used effectively for brain network research. This study also provides important guidance on the choice of network metrics of interest for future applied research in developmental and clinical neuroscience.

Project description:BackgroundNeurocognitive testing is an important concussion evaluation tool, but for neurocognitive tests to be useful, their psychometric properties must be well established. Test-retest reliability of computerized neurocognitive tests can influence their clinical utility. The reliability for a commonly used computerized neurocognitive test, CNS Vital Signs, is not well established. The purpose of this study was to examine test-retest reliability and reliable change indices for CNS Vital Signs in a healthy, physically active college population.HypothesisCNS Vital Signs yields acceptable test-retest reliability, with greater reliability between the second and third test administration compared with between the first and second administration.Study designCohort study.Level of evidenceLevel 3.MethodsForty healthy, active volunteers (16 men, 24 women; mean age, 21.05 ± 2.17 years) reported to a clinical laboratory for 3 sessions, 1 week apart. At each session, participants were administered CNS Vital Signs. Outcomes included standard scores for the following CNS Vital Signs domains: verbal memory, visual memory, psychomotor speed, cognitive flexibility, complex attention, processing speed, reaction time, executive functioning, and reasoning.ResultsParticipants performed significantly better on the second session and/or third session than they did on the first testing session on 6 of 9 neurocognitive domains. Pearson r test-retest correlations between sessions ranged from 0.11 to 0.87. Intraclass correlation coefficients ranged from 0.10 to 0.86.ConclusionClinicians should consider using reliable change indices to account for practice effects, identify meaningful score changes due to pathology, and inform clinical decisions.Clinical relevanceThis study highlights the importance of clinicians understanding the psychometric properties of computerized neurocognitive tests when using them in the management of sport-related concussion. If CNS Vital Signs is administered twice within a small time frame (such as 1 week), athletes should be expected to improve between the first and second administration.

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Test-Retest Reliability of Graph Theoretic Metrics in Adolescent Brains.

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Test-Retest Reliability of Graph Theoretic Metrics in Adolescent Brains.

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