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Article

Impaired Cerebral Hemodynamics in Asymptomatic Carotid Artery Stenosis Assessed by Resting-State Functional MRI

by
Kaio F. Secchinato
1,
Pedro H. R. da Silva
2,
Guilherme R. Rodrigues
3,
Ana P. A. C. Ferreira
3,
Octavio M. Pontes-Neto
3 and
Renata F. Leoni
1,*
1
Departamento de Física, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14040-901, Brazil
2
Serviço Interdisciplinar de Neuromodulação, Laboratório de Neurociências, Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo 05508-220, Brazil
3
Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14049-900, Brazil
*
Author to whom correspondence should be addressed.
J. Vasc. Dis. 2025, 4(2), 15; https://doi.org/10.3390/jvd4020015
Submission received: 28 February 2025 / Revised: 21 March 2025 / Accepted: 1 April 2025 / Published: 7 April 2025
(This article belongs to the Section Neurovascular Diseases)
Browse Figures
Versions Notes

Abstract

:
Background/Objectives: Cerebrovascular reactivity (CVR) and time shift (TS) are vascular-related parameters that reflect cerebral perfusion and may be associated with the risk of developing stroke in patients with asymptomatic carotid artery stenosis (ACAS). We investigated CVR and TS in patients with ACAS using resting-state magnetic resonance imaging based on blood-oxygen-level-dependent contrast (BOLD-MRI). Methods: We included twenty patients with severe unilateral ACAS and twenty age-matched controls. Individual CVR maps were obtained through a voxel-wise regression of the MRI signal, using the global signal filtered in a specific frequency range (0.02–0.04 Hz) as the regressor. A recursive cross-correlation method provided individual TS maps through the BOLD low-frequency fluctuation. CVR and TS values were obtained for the territories irrigated by the main cerebral arteries (anterior, middle, and posterior) separated into proximal, intermediary, and distal regions. Results: Compared to controls, ACAS patients presented reduced CVR and increased TS in the distal parts of the brain vascular territories. Individual CVR and TS values varied more within the patient group than controls. Such individual variability may help identify patients eligible for intervention better than the stenosis grade. Conclusions: CVR and TS may indicate subtle hemodynamic changes and assist in identifying regions at higher risk of neuronal damage or ischemic stroke on an individual basis, aiding in the stratification of patients with ACAS based on their risk of progressing to stroke.

1. Introduction

Cerebrovascular diseases are an important health problem with high prevalence, mortality, and morbidity. Among its subtypes, atherosclerotic disease involving the carotid artery is strongly associated with ischemic stroke due to arterial embolism and hemodynamic impairment [1,2]. Asymptomatic carotid artery stenosis (ACAS), defined as the narrowing of the internal carotid artery (ICA) lumen in individuals with no history of ipsilateral stroke or transient ischemic attack (TIA), causes approximately 10% of all strokes [3]. Although considered asymptomatic, cognitive decline and dementia have been associated with ACAS, probably due to chronic cerebral hypoperfusion [4].
Management of ACAS is contingent upon the degree of stenosis. The 2022 Society for Vascular Surgery clinical practice guidelines recommend revascularization, such as endarterectomy and stenting, for patients with severe stenosis (>70%) at significant risk of stroke [5]. Although effective, the interventions present periprocedural risks [6]. Moreover, patients with similar clinical stenosis classification may have significant differences in hemodynamics and collateral flow [6,7]. Therefore, since the annual stroke risk is <1% if the ACAS patient is under the best medical therapy [8], the classification of patients based on their potential benefit from more invasive treatment is crucial.
Magnetic resonance imaging (MRI) markers of cerebrovascular diseases may help stratify and manage such patients [9], including risk assessment for future stroke and evaluating subclinical tissue changes. Recent studies have reported cerebrovascular reactivity (CVR) as an additional tool to assess if the patient is genuinely asymptomatic and to predict stroke risk [10]. Blood-oxygenation-level-dependent (BOLD) MRI combined with vasoactive stimuli, such as hypercapnia, has been widely used to assess CVR in normal aging and cerebrovascular diseases [11,12,13,14,15]. BOLD-MRI is sensitive to local cerebral perfusion changes and is thus helpful for cerebrovascular assessment [16]. In contrast to the transcranial Doppler ultrasound that provides CVR from a specific artery based on differences in blood velocity, BOLD-MRI yields a brain CVR map, which can show regions with impaired hemodynamics [17]. Despite its high clinical potential [18], vasoactive stimuli require a specific apparatus or individual collaboration [19].
Recently, natural variations in breathing patterns were explored to extract the CVR information from resting-state (RS) BOLD data. Liu and colleagues used the end-tidal CO2 recorded during the RS-MRI scan and showed that the frequency band of 0.02–0.04 Hz contains significant fluctuations in CO2 [20]. Golestani and colleagues reported a validation study in healthy adults, proving an approach for quantitative mapping of CVR [21]. Another study performed the same analysis in ACAS patients and reported that the data filtered in the same frequency band showed the highest correlation with the hypercapnia-based data [22]. Such studies compared their results with measurements obtained using BOLD acquisition under hypercapnia challenge, showing that RS-CVR mapping is reliable as a quantitative tool to map CVR. Moreover, other studies have successfully applied the methodology to different brain diseases [23,24,25,26].
However, RS-CVR mapping relies on the reference time series used in the regression and the temporal variability of hemodynamic measures among patients. Such a temporal lag related to tissue perfusion delay can be measured by analyzing the time shift (TS) of the RS-BOLD signal [27,28]. TS values are estimated by cross-correlating the BOLD signal of all voxels with some reference signal, which is not yet standardized but may include the gray matter signal [29], the homotopic signal from the non-lesioned hemisphere [30], global signal [23], or one which is obtained through a mask that is updated at each step [25]. This method was able to assess vascular hemodynamics in acute and subacute stroke, mild cognitive impairments, and Alzheimer’s disease, revealing the extent and severity of perfusion delay in these patients [24,31,32].
Therefore, we investigated RS-CVR and TS in ACAS patients compared to age-matched controls. CVR and TS values were obtained for the territories irrigated by the main cerebral arteries (anterior, ACA; middle, MCA; posterior, PCA) separated into proximal, intermediary, and distal regions. This is the first study to subdivide the territories to study hemodynamic alterations in ACAS patients. We hypothesize that these vascular-related parameters can discern hemodynamic alterations associated with stenosis, offering a noninvasive means of evaluating brain hemodynamics in ACAS patients. Our findings hold promise for refining risk stratification strategies and guiding personalized management approaches in this patient population.

2. Materials and Methods

2.1. Subjects

Twenty patients with severe unilateral ACAS (12 women, 8 men; mean age = 67.0 ± 10.2 years) and twenty age-matched controls (8 women, 12 men; mean age = 67.5 ± 7.3 years) participated in this study after signing informed consent forms. The inclusion criterion for patients was asymptomatic, severe unilateral carotid artery stenosis (≥70% of carotid occlusion), and for controls, the absence of atherosclerotic disease of the carotid arteries identified by an experienced neuroradiologist through magnetic resonance angiography (MRA). The exclusion criteria for patients and controls were any cerebrovascular event, including transient ischemic attack; severe bilateral stenosis (≥70% of carotid occlusion); neurologic disorders, such as epilepsy, multiple sclerosis, amyotrophic lateral sclerosis, brain tumor, Binswanger’s disease, and dementia; psychiatric disorders; dependence on alcohol and/or other neurotoxic substances in the last 12 months; verbal communication disorders; pregnancy; claustrophobia; and MRI contraindications. Patients with risk factors, such as hypertension and diabetes, were not excluded to avoid masking the actual profile of the patient group. Table 1 shows the demographic information for all patients.

2.2. MRI Acquisition

All images were acquired using a 3T MR system (Achieva, Philips Medical Systems, Best, The Netherlands), equipped with gradients of 80 mT/m of amplitude and 200 mT/m/ms of slew rate. A transmit body coil and a 32-channel receive-only head coil were used. Whole-brain structural images were acquired using a three-dimensional T1-weighted (3DT1), gradient-echo sequence with TR/TE = 6.7/3.1 ms, flip angle = 8°, matrix = 256 × 256, FOV = 256 × 256 mm2, number of slices = 180, and slice thickness = 1 mm. Two time-of-flight (TOF) angiograms (MRA) were acquired for the visualization of the internal carotid arteries (ICAs) and vertebral arteries (VAs) to assess the stenosis or occlusion. A clinical routine sequence was used with TR/TE = 20/3.5 ms, flip angle = 30°, matrix = 512 × 512, FOV = 200 × 200 mm2, number of slices = 175, and slice thickness = 1.1 mm.
Resting-state BOLD-MRI was acquired using an echo-planar (EPI) readout and the following parameters: TR/TE = 2000/30 ms, flip angle = 90°, matrix = 128 × 128, FOV = 230 × 230 mm2, number of slices = 31, slice thickness = 4 mm, slice gap = 0.5 mm, 200 dynamics, and acquisition duration = 6 min and 40 s. Physiological parameters, such as heart rate, respiratory rate, and end-tidal CO2, were monitored during the exam. They remained within normal values for all participants throughout the acquisition.

2.3. Image Preprocessing

BOLD data were preprocessed using SPM12 (University College London, London, UK) and subsequent analyses using our routines written in MATLAB R2022b. The first four volumes of each run were discarded to ensure a steady state. Preprocessing included reorientation using the anterior commissure as a reference point for the origin, slice time correction, realignment for correction of motion artifacts, co-registration with anatomical images, normalization to MNI space, resizing to 4 mm isotropic voxels to ensure proper signal-to-noise ratio at each voxel, and smoothing using a Gaussian filter (full width at half maximum, FWHM = 6 mm). Anatomical 3DT1 images were automatically segmented into gray matter, white matter, and cerebrospinal fluid masks, and a whole-brain mask was obtained, joining these three masks.

2.4. Resting-State Cerebrovascular Reactivity (RS-CVR)

Individual RS-CVR maps were obtained following previously reported procedures [20]. The first step was the temporal filtering of the whole-brain BOLD time course using the optimal frequency band (0.02–0.04 Hz) determined from a previous study with subjects of the same age range [20,22]. In such a frequency band, the resting-state BOLD signal strongly correlates with CO2 partial pressure changes in the blood. The whole-brain mask was used as a reference mask, and the time courses of the voxels inside the mask were averaged to yield the reference time course. A linear regression analysis was then performed in which the reference time course was the independent variable and the time course of each voxel was the dependent variable, yielding a CVR index for each voxel. Finally, each CVR index was normalized to a mean value calculated from the reference mask, providing the resting-state CVR map (RS-CVR).
For each subject’s map, nine regions of interest (ROIs) for each hemisphere were selected based on the atlas of the territories of the main cerebral arteries (anterior carotid artery, ACA; middle carotid artery, MCA; posterior carotid artery, PCA), based on the proximal, intermediate, and distal flow [33], using arterial transit time (ATT). Thus, for each subject, eighteen values of CVR were obtained. For patients, we considered the hemispheres ipsilateral or contralateral to the stenosis.

2.5. Time Shift (TS)

Data were preprocessed as previously described, with the additional removal of linear trending and temporal band-pass filtering (0.02–0.12 Hz). The method for obtaining a TS map has been thoroughly detailed in previous studies [24,25]. We used the average whole-brain signal to make the initial reference time course, which was correlated with all voxels’ time courses in the brain. Voxels with a correlation coefficient greater than 0.2 were then grouped in a new mask, and the mean time course was used as the new regressor for the recursive procedure. The reference time was updated recursively using the combined signal of voxels with the correlation criterion met (r > 0.2). The step for the update was 0.5 s. This procedure was repeated eight times to achieve tracking of 4 s.
We calculated the average TS values for the same eighteen ROIs based on the vascular territories [33]. For patients, we considered the hemispheres ipsilateral or contralateral to the stenosis.

2.6. Statistical Analysis

A t-test was used to compare ages between groups, while a chi-square test was performed to compare sex distribution. Mean CVR and TS values calculated for the eighteen ROIs were used for the statistical analysis. The normality of the CVR and TS variables was tested with the Kolmogorov–Smirnov test. These values were submitted to an intra-subject statistical analysis in R (version 3.6.0) [34], a two-factor ANOVA with repeated measures, and Tukey’s post-hoc test to test the hypothesis of significant differences between hemispheres and territories (p < 0.05) within the groups. Such an analysis was performed for each group separately. Then, both CVR and TS values were compared between groups using ANOVA and Tukey’s post-hoc test (p < 0.05). In this case, for the control group, the average value of CVR and TS for each territory was used, considering both hemispheres together.

3. Results

Age (p = 0.27) and sex (p = 0.20) were not significantly different between groups. All patients had dyslipidemia, 85% had hypertension, and only 3% had diabetes.
Figure 1 shows the RS-CVR maps of all patients and controls. Figure 2 shows mean RS-CVR values for each group and vascular territory. First, we analyzed each group separately. The control group’s variance analysis showed no effect of the hemisphere (p = 0.32) but a significant vascular territory effect (p = 10−16) on RS-CVR values. Once no significant hemisphere effect was observed, we continued the analysis considering both hemispheres together, totaling nine regions. The proximal part of the ACA territory showed reduced RS-CVR compared to the intermediary and distal portions (p = 10−9), and the proximal part of the MCA territory showed reduced RS-CVR when compared to the distal portion (p = 10−3). Also, the intermediary part of the PCA territory showed mean RS-CVR values higher than for the proximal region (p = 0.03). When considering the whole territory for each artery, higher and lower RS-CVR values were observed for PCA and ACA, respectively, compared to MCA territory (p < 10−10).
For patients, no statistical difference in RS-CVR was observed between hemispheres (p = 0.18). However, significant differences were observed among regions (p = 10−16). For both hemispheres, compared to the proximal portion of the ACA territory, reduced values were observed for the distal (contralateral—p = 10−5; ipsilateral—p = 10−5) and intermediary parts (contralateral—p = 10−4; ipsilateral—p = 0.003) of the same territory. For the MCA territory, reduced values were observed for the proximal part compared to the distal one (contralateral—p = 0.007; ipsilateral—p = 0.008). Moreover, the mean RS-CVR values were significantly higher in the intermediary PCA territory than the distal part for the hemisphere ipsilateral to the stenosis (p = 0.01). When considering the whole territory for each artery, reduced RS-CVR values were observed for MCA in both hemispheres compared to ACA and PCA territories (p < 10−7).
Finally, we compared patients with controls. Mean RS-CVR values for the distal ACA territory in patients were significantly lower in both hemispheres (contralateral—p = 0.009; ipsilateral—p = 0.008) compared to controls. However, for the proximal ACA territory, such values were significantly higher for patients (contralateral—p = 10−5; ipsilateral—p = 10−5) than for the control group.
Figure 3 shows the TS map of each subject. Longer time shifts are displayed in warm colors. Figure 4 shows the mean TS values for each group and vascular territory. First, we analyzed each group separately. For the control group, the analysis of variance showed no hemisphere effect (p > 0.5) but a significant effect of the vascular territory (p = 10−7). When grouping the values for both hemispheres, TS for the proximal ACA territory showed higher values than for intermediary (p = 0.007) and distal (p = 10−4) ACA territories. Moreover, the TS value was longer for the ACA than for the PCA territory (p = 0.01). When considering the whole territory for each artery, reduced TS values were observed for PCA (p < 10−11).
For patients, TS was higher in the ipsilateral distal MCA compared to the same region in the contralateral hemisphere (p = 0.002). Moreover, TS values were longer in the three parts of the MCA territory and the distal part of the PCA territory in the ipsilateral hemisphere than the corresponding regions in the control group (proximal—p = 0.004; intermediary and distal—p = 0.002). When considering the whole territory for each artery, increased TS values were observed for MCA in both hemispheres (contralateral—p = 0.012; ipsilateral—p < 10−7).
Analyzing RS-CVR and TS together, the graph bars showed more significant variability within patients than controls, mainly for ACA and MCA values (Figure 2 and Figure 4). This reflected the variability observed in patients’ maps (Figure 1 and Figure 3). Compared to the general pattern of RS-CVR and TS maps observed for controls, seven patients showed reduced RS-CVR and increased TS, which were better visually observed in TS maps. All seven patients were women with different severe stenosis sides.

4. Discussion

We assessed CVR and TS in patients with ACAS using hypercapnic-free, resting-state BOLD-MRI fluctuations. We observed differences in RS-CVR and TS among vascular territories and their subdivisions within and between groups. However, patients showed no RS-CVR changes but altered TS between hemispheres. In contrast, the control group showed no hemispheric differences for both measures.
No hemispheric-related change in RS-CVR and TS in healthy adults was previously reported [35]. However, regional variations were described. The present results showed increased RS-CVR values for the PCA territory and increased TS values for the ACA and PCA territories. Inoue et al. reported no differences in CVR to acetazolamide (ACZ), measured with arterial spin labeling (ASL), among territories in healthy adults [36]. However, a long arrival time was observed in the PCA region [37], probably due to differences between carotid and vertebrobasilar circulations. ASL and BOLD measures with gas challenge showed increased and reduced CVR values in PCA and MCA regions and longer onset response in PCA territory [11,38].
The difference in temporal patterns between the present study and previous ones may be related to healthy aging [12,39], since our control group consisted of older adults. Aging has been related to modifications in blood vessels’ structure, such as the vessel’s thickness and radius, causing vascular stiffness, endothelial dysfunction, and increased blood–brain barrier permeability that alter cerebral hemodynamics. Moreover, we also observed RS-CVR and TS variability within each artery territory, which was not evaluated previously in healthy cohorts. Proximal portions of all territories showed decreased RS-CVR compared to distal portions for both hemispheres. Such findings may help identify regions more vulnerable to neurological diseases [40].
ACAS patients showed no RS-CVR changes between hemispheres. In contrast, previous studies using single-photon emission computed tomography (SPECT) and ACZ showed reduced ipsilateral CVR in about 80% of the ACAS patients and contralateral CVR in one-third of the group [41,42]. The lack of significant hemispheric differences in RS-CVR in our study may be due to the low sensitivity of the method, which depends on the temporal characteristics of the reference time series used in the regression model. Moreover, CVR maps showed high variability among subjects. Previously, Sebök et al. reported that the locations of hemodynamic deficits are highly subject-specific, even for patients with similar stenosis grades [35]. This is related to the different configurations of the circle of Willis that may cause very different patterns of collateral flow, as well as interindividual vasodilator capacity variation [43]. The presence of comorbidities may also explain the variability among patients. Hypertension affects the mechanisms of cerebral blood flow (CBF) regulation, including autoregulation and endothelial responses, acting on vessel wall elasticity [44]. In patients with atherosclerotic disease, it has been associated with elevated baseline CBF, which may influence CVR. Moreover, diabetes has several vascular complications, such as microvascular dysfunction, which can also affect blood flow to brain tissues [45]. Therefore, such individual variability may weaken the group analysis. On the other hand, it may identify patients eligible for intervention better than the stenosis grade.
However, ACAS patients showed altered TS between hemispheres, mainly in the MCA territory. In contrast with the control group, ACAS patients lost the TS gradient (higher in proximal than distal territories), notably in ipsilateral MCA territory. This territory is the most commonly affected by ischemic stroke due to its large size and the blood flowing directly from the internal carotid artery to the middle cerebral artery, providing the most straightforward pathway for thromboembolism [46]. As the TS reflects perfusion dynamics of vascular origin [23], our data suggest that this method is more sensitive to detecting temporal delays in larger-caliber vessels. Moreover, we also observed more significant regional TS variability among patients than controls. These data are relevant because several studies have associated hemodynamic disorders with a higher risk of stroke [47] or cognitive loss [48,49]. The different patterns among patients may explain their cognition status and stroke risk, helping stratify patients with ACAS.
Taking the CVR and TS results together, we can observe the prominence of changes in the distal part of the brain vascular territories. It has previously been shown that the distal flow presents the most significant variation and strongest correlation with age [33], suggesting that these are the most affected by cerebrovascular diseases [50]. Moreover, whole-brain vascular effects across the population can accumulate in distal flow territories, where perfusion measurements have the highest statistical power to detect vascular effects, even if these effects are expected to be distributed throughout the entire brain [33].
A BOLD-MRI study with breath-holding investigated the CVR in individual watershed areas (iWSA) of ACAS patients. Such areas are vulnerable to hemodynamic impairment and stroke associated with ICA stenosis [10]. They reported reduced CVR in ipsilateral iWSA compared with contralateral values. Decreased CVR was also observed in the contralateral iWSA compared to the healthy group [51]. Such findings suggest that unilateral ICA stenosis can affect both hemispheres due to hemodynamic stress. Therefore, iWSA may be the target location for future studies in ACAS patients.
This study has some limitations. First, the sample is small and heterogeneous, including bilateral stenosis, although not severe. However, previous studies with CVR evaluated with resting-state scans included fewer subjects [21,52] or similar sample sizes [25] while still drawing statistically significant conclusions. In comparison to the studies mentioned, we made progress by comparing patients with ACAS and healthy controls. Comparing patients with a well-matched healthy control group reduces the potential impact of extraneous factors that might confound results, such as age and other demographic characteristics. Second, sex and risk factors, such as hypertension and diabetes, were not evaluated. They may help elucidate the contrasting findings among patients. However, in addition to significantly reducing the size of the group, excluding patients with comorbidities would mask the actual profile of this group. Longitudinal studies with larger samples would establish normative cut-off values for CVR, which could facilitate clinical assessments and decision-making, in addition to allowing the evaluation of other important factors, such as comorbidities (diabetes, hypercholesterolemia, smoking, cognitive deficits, and mood disorders). Third, as the subjects were not under stress, this methodology may not assess the entire range of their cerebrovascular reserve. However, RS-CVR maps showed high similarity when compared to the hypercapnia challenge. Fourth, the RS-CVR maps were obtained on relative scales rather than in absolute units of %/mmHg CO2 due to the absence of end-tidal CO2 recordings. However, an intra-subject analysis to assess CVR deficits is of clinical interest; a quantitative value is not mandatory. Finally, it has been shown that the global BOLD signal within the 0.02–0.04 Hz frequency range has a stronger correlation with blood carbon dioxide concentration. However, it is possible that the signal in this frequency range still contains some contributions from unrelated sources. Therefore, recording the end-tidal CO2 fluctuations during the exam would allow for adjusting the most appropriate band frequency for each patient.

5. Conclusions

We successfully evaluated both CVR and TS in ACAS patients noninvasively and with no gas challenge in different subdivisions of the vascular territories. To the best of our knowledge, this is the first study to subdivide the territories to study hemodynamic alterations in ACAS patients. Different RS-CVR and TS patterns were observed among vascular territories within and between groups. The results indicate subtle hemodynamic changes and may assist in identifying regions at higher risk of neuronal damage or ischemic stroke on an individual basis, aiding in the stratification of patients with ACAS based on their risk of progressing to stroke. Combining CVR and TS measures in a multimodal imaging study may improve such stratification.

Author Contributions

Conceptualization, K.F.S. and R.F.L.; methodology, K.F.S., P.H.R.d.S., A.P.A.C.F. and R.F.L.; validation, O.M.P.-N. and R.F.L.; formal analysis, K.F.S. and P.H.R.d.S.; data curation, K.F.S. and A.P.A.C.F.; writing—original draft preparation, K.F.S.; writing—review and editing, K.F.S., P.H.R.d.S., A.P.A.C.F., G.R.R., O.M.P.-N. and R.F.L.; supervision, R.F.L.; funding acquisition, K.F.S. and R.F.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially funded by CAPES through scholarship. PHRS is a recipient of FAPESP grant 22/03266–0.

Institutional Review Board Statement

The study was approved by the Ethics Committee of Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto, Brazil (CAAE: 37162420.9.3001.0068, 3 December 2020).

Informed Consent Statement

Written informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are unavailable due to ethical restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ACAAnterior cerebral artery
ACASAsymptomatic carotid artery stenosis
ATTArterial transit time
BOLDBlood-oxygenation-level-dependent
CBFCerebral blood flow
CVRCerebrovascular reactivity
EPIEcho-planar imaging
FWHMFull width at half maximum
ICAInternal carotid artery
IRBInstitutional review board
MCAMiddle cerebral artery
MRAMagnetic resonance angiography
MRIMagnetic resonance imaging
MTTMean transit time
PCAPosterior cerebral artery
ROIsRegions of interest
RS-BOLDResting-state BOLD
RS-CVRResting-state cerebrovascular reactivity
rs-fMRIResting-state magnetic resonance imaging
sLFOsSystemic low-frequency oscillations
TIATransient ischemic attack
TSTime shift
TTPTime to peak
VAsVertebral arteries

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Figure 1. Resting-state cerebrovascular reactivity (RS-CVR) maps for patients (left) and control subjects (right). Maps are in relative units. Patients 1, 2, 5, 7, 9, 10, 13, 14, 17, and 19 had severe (>70%) left carotid artery stenosis (CAS), while the other patients had severe (>70%) right CAS. L = left hemisphere; R = right hemisphere.
Figure 1. Resting-state cerebrovascular reactivity (RS-CVR) maps for patients (left) and control subjects (right). Maps are in relative units. Patients 1, 2, 5, 7, 9, 10, 13, 14, 17, and 19 had severe (>70%) left carotid artery stenosis (CAS), while the other patients had severe (>70%) right CAS. L = left hemisphere; R = right hemisphere.
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Figure 2. Boxplots showing average resting-state cerebrovascular reactivity (RS-CVR) for the cerebral artery territories ((a): anterior, (b): middle, (c): posterior), ipsilateral and contralateral to the stenosis side for patients, and both hemispheres together for controls. Each box is limited to the first and third quartiles, encompassing 50% of the data points. Smaller boxes mean less variability among measures. The line in the box is the median value. The bars refer to the minimum and maximum values, excluding the outliers (small white circles). Significant statistical differences within groups (* p < 0.05; ** p < 0.01; *** p < 0.001) and among groups (++ p < 0.01; +++ p < 0.001) are shown.
Figure 2. Boxplots showing average resting-state cerebrovascular reactivity (RS-CVR) for the cerebral artery territories ((a): anterior, (b): middle, (c): posterior), ipsilateral and contralateral to the stenosis side for patients, and both hemispheres together for controls. Each box is limited to the first and third quartiles, encompassing 50% of the data points. Smaller boxes mean less variability among measures. The line in the box is the median value. The bars refer to the minimum and maximum values, excluding the outliers (small white circles). Significant statistical differences within groups (* p < 0.05; ** p < 0.01; *** p < 0.001) and among groups (++ p < 0.01; +++ p < 0.001) are shown.
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Figure 3. Time shift (TS) maps for patients (left) and control subjects (right). Maps are in relative units. Patients 1, 2, 5, 7, 9, 10, 13, 14, 17, and 19 had severe (>70%) left carotid artery stenosis (CAS), while the other patients had severe (>70%) right CAS. L = left hemisphere; R = right hemisphere.
Figure 3. Time shift (TS) maps for patients (left) and control subjects (right). Maps are in relative units. Patients 1, 2, 5, 7, 9, 10, 13, 14, 17, and 19 had severe (>70%) left carotid artery stenosis (CAS), while the other patients had severe (>70%) right CAS. L = left hemisphere; R = right hemisphere.
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Figure 4. Boxplots showing average time shift (TS) index for the cerebral artery territories ((a): anterior, (b): middle, (c): posterior), ipsilateral and contralateral to the stenosis side for patients, and both hemispheres together for controls. Each box is limited to the first and third quartiles, encompassing 50% of the data points. Smaller boxes mean less variability among measures. The line in the box is the median value. The bars refer to the minimum and maximum values, excluding the outliers (small white circles). Significant statistical differences within groups (** p < 0.01; *** p < 0.001) and among groups (+ p < 0.05; ++ p < 0.01) are shown.
Figure 4. Boxplots showing average time shift (TS) index for the cerebral artery territories ((a): anterior, (b): middle, (c): posterior), ipsilateral and contralateral to the stenosis side for patients, and both hemispheres together for controls. Each box is limited to the first and third quartiles, encompassing 50% of the data points. Smaller boxes mean less variability among measures. The line in the box is the median value. The bars refer to the minimum and maximum values, excluding the outliers (small white circles). Significant statistical differences within groups (** p < 0.01; *** p < 0.001) and among groups (+ p < 0.05; ++ p < 0.01) are shown.
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Table 1. Patients’ sex, age, and level of vessel obstruction obtained from MR angiography.
Table 1. Patients’ sex, age, and level of vessel obstruction obtained from MR angiography.
IDSexAgeLeft ICAS (%)Right ICAS (%)
p1Male62>70<50
p2Female59>70no
p3Female56no>70
p4Male68no>70
p5Female81>70<30
p6Female8230>70
p7Female68>70no
p8Male6550>70
p9Male77>70<30
p10Male83>70<30
p11Male77no>70
p12Female67>50>70
p13Female67>70no
p14Female65>7050
p15Female71no>70
p16Male61no>70
p17Female52>70no
p18Male70no>75
p19Female53>70no
p20Female53no>70
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MDPI and ACS Style

Secchinato, K.F.; da Silva, P.H.R.; Rodrigues, G.R.; Ferreira, A.P.A.C.; Pontes-Neto, O.M.; Leoni, R.F. Impaired Cerebral Hemodynamics in Asymptomatic Carotid Artery Stenosis Assessed by Resting-State Functional MRI. J. Vasc. Dis. 2025, 4, 15. https://doi.org/10.3390/jvd4020015

AMA Style

Secchinato KF, da Silva PHR, Rodrigues GR, Ferreira APAC, Pontes-Neto OM, Leoni RF. Impaired Cerebral Hemodynamics in Asymptomatic Carotid Artery Stenosis Assessed by Resting-State Functional MRI. Journal of Vascular Diseases. 2025; 4(2):15. https://doi.org/10.3390/jvd4020015

Chicago/Turabian Style

Secchinato, Kaio F., Pedro H. R. da Silva, Guilherme R. Rodrigues, Ana P. A. C. Ferreira, Octavio M. Pontes-Neto, and Renata F. Leoni. 2025. "Impaired Cerebral Hemodynamics in Asymptomatic Carotid Artery Stenosis Assessed by Resting-State Functional MRI" Journal of Vascular Diseases 4, no. 2: 15. https://doi.org/10.3390/jvd4020015

APA Style

Secchinato, K. F., da Silva, P. H. R., Rodrigues, G. R., Ferreira, A. P. A. C., Pontes-Neto, O. M., & Leoni, R. F. (2025). Impaired Cerebral Hemodynamics in Asymptomatic Carotid Artery Stenosis Assessed by Resting-State Functional MRI. Journal of Vascular Diseases, 4(2), 15. https://doi.org/10.3390/jvd4020015

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