Test-retest reliability of high angular resolution diffusion imaging acquisition within medial temporal lobe connections assessed via tract based spatial statistics, probabilistic tractography and a novel graph theory metric

Kuhn, Taylor; Gullett, Joseph M.; Nguyen, Peter; Boutzoukas, Angelique E; Ford, Anastasia; Colon-Perez, Luis M.; Triplett, William; Carney, Paul R.; Mareci, Thomas H.; Price, Catherine C.; Bauer, Russell M.

doi:10.1007/s11682-015-9425-1

Cited by 15 publications

(16 citation statements)

References 59 publications

(58 reference statements)

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“…Many studies have shown that different parcellation scales can provide a better description of local brain regions (Cammoun et al, 2012;Hagmann et al, 2007;Liu et al, 2017;Zhang, Savadjiev, Cai, et al, 2018). The scale of a white matter parcellation also affects the intersubject parcellation consistency (Cousineau et al, 2017;Besseling et al, 2012;Ciccarelli et al, 2003;Kristo et al, 2013;Papinutto et al, 2013;Pfefferbaum et al, 2003;Vollmar et al, 2010), there are many other measures available, for example, MD, apparent fiber density and number of fiber orientations (Cousineau et al, 2017;Kristo et al, 2013;Kuhn et al, 2016;Papinutto et al, 2013). In Supporting Information S1, we provide additional experimental results from relative difference of MD on whole brain white matter parcellation and anatomical fiber tract parcellation.…”

Section: Discussionmentioning

confidence: 99%

“…Third, in the present study, we chose volumetric overlap and FA to investigate white matter parcellation test–retest reproducibility. While these two measures are relatively representative test–retest reproducibility measures and have been used in many related studies (Cousineau et al, ; Besseling et al, ; Ciccarelli et al, ; Kristo et al, ; Papinutto et al, ; Pfefferbaum et al, ; Vollmar et al, ), there are many other measures available, for example, MD, apparent fiber density and number of fiber orientations (Cousineau et al, ; Kristo et al, ; Kuhn et al, ; Papinutto et al, ). In Supporting Information S1, we provide additional experimental results from relative difference of MD on whole brain white matter parcellation and anatomical fiber tract parcellation.…”

Section: Discussionmentioning

confidence: 99%

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Test–retest reproducibility of white matter parcellation using diffusion MRI tractography fiber clustering

Zhang

Norton

et al. 2019

Human Brain Mapping

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There are two popular approaches for automated white matter parcellation using diffusion MRI tractography, including fiber clustering strategies that group white matter fibers according to their geometric trajectories and cortical‐parcellation‐based strategies that focus on the structural connectivity among different brain regions of interest. While multiple studies have assessed test–retest reproducibility of automated white matter parcellations using cortical‐parcellation‐based strategies, there are no existing studies of test–retest reproducibility of fiber clustering parcellation. In this work, we perform what we believe is the first study of fiber clustering white matter parcellation test–retest reproducibility. The assessment is performed on three test–retest diffusion MRI datasets including a total of 255 subjects across genders, a broad age range (5–82 years), health conditions (autism, Parkinson's disease and healthy subjects), and imaging acquisition protocols (three different sites). A comprehensive evaluation is conducted for a fiber clustering method that leverages an anatomically curated fiber clustering white matter atlas, with comparison to a popular cortical‐parcellation‐based method. The two methods are compared for the two main white matter parcellation applications of dividing the entire white matter into parcels (i.e., whole brain white matter parcellation) and identifying particular anatomical fiber tracts (i.e., anatomical fiber tract parcellation). Test–retest reproducibility is measured using both geometric and diffusion features, including volumetric overlap (wDice) and relative difference of fractional anisotropy. Our experimental results in general indicate that the fiber clustering method produced more reproducible white matter parcellations than the cortical‐parcellation‐based method.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Test–retest reproducibility of white matter parcellation using diffusion MRI tractography fiber clustering

Zhang

Norton

et al. 2019

Human Brain Mapping

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“…The University of Florida Institutional Review Board approved this human study. One healthy subject was scanned 10 times over the course of 1 month, which provided 10 controlled brain data set from which to determine the network properties across different MRI acquisitions [ 35 , 36 ]. In all 10 sessions the subject was awake and scans were acquired roughly at the same time of the day (~7:00 a.m.).…”

Section: Methodsmentioning

confidence: 99%

Small Worldness in Dense and Weighted Connectomes

et al. 2016

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The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a 1-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property.

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“…Improved correction would be achieved by techniques that model the diffusion signal and correct for eddy-currents and head motion in one resampling step (Andersson and Sotiropoulos, 2016). More accurate modeling of the diffusion propagator function and the application of more complex tractography techniques to the newborn brain would result in more reproducible description of the structural connectome in the future (Kuhn et al, 2015;Lebel et al, 2012;Wakana et al, 2007). We found only a weak effect of the EPO treatment on the overall structural brain connectivity of preterm infants.…”

mentioning

confidence: 88%

Network based statistics reveals trophic and neuroprotective effect of early high dose erythropoetin on brain connectivity in very preterm infants

Jakab

Rüegger

Bucher

et al. 2019

Preprint

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Periventricular white matter injury is common in very preterm infants and it is associated with long term neurodevelopmental impairments. While evidence supports the protective effects of erythropoetin (EPO) in preventing injury, we currently lack the complete understanding of how EPO affects the emergence and maturation of anatomical brain connectivity and function. In this case-control study, connectomic analysis based on diffusion MRI tractography was applied to evaluate the effect of early high-dose EPO in preterm infants. A whole brain, network-level analysis revealed a sub-network of anatomical brain connections in which connectivity strengths were significantly stronger in the EPO group. This distributed network comprised connections predominantly in the frontal and temporal lobe bilaterally, and the effect of EPO was focused on the peripheral and feeder connections. EPO resulted in a globally increased clustering coefficient and higher local efficiency, while higher strength, efficiency and increased clustering was found for regions in the temporal lobe, supramarginal gyrus, inferior frontal gyrus, in the caudate and cingulate gyri. The connectivity network most affected by the EPO treatment showed a steeper increase in FA with age compared to the placebo group. These results demonstrate a weak but widespread effect of EPO on the structural connectivity network and a possible trophic effect of EPO reflected by increasing network segregation, predominantly in local connections.

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Test-retest reliability of high angular resolution diffusion imaging acquisition within medial temporal lobe connections assessed via tract based spatial statistics, probabilistic tractography and a novel graph theory metric

Cited by 15 publications

References 59 publications

Test–retest reproducibility of white matter parcellation using diffusion MRI tractography fiber clustering

Test–retest reproducibility of white matter parcellation using diffusion MRI tractography fiber clustering

Small Worldness in Dense and Weighted Connectomes

Network based statistics reveals trophic and neuroprotective effect of early high dose erythropoetin on brain connectivity in very preterm infants

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