The arcuate fasciculus: a comparison between diffusion tensor tractography and anatomy using the fiber dissection technique

Jong, Lars de; Kovacs, Silvia; Bamps, Sven; Calenbergh, Frank Van; Sunaert, Stefan; Loon, J. van

doi:10.1016/j.surneu.2008.10.072

Cited by 4 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Overall, we tend to identify a leftward arcuate laterality. This is consistent with previous literature, both ex vivo and in vivo (Catani & Mesulam, ; de Jong et al, ; Glasser & Rilling, ; Takaya et al, ; Thiebaut de Schotten et al, ). In this work, we hypothesize that the mixed result in the literature regarding arcuate laterality is due to the greater variability in probabilistic tractography, and that it can be addressed by using additional constraints on the track identification process.…”

Section: Discussionsupporting

confidence: 93%

Evaluating arcuate fasciculus laterality measurements across dataset and tractography pipelines

Bain

Yeatman

Schurr

et al. 2019

Human Brain Mapping

View full text Add to dashboard Cite

The arcuate fasciculi are white‐matter pathways that connect frontal and temporal lobes in each hemisphere. The arcuate plays a key role in the language network and is believed to be left‐lateralized, in line with left hemisphere dominance for language. Measuring the arcuate in vivo requires diffusion magnetic resonance imaging–based tractography, but asymmetry of the in vivo arcuate is not always reliably detected in previous studies. It is unknown how the choice of tractography algorithm, with each method's freedoms, constraints, and vulnerabilities to false‐positive and ‐negative errors, impacts findings of arcuate asymmetry. Here, we identify the arcuate in two independent datasets using a number of tractography strategies and methodological constraints, and assess their impact on estimates of arcuate laterality. We test three tractography methods: a deterministic, a probabilistic, and a tractography‐evaluation (LiFE) algorithm. We extract the arcuate from the whole‐brain tractogram, and compare it to an arcuate bundle constrained even further by selecting only those streamlines that connect to anatomically relevant cortical regions. We test arcuate macrostructure laterality, and also evaluate microstructure profiles for properties such as fractional anisotropy and quantitative R1. We find that both tractography choice and implementing the cortical constraints substantially impact estimates of all indices of arcuate laterality. Together, these results emphasize the effect of the tractography pipeline on estimates of arcuate laterality in both macrostructure and microstructure.

show abstract

Section: Discussionsupporting

confidence: 93%

Evaluating arcuate fasciculus laterality measurements across dataset and tractography pipelines

Bain

Yeatman

Schurr

et al. 2019

Human Brain Mapping

View full text Add to dashboard Cite

show abstract

“…The finding that frontal lobe FA is greater in the right hemisphere, but greater on the left for the temporal lobes, confirm prior DTI reports of frontal and temporal white matter asymmetries. In general, prior studies focused on specific tracts, e.g., the corticospinal tract (Westerhausen et al, 2007) and the arcuate fasciculus, which is involved in language processing (de Jong et al, 2009; Rodrigo et al, 2007). A voxelwise analysis (Buchel et al, 2004) suggested left greater than right FA white matter asymmetries in the arcuate fasciculus and found asymmetries contralateral to the dominant hand (i.e., higher on the left in right-handers) in tracts innervating the precentral gyrus (as expected, given the crossing of the cortical motor circuitry).…”

Section: Discussionmentioning

confidence: 99%

“…These included quantitative genetic analyses to estimate genetic and environmental contributions to the observed differences. We expected genetic factors to play a substantial role in the lateralization of the fiber anisotropy in language association regions of the temporal lobe, including the arcuate fasciculus (de Jong et al, 2009; Rodrigo et al, 2007). We also predicted that the use of a symmetrized brain template as a registration target might somewhat reduce the level of observed asymmetry, by eliminating factors reflecting brain shape, such as the level of petalia, or torquing, of the brain.…”

Section: Methodsmentioning

confidence: 99%

Genetic influences on brain asymmetry: A DTI study of 374 twins and siblings

Jahanshad¹,

Lee²,

Barysheva³

et al. 2010

NeuroImage

136

118

View full text Add to dashboard Cite

Brain asymmetry, or the structural and functional specialization of each brain hemisphere, has fascinated neuroscientists for over a century. Even so, genetic and environmental factors that influence brain asymmetry are largely unknown. Diffusion tensor imaging (DTI) now allows asymmetry to be studied at a microscopic scale by examining differences in fiber characteristics across hemispheres rather than differences in structure shapes and volumes. Here we analyzed 4 Tesla DTI scans from 374 healthy adults, including 60 monozygotic twin pairs, 45 same-sex dizygotic pairs, and 164 mixed-sex DZ twins and their siblings; mean age: 24.4 years +/− 1.9SD). All DTI scans were nonlinearly aligned to a geometrically-symmetric, population-based image template. We computed voxel-wise maps of significant asymmetries (left/right differences) for common diffusion measures that reflect fiber integrity (fractional and geodesic anisotropy; FA, GA and mean diffusivity, MD). In quantitative genetic models computed from all same-sex twin pairs (N=210 subjects), genetic factors accounted for 33% of the variance in asymmetry for the inferior fronto-occipital fasciculus, 37% for the anterior thalamic radiation, and 20% for the forceps major and uncinate fasciculus (all L>R). Shared environmental factors accounted for around 15% of the variance in asymmetry for the cortico-spinal tract (R>L) and about 10% for the forceps minor (L>R). Sex differences in asymmetry (men > women) were significant, and were greatest in regions with prominent FA asymmetries. These maps identify heritable DTI-derived features, and may empower genome-wide searches for genetic polymorphisms that influence brain asymmetry.

show abstract

“…Previous DTI asymmetry studies have focused on specific tracts (e.g., the corticospinal tract [4], and the arcuate fasciculus involved in language processing [5,6]). Frontal and temporal white matter show left greater than right FA even in early infancy [7], suggesting greater myelination in the left hemisphere [7].…”

Section: Introductionmentioning

confidence: 99%

Genetics of Anisotropy Asymmetry: Registration and Sample Size Effects

Jahanshad

Lee²,

Leporé³

et al. 2009

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

View full text Add to dashboard Cite

Abstract. Brain asymmetry has been a topic of interest for neuroscientists for many years. The advent of diffusion tensor imaging (DTI) allows researchers to extend the study of asymmetry to a microscopic scale by examining fiber integrity differences across hemispheres rather than the macroscopic differences in shape or structure volumes. Even so, the power to detect these microarchitectural differences depends on the sample size and how the brain images are registered and how many subjects are studied. We fluidly registered 4 Tesla DTI scans from 180 healthy adult twins (45 identical and fraternal pairs) to a geometrically-centered population mean template. We computed voxelwise maps of significant asymmetries (left/right hemisphere differences) for common fiber anisotropy indices (FA, GA). Quantitative genetic models revealed that 47-62% of the variance in asymmetry was due to genetic differences in the population. We studied how these heritability estimates varied with the type of registration target (T1-or T2-weighted) and with sample size. All methods consistently found that genetic factors strongly determined the lateralization of fiber anisotropy, facilitating the quest for specific genes that might influence brain asymmetry and fiber integrity.

show abstract

The arcuate fasciculus: a comparison between diffusion tensor tractography and anatomy using the fiber dissection technique

Cited by 4 publications

References 0 publications

Evaluating arcuate fasciculus laterality measurements across dataset and tractography pipelines

Evaluating arcuate fasciculus laterality measurements across dataset and tractography pipelines

Genetic influences on brain asymmetry: A DTI study of 374 twins and siblings

Genetics of Anisotropy Asymmetry: Registration and Sample Size Effects

Contact Info

Product

Resources

About