Exploration of central mechanisms for post-stroke fatigue based on resting-state functional magnetic resonance imaging

doi:10.3969/j.issn.1004-583X.2024.05.003

Abstract

Abstract:

Objective To explore the central mechanism for post-stroke fatigue (PSF) by using resting-state functional magnetic resonance imaging. Methods Patients with acute cerebral infarction who were admitted to the Second Hospital of Hebei Medical University from April 2019 to September 2021 were randomly enrolled. Fatigue severity scale assessment and functional magnetic resonance imaging examination were performed on the subjects in the acute phase of cerebral infarction (within 14 days of onset) and chronic phase (3 months after onset). The subjects were grouped according to the fatigue degree, and the data were processed by MATLAB R2013b software. The differences in eigenvalues γ, λ, σ, Cp, Lp of small-world attribute and whole-brain static functional network connectivity (sFNC) between groups were analyzed, and the correlation between the different brain regions and clinical data was analyzed. Results There was no significant difference in gender and age between the PSF group and the non-fatigue (NPSF) group in the acute and chronic stages of cerebral infarction (P>0.05). The brain networks of the subjects in the both groups had small-world properties (σ>1, γ>1, λ≈1), the area under the curve of λ and Cp in the PSF group in the chronic phase was significantly reduced than that of the NPSF group (P<0.05), and there was no significant difference in area under the curve of other characteristic parameters(P>0.05). Compared with the NPSF group, sFNC of the left fronto-parietal network, visual network (VN) and other networks were significantly decreased in the PSF group at the acute stage of infarction (P<0.05). Left and right fronto-parietal network showed significantly increased sFNC (P<0.05) in the default mode network and sensory-motor network, respectively. Compared with the NPSF group, the sFNC of right fronto-parietal network-VN was significantly decreased in the chronic PSF group (P<0.05), and the sFNC in default mode network and other networks was increased (P<0.05). Conclusion The occurrence of PSF in acute stage of cerebral infarction may be related to cognitive dysfunction. The increase of sFNC between some brain networks in PSF patients with chronic cerebral infarction may lead to cognitive dysfunction. The decrease of sFNC in RFPN-VN is speculated to be an inhibitory compensatory effect caused by excessive advanced executive network function.

Key words: brain infarction, post-stroke fatigue, functional magnetic resonance imaging, small world property, static functional network connectivity

CLC Number:

R743.33

Liu Xiuying, Cui Kaige, Liu Liying, Wu Yankai, Yu Jiaqi, Yang Jiping. Exploration of central mechanisms for post-stroke fatigue based on resting-state functional magnetic resonance imaging[J]. Clinical Focus, 2024, 39(5): 401-407.

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URL: https://huicui.hebmu.edu.cn/EN/10.3969/j.issn.1004-583X.2024.05.003

https://huicui.hebmu.edu.cn/EN/Y2024/V39/I5/401

Figures/Tables 7

Fig.1 Sketch map of RSNs

Tab.1 Comparison of general information and NIHSS scores between groups in the acute phase of cerebral infarction

组别	例数	性别[例(%)]		年龄 (岁)	NIHSS评分 (分)
组别	例数	男性	女性	年龄 (岁)	NIHSS评分 (分)
PSF组	40	26(65.0)	14(35.0)	54.27±10.27	3.70±2.30
NPSF组	35	24(68.6)	11(31.4)	54.23±9.66	2.20±1.80
统计值		χ²=0.107		t=0.153	t=3.126
P值		0.809		0.832	0.096

Tab.2 Comparison of characteristic parameters of small-world properties between groups in the acute period of cerebral infarction

组别	例数	AUC
组别	例数	σ	γ	λ	Cp	Lp
PSF组	40	0.58±0.13	0.67±0.14	0.40±0.02	0.20±0.01	0.75±0.07
NPSF组	35	0.62±0.12	0.71±0.13	0.39±0.02	0.20±0.01	0.74±0.08
统计值		t=1.522	t=1.333	t=1.175	t=0.487	t=1.004
P值		0.132	0.187	0.244	0.628	0.319

Fig.2 Correlation analysis between groups in the acute period of cerebral infarction Note : The connection between different brain regions indicates functional connection, red indicates enhancement, and blue indicates weakening

Tab.3 Comparison of general information between groups in the chronic phase of cerebral infarction

组别	例数	性别[例(%)]		年龄(岁)
组别	例数	男性	女性	年龄(岁)
PSF组	34	24(70.6)	10(29.4)	56.38±8.77
NPSF组	20	12(60.0)	8(40.0)	52.85±10.21
统计值		χ²=0.635		t=1.345
P值		0.425		0.537

Tab.4 Comparison of characteristic parameters of small world attributes between groups in chronic phase of cerebral infarction

组别	例数	AUC
组别	例数	σ	γ	λ	Cp	Lp
PSF组	40	0.57±0.09	0.65±0.10	0.39±0.01	0.20±0.01	0.74±0.05
NPSF组	35	0.56±0.13	0.66±0.14	0.40±0.02	0.20±0.01	0.77±0.08
统计值		t=0.197	t=0.198	t=1.890	t=2.029	t=1.335
P值		0.845	0.828	0.036	0.048	1.145

Fig.3 Correlation analysis between PSF group and NPSF group in the chronic phase of cerebral infarction Note : The connection between different brain regions indicates functional connection, red indicates enhancement, and blue indicates weakening

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