The Impact of In-Scanner Head Motion on Structural Connectivity Derived from Diffusion Tensor Imaging

ABSTRACTMultiple studies have shown that data quality is a critical confound in the construction of brain networks derived from functional MRI. This problem is particularly relevant for studies of human brain development where important variables (such as participant age) are correlated with data quality. Nevertheless, the impact of head motion on estimates of structural connectivity derived from diffusion tractography methods remains poorly characterized. Here, we evaluated the impact of in-scanner head motion on structural connectivity using a sample of 949 participants (ages 8-23 years old) who passed a rigorous quality assessment protocol for diffusion tensor imaging (DTI) acquired as part of the Philadelphia Neurodevelopmental Cohort. Structural brain networks were constructed for each participant using both deterministic and probabilistic tractography. We hypothesized that subtle variation in head motion would systematically bias estimates of structural connectivity and confound developmental inference, as observed in previous studies of functional connectivity. Even following quality assurance and retrospective correction for head motion, eddy currents, and field distortions, in-scanner head motion significantly impacted the strength of structural connectivity in a consistency-and length-dependent manner. Specifically, increased head motion was associated with reduced estimates of structural connectivity for high-consistency network edges, which included both short-and long-range connections. In contrast, motion inflated estimates of structural connectivity for low-consistency network edges that were primarily shorter-range. Finally, we demonstrate that age-related differences in head motion can both inflate and obscure developmental inferences on structural connectivity. Taken together, these data delineate the systematic impact of head motion on structural connectivity, and provide a critical context for identifying motion-related confounds in studies of structural brain network development.

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Optimization of epilepsy surgery through virtual resections on individual structural brain networks

10.21203/rs.3.rs-344720/v1 ◽

2021 ◽

Author(s):

Ida A. Nissen ◽

Cornelis J. Stam ◽

Elisabeth C.W. Straaten ◽

Ana P. Millán ◽

Linda Douw ◽

...

Keyword(s):

Epilepsy Surgery ◽

Diffusion Tensor ◽

Brain Networks ◽

Sir Model ◽

Correct Identification ◽

Epileptogenic Zone ◽

Maximal Effect ◽

Seizure Propagation ◽

The Impact ◽

Structural Brain

Abstract BackgroundThe success of epilepsy surgery in patients with refractory epilepsy depends upon correct identification of the epileptogenic zone (EZ) and an optimal choice of the resection area. In this study we developed individualized computational models based upon structural brain networks to explore the impact of different virtual resections on the propagation of seizures.MethodsThe propagation of seizures was modelled as an epidemic process (susceptible-infected-recovered (SIR) model) on individual structural networks derived from presurgical diffusion tensor imaging (DTI) in 19 patients. The candidate connections for the virtual resection were all connections from the clinically hypothesized EZ, from which the seizures were modelled to start, to other brain areas. As a computationally feasible surrogate for the SIR model, we also removed the connections that maximally reduced the Eigenvector Centrality (EC) (large values indicate network hubs) of the hypothesized EZ, with a large reduction meaning a large effect. The optimal combination of connections to be removed for a maximal effect were found using simulated annealing. For comparison, the same number of connections were removed randomly, or based on measures that quantify the importance of a node or connection within the network.ResultsWe found that 90% of the effect (defined as reduction of EC of the hypothesized EZ) could already be obtained by removing substantially less than 90% of the connections. Thus, a smaller, optimized, virtual resection achieved almost the same effect as the actual surgery yet at a considerably smaller cost, sparing on average 27.49% (standard deviation: 4.65%) of the connections. Furthermore, the maximally effective connections linked the hypothesized EZ to hubs. Finally, the optimized resection was more effective than random removal of the same number of connections, and equally or more effective than removal based on structural network characteristics.ConclusionThe approach of using reduced EC as a surrogate for simulating seizure propagation can suggest more restrictive resection strategies, whilst obtaining an almost optimal effect on reducing seizure propagation, by taking into account the unique topology of individual structural brain networks of patients.

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Progressive Gender Differences of Structural Brain Networks in Healthy Adults: A Longitudinal, Diffusion Tensor Imaging Study

PLoS ONE ◽

10.1371/journal.pone.0118857 ◽

2015 ◽

Vol 10 (3) ◽

pp. e0118857 ◽

Cited By ~ 29

Author(s):

Yu Sun ◽

Renick Lee ◽

Yu Chen ◽

Simon Collinson ◽

Nitish Thakor ◽

...

Keyword(s):

Gender Differences ◽

Diffusion Tensor Imaging ◽

Diffusion Tensor ◽

Brain Networks ◽

Imaging Study ◽

Healthy Adults ◽

Longitudinal Diffusion ◽

Diffusion Tensor Imaging Study ◽

Structural Brain

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Optimization of epilepsy surgery through virtual resections on individual structural brain networks

Scientific Reports ◽

10.1038/s41598-021-98046-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Ida A. Nissen ◽

Ana P. Millán ◽

Cornelis J. Stam ◽

Elisabeth C. W. van Straaten ◽

Linda Douw ◽

...

Keyword(s):

Epilepsy Surgery ◽

Diffusion Tensor ◽

Brain Networks ◽

Sir Model ◽

Correct Identification ◽

Epileptogenic Zone ◽

Maximal Effect ◽

Seizure Propagation ◽

The Impact ◽

Structural Brain

AbstractThe success of epilepsy surgery in patients with refractory epilepsy depends upon correct identification of the epileptogenic zone (EZ) and an optimal choice of the resection area. In this study we developed individualized computational models based upon structural brain networks to explore the impact of different virtual resections on the propagation of seizures. The propagation of seizures was modelled as an epidemic process [susceptible-infected-recovered (SIR) model] on individual structural networks derived from presurgical diffusion tensor imaging in 19 patients. The candidate connections for the virtual resection were all connections from the clinically hypothesized EZ, from which the seizures were modelled to start, to other brain areas. As a computationally feasible surrogate for the SIR model, we also removed the connections that maximally reduced the eigenvector centrality (EC) (large values indicate network hubs) of the hypothesized EZ, with a large reduction meaning a large effect. The optimal combination of connections to be removed for a maximal effect were found using simulated annealing. For comparison, the same number of connections were removed randomly, or based on measures that quantify the importance of a node or connection within the network. We found that 90% of the effect (defined as reduction of EC of the hypothesized EZ) could already be obtained by removing substantially less than 90% of the connections. Thus, a smaller, optimized, virtual resection achieved almost the same effect as the actual surgery yet at a considerably smaller cost, sparing on average 27.49% (standard deviation: 4.65%) of the connections. Furthermore, the maximally effective connections linked the hypothesized EZ to hubs. Finally, the optimized resection was equally or more effective than removal based on structural network characteristics both regarding reducing the EC of the hypothesized EZ and seizure spreading. The approach of using reduced EC as a surrogate for simulating seizure propagation can suggest more restrictive resection strategies, whilst obtaining an almost optimal effect on reducing seizure propagation, by taking into account the unique topology of individual structural brain networks of patients.

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Diffusion tensor imaging reveals altered structural connectivity of the mesial frontal lobe in juvenile myoclonic epilepsy

Klinische Neurophysiologie ◽

10.1055/s-0032-1301458 ◽

2012 ◽

Vol 43 (01) ◽

Author(s):

C Vollmar ◽

J O'Muircheartaigh ◽

M Koepp ◽

M Richardson ◽

J Duncan

Keyword(s):

Diffusion Tensor Imaging ◽

Frontal Lobe ◽

Diffusion Tensor ◽

Structural Connectivity ◽

Juvenile Myoclonic Epilepsy ◽

Myoclonic Epilepsy

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Structural brain alterations in young adult males with narcissistic personality disorder:A diffusion tensor imaging study

International Journal of Neuroscience ◽

10.1080/00207454.2021.1896504 ◽

2021 ◽

pp. 1-16

Author(s):

Jing Lou ◽

Yueji Sun ◽

Zhixia Cui ◽

Lei Gong

Keyword(s):

Diffusion Tensor Imaging ◽

Young Adult ◽

Diffusion Tensor ◽

Imaging Study ◽

Adult Males ◽

Young Adult Males ◽

Narcissistic Personality ◽

Diffusion Tensor Imaging Study ◽

Structural Brain ◽

Structural Brain Alterations

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Retrospective analysis of hemispheric structural network change as a function of location and size of glioma

Brain Communications ◽

10.1093/braincomms/fcaa216 ◽

2020 ◽

Author(s):

Shawn D’Souza ◽

Lisa Hirt ◽

David R Ormond ◽

John A Thompson

Keyword(s):

Diffusion Tensor Imaging ◽

White Matter ◽

Temporal Lobe ◽

Diffusion Tensor ◽

Brain Regions ◽

Structural Network ◽

Tumour Location ◽

The Impact ◽

Tractography Data ◽

Diffusion Tensor Imaging Tractography

Abstract Gliomas are neoplasms that arise from glial cell origin and represent the largest fraction of primary malignant brain tumours (77%). These highly infiltrative malignant cell clusters modify brain structure and function through expansion, invasion and intratumoral modification. Depending on the growth rate of the tumour, location and degree of expansion, functional reorganization may not lead to overt changes in behaviour despite significant cerebral adaptation. Studies in simulated lesion models and in patients with stroke reveal both local and distal functional disturbances, using measures of anatomical brain networks. Investigations over the last two decades have sought to use diffusion tensor imaging tractography data in the context of intracranial tumours to improve surgical planning, intraoperative functional localization, and post-operative interpretation of functional change. In this study, we used diffusion tensor imaging tractography to assess the impact of tumour location on the white matter structural network. To better understand how various lobe localized gliomas impact the topology underlying efficiency of information transfer between brain regions, we identified the major alterations in brain network connectivity patterns between the ipsilesional versus contralesional hemispheres in patients with gliomas localized to the frontal, parietal or temporal lobe. Results were indicative of altered network efficiency and the role of specific brain regions unique to different lobe localized gliomas. This work draws attention to connections and brain regions which have shared structural susceptibility in frontal, parietal and temporal lobe glioma cases. This study also provides a preliminary anatomical basis for understanding which affected white matter pathways may contribute to preoperative patient symptomology.

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White Matter Alteration Following SWAT Explosive Breaching Training and the Moderating Effect of a Neck Collar Device: A DTI and NODDI Study

Military Medicine ◽

10.1093/milmed/usab168 ◽

2021 ◽

Author(s):

Weihong Yuan ◽

Jonathan Dudley ◽

Alexis B Slutsky-Ganesh ◽

James Leach ◽

Pete Scheifele ◽

...

Keyword(s):

Diffusion Tensor Imaging ◽

White Matter ◽

Diffusion Tensor ◽

Moderating Effect ◽

Significant Group ◽

Blast Exposure ◽

Diffusion Weighted ◽

Weighted Data ◽

The Right ◽

The Impact

ABSTRACT Introduction Special Weapons and Tactics (SWAT) personnel who practice breaching with blast exposure are at risk for blast-related head trauma. We aimed to investigate the impact of low-level blast exposure on underlying white matter (WM) microstructure based on diffusion tensor imaging (DTI) and neurite orientation and density imaging (NODDI) in SWAT personnel before and after breacher training. Diffusion tensor imaging is an advanced MRI technique sensitive to underlying WM alterations. NODDI is a novel MRI technique emerged recently that acquires diffusion weighted data from multiple shells modeling for different compartments in the microstructural environment in the brain. We also aimed to evaluate the effect of a jugular vein compression collar device in mitigating the alteration of the diffusion properties in the WM as well as its role as a moderator on the association between the diffusion property changes and the blast exposure. Materials and Methods Twenty-one SWAT personnel (10 non-collar and 11 collar) completed the breacher training and underwent MRI at both baseline and after blast exposure. Diffusion weighted data were acquired with two shells (b = 1,000, 2,000 s/mm2) on 3T Phillips scanners. Diffusion tensor imaging metrices, including fractional anisotropy, mean, axial, and radial diffusivity, and NODDI metrics, including neurite density index (NDI), isotropic volume fraction (fiso), and orientation dispersion index, were calculated. Tract-based spatial statistics was used in the voxel-wise statistical analysis. Post hoc analyses were performed for the quantification of the pre- to post-blast exposure diffusion percentage change in the WM regions with significant group difference and for the assessment of the interaction of the relationship between blast exposure and diffusion alteration. Results The non-collar group exhibited significant pre- to post-blast increase in NDI (corrected P < .05) in the WM involving the right internal capsule, the right posterior corona radiation, the right posterior thalamic radiation, and the right sagittal stratum. A subset of these regions showed significantly greater alteration in NDI and fiso in the non-collar group when compared with those in the collar group (corrected P < .05). In addition, collar wearing exhibited a significant moderating effect for the alteration of fiso for its association with average peak pulse pressure. Conclusions Our data provided initial evidence of the impact of blast exposure on WM diffusion alteration based on both DTI and NODDI. The mitigating effect of WM diffusivity changes and the moderating effect of collar wearing suggest that the device may serve as a promising solution to protect WM against blast exposure.

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