scholarly journals White Matter Tract Disruptions Predict Less Affected Hand Impairment Following Stroke: A Longitudinal Diffusion MRI Study

Author(s):  
Firdaus Fabrice Hannanu ◽  
Bernadette Naegele ◽  
Marc Hommel ◽  
Alexandre Krainik ◽  
Olivier Detante ◽  
...  

Abstract Although less-affected hand (LAH) deficits following unilateral stroke are well documented, many aspects of LAH impairment mechanisms remain unresolved. To provide a better understanding of these mechanisms, we used diffusion MRI to examine the disruptions of white matter structural connections. Based on the redundancy theory, we hypothesized that a summation of motor-related tract disruptions would characterize LAH impairment. We assessed LAH impairment and fractional anisotropy (FA) in 28 patients at one-month post-stroke (baseline), and 6 and 24 months later. LAH impairment was assessed with the Purdue Pegboard Test (PPT), handgrip strength, and movement time. FA was estimated in the CST, Anterior- Corona Radiata (ACR), and Limb of Internal Capsule (ALIC), Superior Longitudinal Fasciculus (SLF), and corpus callosum (CC). We used Linear Mixed Models to determine the tracts associated with LAH impairment over time. Baseline PPT, grip, and movement time were impaired in 43%, 61%, and 25%, respectively. PPT was modeled by baseline ipsilesional-CST (t=3.75; p<0.001), ipsilesional-SLF (t=3.19; p=0.002), contralesional-ALIC (t=-4.89; p<0.001), and lesion volume (t=-3.18; p=0.004); handgrip by baseline ipsilesional-CST (t=3.39; p=0.001), contralesional-ALIC (t=-3.91; p<0.001) and sex (t=-1.43; p=0.007); movement time by baseline ipsilesional-SLF (t=-3.64; p=0.001), CC (t=4.00; p=<0.001), and lesion volume (t=3.03; p=0.006). In conclusion, white matter tract disruptions determine the LAH impairment profile, with ipsilesional-CST related to motor and ipsilesional-SLF to visuomotor processing. LAH impairment was associated with the summation of several tract disruptions, supporting the concept of cerebral redundancy. These results provide a theoretical basis for integrating LAH in rehabilitation programs and for treatment interventions such as neuromodulation.

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Konstantinos Poulakis ◽  
Robert I Reid ◽  
Scott A Przybelski ◽  
David S Knopman ◽  
Jonathan Graff-Radford ◽  
...  

Abstract Deterioration in white-matter health plays a role in cognitive ageing. Our goal was to discern heterogeneity of white-matter tract vulnerability in ageing using longitudinal imaging data (two to five imaging and cognitive assessments per participant) from a population-based sample of 553 elderly participants (age ≥60 years). We found that different clusters (healthy white matter, fast white-matter decliners and intermediate white-matter group) were heterogeneous in the spatial distribution of white-matter integrity, systemic health and cognitive trajectories. White-matter health of specific tracts (genu of corpus callosum, posterior corona radiata and anterior internal capsule) informed about cluster assignments. Not surprisingly, brain amyloidosis was not significantly different between clusters. Clusters had differential white-matter tract vulnerability to ageing (commissural fibres &gt; association/brainstem fibres). Identification of vulnerable white-matter tracts is a valuable approach to assessing risk for cognitive decline.


NeuroImage ◽  
2016 ◽  
Vol 127 ◽  
pp. 277-286 ◽  
Author(s):  
Anastasia Yendiki ◽  
Martin Reuter ◽  
Paul Wilkens ◽  
H. Diana Rosas ◽  
Bruce Fischl

2021 ◽  
Vol 89 (9) ◽  
pp. S85
Author(s):  
Suheyla Cetin-Karayumak ◽  
Ofer Pasternak ◽  
Fan Zhang ◽  
Johanna Seitz ◽  
Doron Elad ◽  
...  

NeuroImage ◽  
2020 ◽  
Vol 223 ◽  
pp. 117313
Author(s):  
Zihan Zhou ◽  
Qiqi Tong ◽  
Lei Zhang ◽  
Qiuping Ding ◽  
Hui Lu ◽  
...  

2020 ◽  
Vol 15 (9) ◽  
pp. 965-972
Author(s):  
Deepthi Rajashekar ◽  
Pauline Mouchès ◽  
Jens Fiehler ◽  
Bijoy K Menon ◽  
Mayank Goyal ◽  
...  

Background and purpose Clinical assessment scores in acute ischemic stroke are only moderately correlated with lesion volume since lesion location is an important confounding factor. Many studies have investigated gray matter indicators of stroke severity, but the understanding of white matter tract involvement is limited in the early phase after stroke. This study aimed to measure and model the involvement of white matter tracts with respect to 24-h post-stroke National Institutes of Health Stroke Scale (NIHSS). Material and methods A total of 96 patients (50 females, mean age 66.4 ± 14.0 years, median NIHSS 5, interquartile range: 2–9.5) with follow-up fluid-attenuated inversion recovery magnetic resonance imaging data sets acquired one to seven days after acute ischemic stroke onset due to proximal anterior circulation occlusion were included. Lesions were semi-automatically segmented and non-linearly registered to a common reference atlas. The lesion overlap and tract integrity were determined for each white matter tract in the AALCAT atlas and used to model NIHSS outcomes using a supervised linear-kernel support vector regression method, which was evaluated using leave-one-patient-out cross validation. Results The support vector regression model using the tract integrity and tract lesion overlap measurements predicted the 24-h NIHSS score with a high correlation value of r = 0.7. Using the tract overlap and tract integrity feature improved the modeling accuracy of NIHSS significantly by 6% (p < 0.05) compared to using overlap measures only. Conclusion White matter tract integrity and lesion load are important predictors for clinical outcome after an acute ischemic stroke as measured by the NIHSS and should be integrated for predictive modeling.


2020 ◽  
Vol 41 (8) ◽  
pp. 1495-1502
Author(s):  
F. Arrigoni ◽  
D. Peruzzo ◽  
S. Mandelstam ◽  
G. Amorosino ◽  
D. Redaelli ◽  
...  

2014 ◽  
Vol 10 ◽  
pp. P701-P702
Author(s):  
Lotte Cremers ◽  
Marius de Groot ◽  
Albert Hofman ◽  
Gabriel Krestin ◽  
Aad van der Lugt ◽  
...  

2012 ◽  
Vol 60 (5) ◽  
pp. S197
Author(s):  
A. Bargiacchi ◽  
A. Cachia ◽  
L. Lemaitre ◽  
N. Chabane ◽  
N. Boddaert ◽  
...  

2021 ◽  
Author(s):  
Bramsh Qamar Chandio ◽  
Tamoghna Chattopadhyay ◽  
Conor Owens-Walton ◽  
Julio E Villalon Reina ◽  
Leila Nabulsi ◽  
...  

Whole-brain tractograms generated from diffusion MRI digitally represent the white matter structure of the brain and are composed of millions of streamlines. Such tractograms can have false positive and anatomically implausible streamlines. To obtain anatomically relevant streamlines and tracts, supervised and unsupervised methods can be used for tractogram clustering and tract extraction. Here we propose FiberNeat, an unsupervised streamline clustering and tract filtering method. FiberNeat takes an input set of streamlines that could either be unlabeled clusters or labeled tracts. Individual clusters/tracts are projected into a latent space using nonlinear dimensionality reduction techniques, such as t-SNE and UMAP, to find spurious and outlier streamlines. In addition, outlier streamline clusters are detected using DBSCAN and then removed from the data in streamline space. Quantitative comparisons with expertly delineated tracts show the promise of the approach. This approach can be deployed as a filtering step after tracts are extracted.


Sign in / Sign up

Export Citation Format

Share Document