Spontaneous Echo Contrast in the Left Atrium and Aortic-Arch Atheroma,Detected by Transesophageal Echocardiography,Was Negatively Correlated with Cognitive Function

Abstract

Background:

The relationship between transesophageal echocardiography findings and cognitive function.

Objective:

This study aimed to establish an association between transesophageal echocardiography findings and cognitive function in stroke survivors.

Methods:

A single-center study was conducted between April 1, 2017 and March 31, 2022. All subjects that were included had a past history of ischemic stroke and were admitted after >21 days from onset. The participants underwent cognitive function tests including a Mini-Mental State Examination, Revised Hasegawa Dementia Scale, Frontal Assessment Battery, and transesophageal echocardiography.

Results:

The results of 126 participants were analyzed. The cognitive function of participants with a spontaneous echo contrast (+) in the left atrium including appendage or of those with an aorta-arch plaque with a maximum thickness ≥4 mm significantly worse while neither the patent foramen ovale nor the branch extending plaque influenced cognitive function (The median cognitive scores of the spontaneous echo contrast (–) versus (+) were 26 versus 22, p < 0.01^**, 26 versus 21, p < 0.001^***, and 14 versus 11, p < 0.01^**. Those of the aortic-arch plaque max thickness (<4 mm) versus (≥4 mm) were 26 versus 25, p < 0.05^*, 27 versus 24, p < 0.05^*, and 15 versus 13, p < 0.05^*).

Conclusion:

Our findings show that spontaneous echo contrast in the left atrium and aortic-arch atheroma detected by transesophageal echocardiography, were negatively associated with cognitive function.

Keywords

Aortic-arch atheroma cognitive function examination spontaneous echo contrast transesophageal echocardiography

INTRODUCTION

Dementia is an important global issue [1, 2], with Alzheimer’s disease (AD) accounting for more than 50% of all diagnosed cases of dementia in aged populations of developed countries [3]. One way to overcome the problem of an increasing incidence of AD in aging societies is by understanding the pathology and causative factors of AD, in order to enable improve treatment and fortify prevention. Numerous reports have noted a correlation between amyloid-β (Aβ) metabolism and AD pathology [4]. The association between cerebrovascular circumstance and neuron, which is called as the perivascular fluid compartment, is considered to be important in AD pathology because strokes can impact cognitive function, even in ischemic stroke survivors [5 –7]. Previously, we reported that spontaneous echo contrast and the velocity of the internal jugular vein (IJV) were significantly correlated with AD, cognitive function, and the Fazekas scale, findings that were validated using carotid duplex ultrasonography [8]. It is also possible that cardiac dysfunction of systemic venous flow can impact AD pathology [9, 10].

Transesophageal echocardiography (TEE) is a relatively safe tool to examine several cardiogenic and aortogenic (including around the vessels) parameters, as well as paradoxical embolic sources [11 –13]. The purpose of TEE examinations is to determine the source of an embolic ischemic stroke. Detailed cardiac and aortic-arch parameters such as cardiac venous flow congestion and aortic-arch atheroma can be evaluated using TEE. In addition, some recent reports showed, a relationship between microemboli and cognitive impairment [14 –16], while others showed a relationship between atrial fibrillation (AF) and cognitive impairment [17, 18]. However, to the best of our knowledge, no study has evaluated the relationship between TEE findings and cognitive function. The aim of this study was to establish a clear relationship between TEE findings and cognitive function of ischemic stroke survivors.

METHODS

Subjects and study design

The study period of this single-center study was between April 1, 2017 and March 31, 2022. All participants that were included had a history of ischemic stroke and were admitted after >21 days from the onset of a stroke. Considering that acute ischemic stroke itself influences cognitive function [19 –21], patients who had an acute ischemic stroke, defined as admission within 21 days after the onset of a stroke [22, 23], were excluded from this study. Comorbid psychiatric/neurological disorders, except for dementing diseases such as Parkinson’s disease or organic central nervous system disorders such as brain tumor patients, were also excluded from this study.

A total of 1,438 patients who had suffered an ischemic stroke were admitted to the Division of Neurology, Department of Medicine, of Jichi Medical University in Japan, during the study period. Thirty-one patients had a recurrent stroke. Of the remaining 1,407 patients, 949 were admitted within 21 days from onset while 458 patients were admitted after >21 days from onset. Among the 458 patients admitted after >21 days from onset, 165 underwent TEE. Of these 165 patients, 126 agreed to participate in this study and underwent additional cognitive function tests, including the Mini-Mental State Examination (MMSE), Revised Hasegawa Dementia Scale (HDS-R), and Frontal Assessment Battery (FAB). The findings of these 126 participants were analyzed (Fig. 1).

This study was approved by the ethics committee of Jichi Medical University. An exemption from approval was obtained from the institutional review board based on the university’s guidelines (approval #Rin-Dai 20-054). All participants provided informed consent to participate in this study.

Fig. 1

Flow diagram of patient enrollment in the present study.

Baseline assessment

We recorded the following parameters for each and all participants: age; gender; body mass index (BMI); past history of stroke (recurrent ischemic stroke or hemorrhagic stroke); presence of hypertension, diabetes mellitus, hyperlipidemia, coronary artery disease, congestive heart failure, peripheral arterial disease, chronic kidney disease, and AF. For any participant, we recorded the incidence of comorbidity-related dementing disorders that were diagnosed or treated prior to admission. Ischemic stroke subtypes, which were diagnosed after TEE examination, were classified based on the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria [24]. Subjects who had a transient ischemic attack (TIA) were included in the study but were assessed separately from patients with a cerebral infarction [25]. Each participant was assessed upon admission using the National Institute of Health Stroke Scale (NIHSS) score and upon discharge using the modified Rankin Scale (mRS) score.

Assessment by TEE

We validated cardiac and aortic associations using TEE. A commercially available ultrasound imaging system (EPIQ7; Philils, Amsterdam, the Netherlands) and a multiplane probe were used to perform TEE. The following parameters were evaluated: spontaneous echo contrast (+ or –) in the left atrium, including appendage, inlet and outlet flow velocities at the left atrial appendage, patent foramen ovale (PFO) (+ or –), maximum thickness of the aortic-arch plaque, ulceration or the presence of a mobile component at the aortic-arch (+ or –), and branch extending plaque (+ or –). To validate PFO, the Valsalva contrast test was performed [26]. Ulceration was defined as the formation of a recess with a >2 mm depth from the luminal surface of the plaque and a base width of >2 mm [27]. Branch extending plaque (+) was defined as the presence of a >1 mm plaque in the right vertebral, right carotid, or brachiocephalic artery [28]. Aortic-arch atheroma (+) was defined as the presence of a ≥4 mm plaque at the aortic-arch [29]. All TEE examinations were performed by expert neurologists certified by the Japanese Association of Neurosonology.

Data analysis

Cognitive test scores (MMSE, HDS-R, and FAB) were evaluated by professional medical staff who were blinded to the TEE findings. All statistical analyses were performed using JMP 16 statistical software (SAS Institute Inc., Cary, NC, USA). Data are expressed as the median±interquartile range (IQR) and were analyzed using the nonparametric Wilcoxon’s rank sum test or the Kruskal-Wallis test, as appropriate. For the post-hoc analysis, to assess differences among groups, the Steel-Dwass test was used. Pearson’s correlation coefficient was calculated to assess the correlation between inlet or outlet flow velocities at the left atrial appendage and cognitive function. A multivariate analysis, in the form of a logistic regression analysis, was performed using the five TEE parameters according to previously diagnosed or treated AD cases. Statistical significance was assessed at p < 0.05.

RESULTS

Characteristics of participants

Characteristics of the 126 participants are shown in Table 1. Median age was 72 years (IQR; 65–82 years), and males accounted for 61.1% of the study population. Of the participants that were included, 31.7% had recurrent ischemic stroke, 4.8% had hemorrhagic stroke, 74.6% had hypertension, 25.4% had diabetes mellitus, 44.4% had hyperlipidemia, and 31.7% had AF. Based on comorbidity-related dementing disorders, 16 cases (12.7%) were previously diagnosed or treated as AD before admission to this study. There were no comorbidity-related dementing disorders without AD participants in our study. A TEE examination revealed that 29.4% of those with ischemic stroke had “cardioembolism” as the diagnosis subtype, 7.9% had “large-artery atherosclerosis”, 7.1% had “small-vessel occlusion (lacunar)”, 26.1% had “stroke of other determined etiology”, and 20.6% had “stroke of undetermined etiology” subtype. Participants with TIA accounted for 8.7% of the study group. The median participant NIHSS and mRS scores were 2 (IQR; 1–4) and 1 (IQR: 0–2), respectively.

Table 1

Participant characteristics

Patient demographics
Total number of patients	126
Age (y) (median, [IQR])	72 (65–82)
Male, n (%)	77 (61.1)
Female, n (%)	49 (38.9)
BMI (kg/m²) (median, [IQR])	22.6 (20.3–25.2)
Past history of disease
Recurrent ischemic stroke, n (%)	40 (31.7)
Hemorrhagic stroke, n (%)	6 (4.8)
Hypertension, n (%)	94 (74.6)
Diabetes mellitus, n (%)	32 (25.4)
Hyperlipidemia, n (%)	56 (44.4)
Coronary disease, n (%)	15 (11.9)
Congestive heart failure, n (%)	13 (10.3)
Peripheral arterial disease, n (%)	7 (5.6)
Chronic kidney disease, n (%)	20 (15.9)
Atrial fibrillation (+), n (%)	40 (31.7)
Paroxysmal atrial fibrillation, n (%)	19 (15.1)
Continuous atrial fibrillation, n (%)	19 (15.1)
Valvular atrial fibrillation, n (%)	2 (1.6)
Comorbid dementing diseases
Alzheimer’s disease	16 (12.7)
Ischemic stroke subtype
Ischemic stroke	115 (91.3)
Large-artery atherosclerosis, n (%)	10 (7.9)
Small-vessel occlusion (Lacunar), n (%)	9 (7.1)
Cardioembolism, n (%)	37 (29.4)
Stroke of other determined etiology, n (%)	33 (26.1)
Stroke of undetermined etiology, n (%)	26 (20.6)
TIA	11 (8.7)
NIHSS score (median, [IQR])	2 (1–4)
mRS (median, [IQR])	1 (0–2)

BMI, Body mass index; IQR, Inter quartile range; NIHSS, National Institute of Health Stroke Scale; mRS, Modified Rankin Scale; TIA, Transient ischemic attack.

Correlation between TEE findings and cognitive function

The correlation between each TEE finding and cognitive function is shown in Table 2. According to the spontaneous echo contrast in the left atrium, including the appendage, the cognitive function of the spontaneous echo contrast (+) group was significantly inferior to that of the spontaneous echo contrast (–) group (Fig. 2A). Both inlet and outlet flow velocities at the left atrial appendage showed a positive correlation with cognitive function. The r values for MMSE, HDS-R, and FAB related to inlet or outlet flow velocity were all 0.2. In contrast, there was no significant difference between PFO and cognitive function. According to the aortic-arch status, the cognitive function of the group with aortic arch atheroma ≥4 mm was significantly lower than that of the group with atheroma <4 mm (Fig. 2B). The cognitive function of the group with an aorta-arch plaque ulcer or mobile (+) was lower than, but not significantly different to that of the (–) group. In contrast, there was no significant difference between branch extending plaque and cognitive function.

Fig. 2

A) Comparison of the cognitive functions, MMSE, HDS-R, and FAB, between the spontaneous echo contrast (–) and (+) group in the left atrium, including an appendage. B) Comparison of cognitive function between the group with an aortic arch plaque with maximum thickness <4 mm and with a thickness ≥4 mm.

Table 2

Association between TEE findings and cognitive function

TEE finding		n (%)	MMSE	p	HDS-R	p	FAB	p
			median		median		median
			(IQR)		(IQR)		(IQR)
Spontaneous echo contrast	(–)	86	26	<0.01^**a	26	<0.001^***a	14	<0.01^**a
		(68.3%)	(23–29)		(21–29)		(9–16)
	(+)	40	22		21		11
		(31.7%)	(16–27)		(11–26)		(5–15)
PFO	(–)	104	25	0.21	25	0.30	14	0.52
		(82.5%)	(20–29)		(17–29)		(7–16)
	(+)	18	25		24		14
		(14.3%)	(18–27)		(15–28)		(11–16)
Aortic-arch plaque max thickness	<4 mm	69	26	<0.05^*a	27	<0.05^*a	15	<0.05^*a
		(54.8%)	(22–29)		(19–29)		(7–17)
	≥4 mm	57	25		24		13
		(45.2%)	(18–27)		(17–28)		(8–15)
Aorta-arch plaque ulcer or mobile	(–)	104	26	0.23	25	0.78	14	0.11
		(82.5%)	(20–29)		(17–29)		(7–16)
	(+)	22	25		23		11
		(17.5%)	(19–26)		(18–29)		(8–14)
Branch extending plaque	(–)	89	25	0.77	25	0.68	14	0.58
		(70.6%)	(21–28)		(18–29)
	(+)	37	26		25		13
		(29.4%)	(19–28)		(16–29)

FAB, Frontal Assessment Battery; HDS-R, Hasegawa Dementia Rating Scale-Revised; IQR, inter quartile range; MMSE, Mini-Mental State Examination; PFO, patent foramen ovale; TEE, Transesophageal echocardiography. ^anonparametric Wilcoxon’s rank sum test was performed. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001.

Furthermore, we analyzed the influence of the coexistence of spontaneous echo contrast in the left atrium and aortic arch atheroma ≥4 mm on cognitive function (+) (Fig. 3). A total of 44 participants (34.9%) were in neither group, 67 participants (53.2%) were in either the spontaneous echo contrast (+) or the aortic-arch plaque max thickness ≥4 mm group, while 15 participants (11.9%) were in both groups. There were significant differences in MMSE (p < 0.001), HDS-R (p < 0.001), and FAB (p < 0.01) among the three groups. A post-hoc analysis revealed that although the cognitive function of participants in both groups was significantly lower than in participants that did not appear in either group, no significance differences were observed in MMSE in intra-group and inter-group comparisons, but only showed a decreasing tendency (p = 0.05).

Fig. 3

Comparison of cognitive function between two groups. In the first group, participants displayed neither spontaneous echo contrast (+) nor an aortic arch plaque with a maximum thickness ≥4 mm. In the second group, participants displayed either spontaneous echo contrast (+) or an aortic arch plaque with a maximum thickness ≥4 mm. In the third group, participants displayed both spontaneous echo contrast (+) and an aortic arch plaque with a maximum thickness ≥4 mm.

Finally, we analyzed the association between TEE findings and 16 patients that were previously diagnosed with or treated for AD (Table 3). A logistic regression analysis indicated an odds ratio of 4.76 for the spontaneous echo contrast (p < 0.05^*) and of 3.99 for aortic-arch plaque maximum thickness (p < 0.05^*). Other parameters showed no significant relationships.

Table 3

Association between TEE findings and AD patients

TEE finding		AD		Odds ratio	p
		(–)	(+)
	n (%)	110 (87.3)	16 (12.7)
Spontaneous echo contrast	(–)	79	7	4.76	<0.05^*a
	(+)	31	9
PFO	(–)	89	15	5.12	0.16
	(+)	17	1
Aortic-arch plaque max thickness	<4 mm	63	6	3.99	<0.05^*
	≥4 mm	47	10
Aorta-arch plaque ulcer or mobile	(–)	91	13	1.17	0.85
	(+)	19	3
Branch extending plaque	(–)	78	11	1.34	0.66
	(+)	32	5

AD, Alzheimer’s disease; PFO, patent foramen ovale; TEE, Transesophageal echocardiography. ^alogistic regression analysis was performed. ^*p < 0.05.

DISCUSSION

Our results indicate three main findings: 1) the cognitive function of participants with a spontaneous echo contrast (+) in the left atrium, and including an appendage, was significantly worse; 2) the cognitive function of participants with an aortic arch atheroma ≥4 mm decreased significantly; 3) neither PFO nor branch extending plaque were associated with cognitive function.

The results of this study should be carefully considered to identify whether the factors that influence post-stroke dementia (PSD) or dementia develop from a pathology independent of vascular diseases. PSD is a clinical entity that encompasses all types of dementia following an index event [30]. A previous report showed that the prevalence rate of PSD was two-thirds higher than the prevalence of vascular dementia and one-third higher than the prevalence of AD [31]. Although PSD is considered to be important for the determination of dementia, the actual pathology has not yet been clearly elucidated [32, 33]. In conclusion, our study did not strictly separate the interaction between cerebrovascular disease and AD from the PSD pathology because all participants were stroke survivors and because all of the subjects in this study had a history of ischemic stroke. Our study encompassed two conditions, dementia after a stroke independent from PSD, and associated with PSD. Thus, simple cognitive function was established as the analyzed result in this study, emphasizing that the AD conversion rate was not a result.

Accordingly, the cognitive function of patients with spontaneous echo contrast (+) in the left atrium, including an appendage, decreased significantly. This result supports the findings of previous reports and suggests that venous flow congestion may be associated with AD pathology [8, 9]. Although there are only a few reports that focused on the association between venous blood flow and cognitive impairment, including AD pathology, a 4D flow MRI study revealed a significantly decrease in the velocities of the intracranial venous sinus such as the superior sagittal sinus and transverse sinus [34]. We also previously reported that spontaneous echo contrast and the velocity of IJV were significantly correlated with AD, cognitive function, and the Fazekas scale [8]. Other reports have shown a relationship between AF and cognitive function [35], with AF leading to a decrease in cognitive function independently of the history of arterial stroke [36]. These studies (i.e., intracranial venous flow analyzed by 4D MRI, IJV analyzed by ultrasonography, and AF-related research) all confirm that a disturbance to venous flow occurs during cognitive impairment, including AD pathology. In terms of brain perfusion, several groups have proposed that clearance of the drainage system by cerebrovascular dynamics plays an important role in AD pathology [37, 38] because a healthy venous state is required for the cleavage and clearance of Aβ and related products [39]. Since the brain lacks a traditional lymphatic system for clearing waste products, it has been hypothesized that cerebral vascular motion is involved with the perivascular fluid compartment [40]. This vascular motion affects some of the pathways, such as changes in blood vessel caliber from both the cardiac cycle pulsations [41] and low-frequency flow oscillations (LFOs) induced by the smooth muscles of the arterial wall [42]. Previous data suggest that decreased vascular elasticity may diminish both cardiac cycle-induced changes in blood vessel caliber and LFOs, inducing a venous reflux of congestive flow and resulting in reduced clearance of Aβ and related products [43, 44]. The destructive impact of the pulse flow on cerebral vasculature may induce brain damage [45] and venous flow congestion, which is detected as spontaneous echo contrast (+) in TEE, can decrease the durability of the pulse.

The cognitive function of participants with an aortic arch atheroma ≥4 mm decreased significantly, while the presence of a branch extending plaque did not influence cognitive function. This suggests that the aorta-arch status is important for cognitive function, more so than the simple atheromatous. Microemboli are considered to be associated with cognitive decline [15 –17], and aortic arch atheroma is the major embolic source here; it is also a source for cardioembolism [29]. Ischemic stroke due to plaque in the aortic arch is classified as a “stroke of other determined etiology” in the TOAST criteria [24] and is considered separately from atherosclerotic ischemic stroke subtypes [29]. An aortic arch atheroma ≥4 mm would not only be a simple atherosclerotic change but will also have several confounding factors, such as an abnormal lipid profile, chronic kidney disease, and an abnormal white blood cell subtype profile [46 –49]. Moreover, the aortic arch receives the most evident jet flow [50 –52]. A more complex status of arterial impairment, for example, vasomotion of cerebrovascular smooth muscle failure or failure of the intramural periarterial drainage system, has the possibility of being associated with the pathology of AD more than atherosclerotic changes [9 , 54]. In this sense, the status of the aortic arch may be related. Although there was no significance difference, possibly due to the small sample size (n = 15) between the spontaneous echo contrast (+) and the aortic arch atheroma ≥4 mm group, our results suggest the possibility that cardiac venous flow impairment and aortic arch impairment status are independently and synergistically involved in cognitive impairment. We propose a synergistic hypothesis: since the background evidently becomes risky and the risk of embolic stroke increases when there are multiple sources of stroke [55], this would involve both a disturbance in brain perfusion and microemboli. Our results suggest that two pathologies are possible based on cognitive impairment, namely a disturbance of synergistic brain perfusion by AF and microemboli by aortic arch atheroma or microemboli as the major cause, and AF with aortic arch atheroma synergistically involved as a multiple embolic source.

This study has several limitations. First, all participants that were included had a history of ischemic stroke, and participants without ischemic stroke or a healthy control group were not included. Second, this study was conducted at a single institute, so sample location and size were limited. Third, the analyzed relationship was limited to a simple cognitive function and the conversion of dementia via a longitudinal study was not performed. We recognize that the pathological disease relationship was not analyzed. Fourth, associated with the first limitation, our study was unable to separate two conditions, i.e., dementia after stroke independent from PSD and association with PSD. Fifth, an age-adjusted comparison was not performed. Finally, there may be selection bias in the form of confounding factors such as aging, AF, and cognitive decline.

In conclusion, a spontaneous echo contrast in the left atrium and an aortic arch atheroma detected by TEE were negatively correlated with cognitive function.

Footnotes

ACKNOWLEDGMENTS

We extend our appreciation to the participants who cooperated in the study as well as the medical staff involved in the study. We thank Editage (http://www.editage.com) and SciRevision () for English language editing. We also appreciate cooperative by Dr. Kumiko Miura.

This work was partly supported by a grant from the Konica Minolta Science and Technology Foundation (Konica Minolta Imaging Science Encouragement Award).

Authors’ disclosures available online ().

References

Daly

, Walsh

(2019) Dementia-a major public health problem: The role of in-patient psychiatric facilities. Ir J Med Sci 188, 641–647.

Abbott

(2011) Dementia: A problem for our age. Nature 475, S2–S4.

Fratiglioni

, Grut

, Forsell

, Viitanen

, Grafström

, Holmén

, Ericsson

, Bäckman

, Ahlbom

, Winblad

(1991) Prevalence of Alzheimer’s disease and other dementias in an elderlyurban population: Relationship with age, sex, and education. Neurology 41, 1886–1892.

Atamna

, Frey

2nd (2004) A role for heme in Alzheimer’s disease: Heme binds amyloid beta and has altered metabolism. Proc Natl Acad Sci U S A 101, 11153–11158.

Nedergaard

(2013) Neuroscience. Garbage truck of the brain. Science 340, 1529–1530.

Sweeney

, Sagare

, Zlokovic

(2018) Blood-brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat Rev Neurol 14, 133–150.

Wardlaw

, Smith

, Biessels

, Cordonnier

, Fazekas

, Frayne

, Lindley

, O’Brien

, Barkhof

, Benavente

, Black

, Brayne

, Breteler

, Chabriat

, Decarli

, de Leeuw

, Doubal

, Duering

, Fox

, Greenberg

, Hachinski

, Kilimann

, Mok

, Oostenbrugge

, Pantoni

, Speck

, Stephan

, Teipel

, Viswanathan

, Werring

, Chen

, Smith

, van Buchem

, Norrving

, Gorelick

, Dichgans

; STandards for ReportIng Vascular changes on nEuroimaging (STRIVE v1) (2013) Neuroimaging standards for research into small vesseldisease and its contribution to ageing and neurodegeneration. Lancet Neurol 12, 822–838.

Matsuzono

, Suzuki

, Miura

, Ozawa

, Mashiko

, Koide

, Tanaka

, Fujimoto

(2021) Internal jugular vein velocity and spontaneous echo contrast correlate with Alzheimer’s disease and cognitive function. J Alzheimers Dis 84, 787–796.

Ghali

MGZ

, Marchenko

, Yasargil

, Ghali

(2020) Structure and function of the perivascular fluid compartment and vertebral venous plexus: Illumining a novel theory on mechanisms underlying the pathogenesis of Alzheimer’s, cerebral small vessel, and neurodegenerative diseases. Neurobiol Dis 144, 105022.

10.

Moody

, Brown

, Challa

, Anderson

(1995) Periventricular venous collagenosis: Association with leukoaraiosis. Radiology 194, 469–476.

11.

Daniel

, Mugge

(1995) Transesophageal echocardiography. N Engl J Med 332, 1268–1279.

12.

Khandheria

, Seward

, Tajik

(1994) Transesophageal echocardiography. Mayo Clin Proc 69, 856–863.

13.

Daniel

, Erbel

, Kasper

, Visser

, Engberding

, Sutherland

, Grube

, Hanrath

, Maisch

, Dennig

(1991) Safety of transesophageal echocardiography. A multicenter survey of 10,419 examinations. Circulation 83, 817–821.

14.

Yan

, Li

, Wills

, Rajah

, Wang

, Bai

, Dong

, Zhao

(2021) Intracranial microembolic signals might be a potential risk factor for cognitive impairment. Neurol Res 43, 867–873.

15.

Russell

(2002) Cerebral microemboli and cognitive impairment. J Neurol Sci 203, 211–214.

16.

van Veluw

, Zwanenburg

, Engelen-Lee

, Spliet

, Hendrikse

, Luijten

, Biessels

(2013) In vivodetection of cerebral cortical microinfarcts with high-resolution 7T MRI, J Cereb Blood Flow Metab 33, 322–329.

17.

Cheng

, Liu

, Li

(2018) Relationship of anticoagulant therapy with cognitive impairment among patients with atrial fibrillation: A meta-analysis and systematic review. J Cardiovasc Pharm 71, 380–387.

18.

Gardarsdottir

, Sigurdsson

, Aspelund

, Rokita

, Launer

, Gudnason

, Arnar

(2018) Atrial fibrillation is associated with decreased total cerebral blood flow and brain perfusion. Europace 20, 1252–1258.

19.

Nys

, van Zandvoort

, de Kort

, Jansen

, de Haan

, Kappelle

(2007) Cognitive disorders in acute stroke: Prevalence and clinical determinants. Cerebrovasc Dis 23, 408–416.

20.

Zhong

, Bu

, Xu

, Guo

, Wang

, Zhang

, Cui

, Li

, Zhang

, Ju

, Chen

, Zhang

, He

(2018) Serum matrix metalloproteinase-9 and cognitive impairment after acute ischemic stroke. J Am Heart Assoc 7, e007776.

21.

Liao

, Zuo

, Zhang

, Yang

, Pan

, Xiang

, Chen

, Meng

, Li

, Zhao

, Wang

, Shi

, Wang

; Impairment of CognitiON and Sleep quality for patients after acute ischemic stroke or transient ischemic attack (ICONS) Investigators (2020) The occurrence and longitudinal changes of cognitive impairment after acute ischemic stroke. Neuropsychiatr Dis Treat 16, 807–814.

22.

Wang

, Wang

, Zhao

, Liu

, Wang

, Li

, Meng

, Cui

, Jia

, Dong

, Xu

, Zeng

, Li

, Wang

, Xia

, Johnston

; CHANCE Investigators (2013) Clopidogrel with aspirin in acute minor stroke or transient ischemic attack. N Engl J Med 369, 11–19.

23.

Johnston

, Easton

, Farrant

, Barsan

, Conwit

, Elm

, Kim

, Lindblad

, Palesch

; Clinical Research Collaboration, Neurological Emergencies Treatment Trials Network, and the POINT Investigators (2018) Clopidogrel and aspirin in acute ischemic stroke and high-risk TIA. N Engl J Med 379, 215–225.

24.

Gordon

, Bendixen

, Adams

Jr. , Clarke

, Kappelle

, Woolson

(1993) Interphysician agreement in the diagnosis of subtypes of acute ischemic stroke: Implications for clinical trials. The TOAST Investigators. Neurology 43, 1021–1027.

25.

Sacco

, Kasner

, Broderick

, Caplan

, Connors

, Culebras

, Elkind

, George

, Hamdan

, Higashida

, Hoh

, Janis

, Kase

, Kleindorfer

, Lee

, Moseley

, Peterson

, Turan

, Valderrama

, Vinters

; American Heart Association Stroke Council, Council on Cardiovascular Surgery and Anesthesia; Council on Cardiovascular Radiology and Intervention; Council on Cardiovascular and Stroke Nursing; Council on Epidemiology and Prevention; Council on Peripheral Vascular Disease; Council on Nutrition, Physical Activity and Metabolism (2013) An updated definition of stroke for the 21st century: A statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 44, 2064–2089.

26.

Matsuzono

, Arai

, Suzuki

, Kim

, Ozawa

, Mashiko

, Shimazaki

, Koide

, Matsuura

, Fujimoto

(2018) Tissue plasminogen activator to treat a stroke after foam sclerotherapy in a woman with a patent foramen ovale, J Stroke Cerebrovasc Dis 27, e110–e112.

27.

Suzuki

, Furuya

, Ozawa

, Miura

, Ozawa

, Matsuzono

, Mashiko

, Koide

, Fujimoto

, Tanaka

(2021) Complex aortic arch atherosclerosis in acute ischemic stroke patients with non-valvular atrial fibrillation. J Atheroscler Thromb 28, 776–785.

28.

Fujimoto

, Yasaka

, Otsubo

, Oe

, Nagatsuka

, Minematsu

(2004) Aortic arch atherosclerotic lesions and the recurrence of ischemic stroke. Stroke 35, 1426–1429.

29.

Macleod

, Amarenco

, Davis

, Donnan

(2004) Atheroma of the aortic arch: An important and poorly recognised factor in the aetiology of stroke. Lancet Neurol 3, 408–414.

30.

, Chen

(2017) Post-stroke dementia: Epidemiology, mechanisms and management. Int J Gerontol 11, 210–214.

31.

Henon

, Durieu

, Guerouaou

, Lebert

, Pasquier

, Leys

(2001) Poststroke dementia: Incidence and relationship to prestroke cognitive decline. Neurology 57, 1216–1222.

32.

Pendlebury

, Rothwell

(2009) Prevalence, incidence, and factors associated with pre-stroke and post-stroke dementia: A systematic review and meta-analysis. Lancet Neurol 8, 1006–1018.

33.

Allan

, Rowan

, Firbank

, Thomas

, Parry

, Polvikoski

, O’Brien

, Kalaria

(2011) Long term incidence of dementia, predictors of mortality and pathological diagnosis in older stroke survivors. Brain 134, 3716–3727.

34.

Rivera-Rivera

, Schubert

, Turski

, Johnson

, Berman

, Rowley

, Carlsson

, Johnson

, Wieben

(2017) Changes in intracranial venous blood flow and pulsatility in Alzheimer’s disease: A 4D flow MRI study. J Cereb Blood Flow Metab 37, 2149–2158.

35.

Saji

, Sakurai

, Ito

, Tomimoto

, Kitagawa

, Miwa

, Tanaka

, Kozaki

, Kario

, Eto

, Suzuki

, Shimizu

, Niida

, Hirakawa

, Toba

; Strawberry study investigators (2018) Protective effects of oral anticoagulants on cerebrovascular diseases and cognitive impairment in patients with atrial fibrillation: Protocol for a multicentre, prospective, observational, longitudinal cohort study (Strawberry study). BMJ Open 8, e021759.

36.

Kalantarian

, Ruskin

(2013) Cognitive impairment associated with atrial fibrillation–in response. Ann Intern Med 158, 849.

37.

Weller

, Subash

, Preston

, Mazanti

, Carare

(2008) Perivascular drainage of amyloid-beta peptides from the brain and its failure in cerebral amyloid angiopathy and Alzheimer’s disease. Brain Pathol 18, 253–266.

38.

Hawkes

, Jayakody

, Johnston

, Bechmann

, Carare

(2014) Failure of perivascular drainage of beta-amyloid in cerebral amyloid angiopathy. Brain Pathol 24, 396–403.

39.

Naliyaeya

, Turner

(2019) Targeting amyloid clearance in Alzheimer’s disease as a therapeutic strategy. Br J Pharmacol 176, 3447–3463.

40.

Weller

, Boche

, Nicoll

JAR

(2009) Microvasculature changes and cerebral amyloid angiopathy in Alzheimer’s disease and their potential impact on therapy. Acta Neuropathol 118, 87–102.

41.

Diem

, MacGregor Sharp

, Gatherer

, Bressloff

, Carare

, Richardson

(2017) Arterial pulsations cannot drive intramural periarterial drainage: Significance for Abeta drainage. Front Neurosci 11, 475.

42.

Rivera-Rivera

, Cody

, Rutkowski

, Cary

, Eisenmenger

, Rowley

, Carlsson

, Johnson

(2020) Intracranial vascular flow oscillations in Alzheimer’s disease from 4D flow MRI. Neuroimage Clin 28, 102379.

43.

Di Marco

, Farkas

, Martin

, Venneri

, Frangi

(2015) Is vasomotion in cerebral arteries impaired in Alzheimer’s disease? J Alzheimers Dis 46, 35–53.

44.

Plog

, Nedergaard

(2018) the glymphatic system in central nervous system health and disease: Past, present, and future. Annu Rev Pathol 13, 3793–3794.

45.

Stone

, Johnstone

, Mitrofanis

, O’Rourke

(2015) The mechanical cause of age-related dementia (Alzheimer’s disease): The brain is destroyed by the pulse. J Alzheimers Dis 44, 355–373.

46.

Kong

, Ma

, Wang

, Feng

, Ovbiagele

, Zhang

, Du

, Fang

(2019) Influence of age ranges on relationship of complex aortic plaque with cervicocephalic atherosclerosis in ischemic stroke. J Stroke Cerebrovasc Dis 28, 1586–1596.

47.

Machino-Ohtsuka

, Seo

, Ishizu

, Sekiguchi

, Sato

, Tada

, Watanabe

, Aonuma

(2010) Combined assessment of carotid vulnerable plaque, renal insufficiency, eosinophilia, and hs-CRP for predicting risky aortic plaque of cholesterol crystal embolism. Circ J 74, 51–58.

48.

Elkind

MSV

, Sciacca

, Boden-Albala

, Homma

, Di Tullio

(2002) Leukocyte count is associated with aortic arch plaque thickness. Stroke 33, 2587–2592.

49.

Kitano

, Nezu

, Shiromoto

, Kubo

, Uemura

, Wada

, Yagita

(2017) Association between absolute eosinophil count and complex aortic arch plaque in patients with acute ischemic stroke. Stroke 48, 1074–1076.

50.

Garcia

, Barker

, Markl

(2019) The role of imaging of flow patterns by 4D flow MRI in aortic stenosis. JACC Cardiovasc Imaging 12, 252–266.

51.

Mohiaddin

, Kilner

, Rees

, Longmore

(1993) Magnetic resonance volume flow and jet velocity mapping in aortic coarctation. J Am Coll Cardiol 22, 1515–1521.

52.

Sigovan

, Hope

, Dyverfeldt

, Saloner

(2011) Comparison of four-dimensional flow parameters for quantification of flow eccentricity in the ascending aorta. J Magn Reson Imaging 34, 1226–1230.

53.

Aldea

, Weller

, Wilcock

, Carare

, Richardson

(2019) Cerebrovascular smooth muscle cells as the drivers of intramural periarterial drainage of the brain. Front Aging Neurosci 11, 1.

54.

van Veluw

, Hou

, Calvo-Rodriguez

, Arbel-Ornath

, Snyder

, Frosch

, Greenberg

, Bacskai

(2020) Vasomotion as a driving force for paravascular clearance in the awake mouse brain. Neuron 105, 549–561.

55.

Anan

, Mashiko

, Matsuzono

, Miura

, Ozawa

, Suzuki

, Ozawa

, Kameda

, Koide

, Tanaka

, Fujimoto

(2022) Coexisting of aortic arch atheroma and atrial fibrillation for short-term recurrence and poor functional outcome in acute stroke. Neurol Sci 43, 2387–2396.