The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
White matter damage in primary progressive aphasias: a diffusion tensor tractography study
Open accessAbstract
Primary progressive aphasia is a clinical syndrome that encompasses three major phenotypes: non-fluent/agrammatic, semantic and logopenic. These clinical entities have been associated with characteristic patterns of focal grey matter atrophy in left posterior frontoinsular, anterior temporal and left temporoparietal regions, respectively. Recently, network-level dysfunction has been hypothesized but research to date has focused largely on studying grey matter damage. The aim of this study was to assess the integrity of white matter tracts in the different primary progressive aphasia subtypes. We used diffusion tensor imaging in 48 individuals: nine non-fluent, nine semantic, nine logopenic and 21 age-matched controls. Probabilistic tractography was used to identify bilateral inferior longitudinal (anterior, middle, posterior) and uncinate fasciculi (referred to as the ventral pathway); and the superior longitudinal fasciculus segmented into its frontosupramarginal, frontoangular, frontotemporal and temporoparietal components, (referred to as the dorsal pathway). We compared the tracts' mean fractional anisotropy, axial, radial and mean diffusivities for each tract in the different diagnostic categories. The most prominent white matter changes were found in the dorsal pathways in non-fluent patients, in the two ventral pathways and the temporal components of the dorsal pathways in semantic variant, and in the temporoparietal component of the dorsal bundles in logopenic patients. Each of the primary progressive aphasia variants showed different patterns of diffusion tensor metrics alterations: non-fluent patients showed the greatest changes in fractional anisotropy and radial and mean diffusivities; semantic variant patients had severe changes in all metrics; and logopenic patients had the least white matter damage, mainly involving diffusivity, with fractional anisotropy altered only in the temporoparietal component of the dorsal pathway. This study demonstrates that both careful dissection of the main language tracts and consideration of all diffusion tensor metrics are necessary to characterize the white matter changes that occur in the variants of primary progressive aphasia. These results highlight the potential value of diffusion tensor imaging as a new tool in the multimodal diagnostic evaluation of primary progressive aphasia.
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Cites
A fast diffeomorphic image registration algorithm
Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122
The basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,628
Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
Song, S.-K., Sun, S.-W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002) · NeuroImage · doi:10.1006/nimg.2002.1267 · Cited by 2,582
Perisylvian language networks of the human brain
Catani, M., Jones, D. K., & ffytche, D. H. (2005) · Annals of Neurology · doi:10.1002/ana.20319 · Cited by 1,832 · cited 3×
“Finally, a fifth temporoparietal component (SLF-tp), connects the inferior parietal lobe with the posterior temporal lobe, and has been described in several previous studies (Catani et al., 2005; Frey et al., 2008; Makris et al., 2009), although there remains some controversy about the nomenclature and the functional…”
BackgroundMethodResultDiffusion tensor imaging (DTI)-based white matter mapping in brain research: a review
Assaf, Y., & Pasternak, O. (2008) · Journal of Molecular Neuroscience · doi:10.1007/s12031-007-0029-0 · Cited by 1,537
About “axial” and “radial” diffusivities
Wheeler‐Kingshott, C. A. M., & Cercignani, M. (2009) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21965 · Cited by 885
Friederici, A. D., Bahlmann, J., Heim, S., Schubotz, R. I., & Anwander, A. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0509389103 · Cited by 734
Alzheimer and frontotemporal pathology in subsets of primary progressive aphasia
Mesulam, M., Wicklund, A., Johnson, N., Rogalski, E., Léger, G. C., Rademaker, A., Weintraub, S., & Bigio, E. H. (2008) · Annals of Neurology · doi:10.1002/ana.21388 · Cited by 513
Croxson, P. L., Johansen-Berg, H., Behrens, T. E. J., Robson, M. D., Pinsk, M. A., Gross, C. G., Richter, W., Richter, M. C., Kastner, S., & Rushworth, M. F. S. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.1311-05.2005 · Cited by 410
Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease
Acosta-Cabronero, J., Williams, G. B., Pengas, G., & Nestor, P. J. (2010) · Brain · doi:10.1093/brain/awp257 · Cited by 393
Cited by
Dissecting the uncinate fasciculus: disorders, controversies and a hypothesis.
Von Der Heide, R. J., Skipper, L. M., Klobusicky, E., & Olson, I. R. (2013) · Brain · doi:10.1093/brain/awt094 · Cited by 829
Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language
Dick, A. S., & Tremblay, P. (2012) · Brain · doi:10.1093/brain/aws222 · Cited by 470
Syntactic Processing Depends on Dorsal Language Tracts
Wilson, S. M., Galantucci, S., Tartaglia, M. C., Rising, K., Patterson, D. K., Henry, M. L., Ogar, J. M., DeLeon, J., Miller, B. L., & Gorno-Tempini, M. L. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.014 · Cited by 311
Self-citationWhite matter damage in frontotemporal lobar degeneration spectrum
Agosta, F., Scola, E., Canu, E., Marcone, A., Magnani, G., Sarro, L., Copetti, M., Caso, F., Cerami, C., Comi, G., et al. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr288 · Cited by 180
Self-citationMandelli, M. L., Vilaplana, E., Brown, J. A., Hubbard, H. I., Binney, R. J., Attygalle, S., Santos-Santos, M. A., Miller, Z. A., Pakvasa, M., Henry, M. L., et al. (2016) · Brain · doi:10.1093/brain/aww195 · Cited by 139
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Metadata
- Authors
- Galantucci, S., Tartaglia, M. C., Wilson, S. M., Henry, M. L., Filippi, M., Agosta, F., Dronkers, N. F., Henry, R. G., Ogar, J. M., Miller, B. L., & Gorno-Tempini, M. L.
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-06-11
- Volume
- 134
- Issue
- 10
- Pages
- 3011-3029
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- OpenAlex
- W2157453960
- Cited by
- 306
- References
- 14
- FWCI
- 14.58
- Type
- journal article
- Language
- en
- Open access
- bronze
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