Structural connectivity-based predictors of cognitive impairment in stroke patients attributable to aging

Rehák Bučková, Barbora; Kala, David; Kořenek, Jakub; Matušková, V.; Kumpošt, Vojtěch; Svobodová, L.; Otáhal, Jakub; Škoch, A.; Šulc, V.; Olšerová, A.; Vyhnálek, M.; Janský, P.; Tomek, A.; Marusič, P.; Jiruška, P.; Hlinka, Jaroslav

doi:https://dx.doi.org/10.1371/journal.pone.0280892

Number of the records: 1

Structural connectivity-based predictors of cognitive impairment in stroke patients attributable to aging

1.

SYSNO ASEP	0572336
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Structural connectivity-based predictors of cognitive impairment in stroke patients attributable to aging
Author(s)	Rehák Bučková, Barbora (UIVT-O)_{RID, ORCID, SAI} Kala, David (FGU-C) Kořenek, Jakub (UIVT-O)_{ORCID, RID, SAI} Matušková, V. (CZ) Kumpošt, Vojtěch (FGU-C)_ORCID Svobodová, L. (CZ) Otáhal, Jakub (FGU-C)_{RID, ORCID, SAI} Škoch, A. (CZ) Šulc, V. (CZ) Olšerová, A. (CZ) Vyhnálek, M. (CZ) Janský, P. (CZ) Tomek, A. (CZ) Marusič, P. (CZ) Jiruška, P. (CZ) Hlinka, Jaroslav (UIVT-O)_{RID, SAI, ORCID}
Article number	e0280892
Source Title	PLoS ONE. - : Public Library of Science - ISSN 1932-6203 Roč. 18, č. 4 (2023)
Number of pages	18 s.
Publication form	Online - E
Language	eng - English
Country	US - United States
Keywords	Stroke ; Aging ; Structural connectivity ; Diffusion Magnetic Resonance Imaging ; White matter ; Cognitive Dysfunction ; Tract-Based Spatial Statistics ; Graph Theory ; Tractography
OECD category	Neurosciences (including psychophysiology
R&D Projects	NV17-28427A GA MZd - Ministry of Health (MZ)
Method of publishing	Open access
Institutional support	UIVT-O - RVO:67985807 ; FGU-C - RVO:67985823
UT WOS	001017121000011
EID SCOPUS	85152630346
DOI	10.1371/journal.pone.0280892
Annotation	Despite the rising global burden of stroke and its socio-economic implications, the neuroimaging predictors of subsequent cognitive impairment are still poorly understood. We address this issue by studying the relationship of white matter integrity assessed within ten days after stroke and patients' cognitive status one year after the attack. Using diffusion-weighted imaging, we apply the Tract-Based Spatial Statistics analysis and construct individual structural connectivity matrices by employing deterministic tractography. We further quantify the graph-theoretical properties of individual networks. The Tract-Based Spatial Statistic did identify lower fractional anisotropy as a predictor of cognitive status, although this effect was mostly attributable to the age-related white matter integrity decline. We further observed the effect of age propagating into other levels of analysis. Specifically, in the structural connectivity approach we identified pairs of regions significantly correlated with clinical scales, namely memory, attention, and visuospatial functions. However, none of them persisted after the age correction. Finally, the graph-theoretical measures appeared to be more robust towards the effect of age, but still were not sensitive enough to capture a relationship with clinical scales. In conclusion, the effect of age is a dominant confounder especially in older cohorts, and unless appropriately addressed, may falsely drive the results of the predictive modelling.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2024
Electronic address	https://dx.doi.org/10.1371/journal.pone.0280892

Number of the records: 1