Poster No:
1257
Submission Type:
Abstract Submission
Authors:
Viktoriia Pozdniakova1, Stephen Wilson2, Katie McMahon3, David Copland1, Sonia Brownsett1
Institutions:
1University of Queensland; Queensland Aphasia Research Centre, Brisbane, Queensland, 2University of Queensland, Brisbane, Queensland, 3Royal Brisbane & Women’s Hospital; Queensland University of Technology, Brisbane, Queensland
First Author:
Co-Author(s):
Katie McMahon
Royal Brisbane & Women’s Hospital; Queensland University of Technology
Brisbane, Queensland
David Copland
University of Queensland; Queensland Aphasia Research Centre
Brisbane, Queensland
Sonia Brownsett
University of Queensland; Queensland Aphasia Research Centre
Brisbane, Queensland
Introduction:
In aphasia rehabilitation, it is widely accepted that the most significant improvements occur within the first three months following a stroke. After this period, recovery becomes less pronounced and depends on various factors, including lesion site and size, and initial impairment severity (Wilson et al., 2023). Reduced connectivity of the white-matter (WM) tracts involved in language processing is commonly observed in post-stroke aphasia. However, findings regarding changes in WM integrity have been inconsistent (e.g., Forkel et al., 2014; Osa García et al., 2020; Sihvonen et al., 2023; Soliman et al., 2023).
This longitudinal study examined WM connectivity in the brain at the early subacute, late subacute, and chronic stages of stroke rehabilitation, aiming to evaluate (1) macro- and microstructural changes in the clinical group, in comparison to the control group; and (2) longitudinal changes over the course of recovery.
Methods:
We conducted a longitudinal diffusion-weighted magnetic resonance imaging (dMRI) study with a cohort of 15 stroke survivors (4 females, age: 45-72 years old, mean: 61 years old). The participants' imaging and behavioural data were collected at the early subacute (15-44 days post-onset, mean: 31.5), late subacute (83-112 days post-onset, mean: 95.6) and chronic (182-246 days post-onset, mean: 210.4) stroke stages. The control group comprised 12 age-matched healthy participants (6 females, age: 46-68 years old, mean: 56 years old).
Tracts of interest (the bilateral arcuate (AF), uncinate (UF), inferior longitudinal (ILF), inferior fronto-occipital (IFOF), middle longitudinal (MdLF) fasciculi and frontal aslant tract (FAT) were mapped with an automatic fibre-tracking algorithm in DSI Studio (Yeh, 2021). We extracted the following metrics: quantitative anisotropy (QA), axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD), and total tract volume.
Student's t-tests and one-way repeated measures ANOVA were used to determine the difference between the clinical and healthy group metrics, and to analyse longitudinal changes in WM metrics and language scores.
Results:
At the early subacute stage, QA was significantly decreased in the clinical group compared to controls in the left-hemispheric AF (p<.001) and MdLF (P=.01). RD and MD of these tracts were significantly increased (p<.02). AD was significantly increased in the left ILF (P=.04), and the right AF (P=.04), IFOF (P=.04), MdLF (P=.04), and UF (P=.04).
At the late subacute stage, QA remained significantly decreased in the left AF (P=.008) and MdLF (P=.03). There was a significant increase in RD and MD in the left AF (P=.003), FAT (p<.02), and MdLF (P=.02). Volume of the left AF was significantly decreased (P=.002).
At the chronic stage, QA was significantly decreased in the left AF (P=.003) and MdLF (P=.03), while RD was increased in the left AF (P=.004), FAT (P=.006), and MdLF (P=.006). AD was increased in the left AF (P=.006), FAT (P=.002), ILF (P=.02), and MdLF (P=.002). MD was increased in the left AF (P=.003), FAT (P=.003), ILF (P=.03), and MdLF (P=.003). There was a significant decrease in volume (P=.002) of the left AF.
The only significant longitudinal change was an increase in AD in the left AF over time (P<.001).
Conclusions:
Post-stroke changes in structural connectivity were observed in the left-hemispheric tracts, including the AF and MdLF. Specifically, QA was decreased, while RD and MD were increased in these tracts at the early subacute evaluation, and these changes persisted into the chronic stage, along with the decreased volume. The increase of AD in the right-hemispheric tracts was only observed at the early subacute stage, while the AD of the left-hemispheric tracts increased at the chronic stage. Longitudinal analysis showed a significant increase in AD in the left AF over time. We hypothesize that our results reflect lesion-induced damage with prolonged axonal degeneration.
Language:
Language Other
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 1
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Novel Imaging Acquisition Methods:
Diffusion MRI 2
Keywords:
Aphasia
Tractography
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Stroke
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Other
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
Structural MRI
Diffusion MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
SPM
FSL
Other, Please list
-
DSI Studio, MRTrix
Provide references using APA citation style.
Forkel, S. J., Thiebaut de Schotten, M., Dell’Acqua, F., Kalra, L., Murphy, D. G. M., Williams, S. C. R., & Catani, M. (2014). Anatomical predictors of aphasia recovery: A tractography study of bilateral perisylvian language networks. Brain, 137(7), 2027–2039. https://doi.org/10.1093/brain/awu113
Osa García, A., Brambati, S. M., Brisebois, A., Désilets-Barnabé, M., Houzé, B., Bedetti, C., Rochon, E., Leonard, C., Desautels, A., & Marcotte, K. (2020). Predicting Early Post-stroke Aphasia Outcome From Initial Aphasia Severity. Frontiers in Neurology, 11, 120. https://doi.org/10.3389/fneur.2020.00120
Sihvonen, A. J., Vadinova, V., Garden, K. L., Meinzer, M., Roxbury, T., O’Brien, K., Copland, D., McMahon, K. L., & Brownsett, S. L. E. (2023). Right hemispheric structural connectivity and poststroke language recovery. Human Brain Mapping, 44(7), 2897–2904. https://doi.org/10.1002/hbm.26252
Soliman, R. K., Tax, C. M. W., Abo-Elfetoh, N., Zaitoun, M. M. A., & Khedr, E. M. (2023). Constrained spherical deconvolution -based tractography of major language tracts reveals post-stroke bilateral white matter changes correlated to aphasia. Magnetic Resonance Imaging, 95, 19–26. https://doi.org/10.1016/j.mri.2022.10.004
Wilson, S. M., Entrup, J. L., Schneck, S. M., Onuscheck, C. F., Levy, D. F., Rahman, M., Willey, E., Casilio, M., Yen, M., Brito, A. C., Kam, W., Davis, L. T., de Riesthal, M., & Kirshner, H. S. (2023). Recovery from aphasia in the first year after stroke. Brain, 146(3), 1021–1039. https://doi.org/10.1093/brain/awac129
Yeh, F. (2021). DSI Studio (Version 2021 June) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.4978980
No