Longitudinal Resting-State Functional Magnetic Resonance Imaging Study: A Seed-Based Connectivity Biomarker in Patients with Ischemic and Intracerebral Hemorrhage Stroke

Abstract

Objective:

The primary aim of the research was to compare the impact of postischemic and hemorrhagic stroke on brain connectivity and recovery using resting-state functional magnetic resonance imaging.

Methods and Procedures:

We serially imaged 20 stroke patients, 10 with ischemic stroke (IS) and 10 with intracerebral hemorrhage (ICH), at 1, 3, and 12 months (1M, 3M, and 12M) after ictus. Data from 10 healthy volunteers were obtained from a publically available imaging data set. All functional and structural images underwent standard processing for brain extraction, realignment, serial registration, unwrapping, and denoising using SPM12. A seed-based group analysis using CONN software was used to evaluate the default mode network and the sensorimotor network connections by applying bivariate correlation and hemodynamic response function weighting.

Results:

In comparison with healthy controls, both IS and ICH exhibited disrupted interactions (decreased connectivity) between these two networks at 1M. Interactions then increased by 12M in each group. Temporally, each group exhibited a minimal increase in connectivity at 3M compared with 12M. Overall, the ICH patients exhibited a greater magnitude of connectivity disruption compared with IS patients, despite a significant intrasubject reduction in hematoma volume. We did not observe any significant correlation between change in connectivity and recovery as measured on the National Institutes of Health Stroke Scale (NIHSS) at any time point.

Conclusions:

These findings demonstrate that the largest changes in functional connectivity occur earlier (3M) rather than later (12M) and show subtle differences between IS and ICH during recovery and should be explored further in larger samples.

Impact statement

The primary aim of the serial neuroimaging study was to compare the impact of postischemic and hemorrhagic stroke on brain connectivity and recovery using resting-state functional magnetic resonance imaging. A seed-based connectivity analysis was applied to evaluate the interaction between the default mode network and the sensorimotor network using bivariate correlation and hemodynamic response function weighting. Overall, the intracerebral hemorrhage patients exhibited a greater magnitude of connectivity disruption compared with ischemic stroke patients, despite a significant intrasubject reduction in hematoma volume.

Introduction

Stroke is the number one cause of disability, with about 600,000 newly reported stroke cases in the United States annually. About 87% of all strokes are ischemic and 13% are hemorrhagic (Benjamin et al, 2019; Virani et al, 2020). Despite significant differences in pathophysiology between ischemic and hemorrhagic stroke, severe to mild disabilities develop in most survivors. Patients with intracerebral hemorrhage (ICH) have a higher risk of fatality and about half of them die within the first month (Pinho et al, 2019). ICH not only causes tissue damage but also leads to secondary injuries such as cellular toxicity, expansion of cytotoxic and vasogenic edema causing an increase in intracranial pressure, tissue compression, and impaired coagulation.

Conceptually, it is believed that ICH survivors past the acute stage have better neurological and functional prognoses than patients with ischemic stroke (IS) (Chae et al, 1996; Paolucci et al, 2003), but the literature is contradictory (Perna and Temple, 2015). There are several key prognostic factors such as stroke severity, age, lesion volume, location, presence of a mass effect, and midline shift that are relevant to functional outcome (Alawieh et al, 2018).

Recently, several task-based and resting-state functional magnetic resonance imaging (rs-fMRI) studies have been applied to evaluate poststroke recovery (Arya et al, 2015; Hallam et al, 2018; Jing et al, 2020; Rehme et al, 2011a, 2011b). fMRI relies on the magnetic properties of oxyhemoglobin and deoxyhemoglobin to detect localized changes in blood flow caused by neuronal activity. The fMRI signal is known as the blood-oxygen-level-dependent (BOLD) response, which can be localized and quantified (Ogawa et al, 1990). Since most stroke survivors cannot follow the commands or perform a task during imaging, rs-fMRI, which evaluates neuronal connectivity at rest, has emerged as a method of choice.

A wide variety of neurological disorders have been investigated with rs-fMRI as a noninvasive tool to track the progression or regression of neurological diseases (Dennis and Thompson, 2014; Guerra-Carrillo et al, 2014; Polosecki et al, 2020; Sidhu et al, 2018). Previous connectivity studies on stroke survivors have revealed that the effects of damage can extend beyond the area of the stroke lesion (Grefkes and Fink, 2011; Grefkes and Ward, 2014).

The default mode network (DMN) and sensorimotor network (SMN) of the brain have emerged as the two most reliable networks for assessing connectivity during stroke recovery (Chen et al, 2019; Huang et al, 2015; Tuladhar et al, 2013; Wu et al, 2020). The DMN is the baseline functional network when a subject is not engaged in a specific task and includes the medial temporal lobe, medial prefrontal cortex, posterior cingulate cortex, ventral precuneus, and parietal cortex regions (Mak et al, 2017; Otti et al, 2015). The DMN disengages with other networks during a goal-oriented task and reflects as negatively correlated with various resting-state networks. The SMN includes the primary motor (precentral gyrus), supplementary motor, and somatosensory (postcentral gyrus) regions.

Slight engagement of motor functions such as twitches and shuffling can briefly disengage the connectivity between the DMN and SMN (Wu et al, 2020). The DMN and SMN negatively interact such that the activation of one is mirrored by the inactivation of the other (Huang et al, 2015).

Motor impairment is one of the most common complications reported in stroke survivors (Carey et al, 2011; Dhand et al, 2019). The SMN plays a significant role in poststroke paresis, aphasia, dysphagia, and dysarthria in both types of stroke. In addition, the SMN closely interacts with the basal ganglia motor circuitry, which is a predominant location for ICH. Previously, Tuladhar et al (2013) demonstrated a significant reduction in DMN connectivity in patients with first-ever IS. However, the underlying mechanisms of recovery remain not well understood. Various fMRI studies have shown the complexity of the process involved in motor function recovery (Golestani et al, 2013; Wang et al, 2010; Xu et al, 2014).

Several cross-sectional studies reported altered connectivity in brain networks after stroke, but only a handful of serial studies reported long-term temporal changes (Golestani et al, 2013; Hu et al, 2018; Ovadia-Caro et al, 2013; Park et al, 2011; Tombari et al, 2004) and few have compared the temporal changes between ischemic and hemorrhagic stroke. In this longitudinal study, we compared the impact of IS and ICH on brain connectivity and their temporal changes over time using rs-fMRI.

Methods and Procedures

Patient enrollment and human protection

A total of 20 patients with ICH and IS, 10 each, were admitted between 2012 and 2020 to the Memorial Hermann Hospital and participated in a longitudinal imaging study. The images from 10 healthy volunteers were downloaded from a public domain imaging database. The study was approved by the Institutional Review Board of the University of Texas Health Sciences Center at Houston and by the Memorial Hermann Hospital Office of Research. Written informed consent was obtained after a thorough discussion with patients and family members. The inclusion–exclusion criteria included all patients diagnosed with IS or ICH age 18–80 years, hematoma volume or ischemic size <100cc, and National Institutes of Health Stroke Scale (NIHSS) 0–20. Patients with a brain tumor, claustrophobia, or metal implantation were excluded.

Neurological and radiological assessments

All participants underwent baseline and serial assessment of neurological deficits using the NIHSS. The neurological assessments were correlated with the change in neuronal connectivity between DMN and SMN. Baseline images (computed tomography/MRI) were obtained within 6–24 h of onset as part of the standard-of-care protocols. Follow-up imaging was obtained at 1, 3, and 12 months (1M, 3M, and 12M) of ictus. The radiological assessments included lesion size, location, serial changes in hematoma, and edema volume.

Image acquisition

Serial images were obtained on a full-body 3.0T Philips Intera later upgraded to the Ingenia (Philips Medical Systems, Best, Netherland) system. Anatomical imaging included 3D T1-weighted (TR/TE = 8.11/3.74 ms, imaging matrix = 256 × 256 × 180 mm, slice thickness = 1 mm) and 3D fluid-attenuated inversion recovery (FLAIR, TR/TE = 4800/129 ms, imaging matrix = 256 × 256 × 180 mm, slice thickness = 1 mm). Resting-state BOLD functional MRIs (rs-fMRI) (TR/TE = 2000/30 ms, FA = 80, dynamics = 120, voxel size = 2.75 × 2.75 × 3 mm³) were obtained using echo planner imaging.

The healthy control images were also obtained on a Philips 3T MRI scanner. The T1 images (TR/TE = 100/9.99 ms, imaging matrix = 256 × 256 × 180 mm³, slice thickness = 1 mm) and fMRI images (TR/TE = 2000/30 ms, flip angle = 75, dynamics = 210, voxel size = 3 × 3 × 3 mm³). We adjusted the number of dynamic images to match our study cohort.

Lesion volume measurements

A semiautomated seed growing algorithm in Analyze 12.0 (Analyze Direct, Inc., KS) was used to measure hematoma and infarct volume on FLAIR images by a single rater. The rater selected a seed point within the infarct and a region-growing algorithm automatically expanded the seed points within the 3D space of the image. Manual editing was implemented when automated segmentation was not possible due to incongruent infarcts or if there were unclear lines of shape distinction with voxel intensities. For illustration purposes, all hematoma and infarct volumes were registered to the Montreal Neurological Institute (MNI) brain template.

Resting-state fMRI

All patient lesions were aligned to the left hemisphere by flipping laterality and labeled as ipsilesional (or ipsi), whereas the right hemisphere as contralesional. The connectivity analysis was performed using the CONN toolbox version 20b. All rs-fMRI images were aligned and unwarped using SPM 12. The subject motion was corrected after slice-time correction, in which the data were time-shifted and resampled through sinc-interpolation to match the midpoint time of each acquisition. All scans were then coregistered to the first scan of each session using b-spline interpolation and centered to the (0,0,0) coordinates in all sessions. Potential outliers were identified as changes above five standard deviations or a frame-wise displacement above 0.9 mm (Esteban et al, 2019; Parker and Razlighi, 2019; Power et al, 2014).

All functional and structural data files are normalized into standard MNI space and undergo gray matter, white matter, and cerebrospinal fluid (CSF) tissue segmentation. Brain volumes were extracted from the surrounding cranium as part of the segmentation and normalization process. Finally, the functional data undergo data smoothing through spatial convolution with an 8 mm Gaussian kernel. Potential confounding effects to the BOLD signal in the white matter, CSF, realignment, scrubbing, and session effects were estimated and removed separately for each voxel in each functional data file using ordinary least-squares regression. All BOLD signal time series were projected to the subspace orthogonal to all potential confounding effects.

Connectivity analysis

Connectivity was evaluated using region-of-interest (ROI)-to-ROI group analysis by applying bivariate correlation and hemodynamic response function weighting. The analysis utilizes ROIs constituting the DMN and the SMN as these two networks have previously been reported in stroke patients (Chen et al, 2019; Wu et al, 2020). The ROIs were taken from the Harvard–Oxford and automated anatomical labeling atlases integrated within CONN functional connectivity toolbox (Frazier et al, 2005; Rolls et al, 2020).

The connectivity analysis was performed in two separate groups. The first group compared IS patients and healthy control and the second group compared ICH patients with the healthy control. No direct comparison between IS and ICH was done due to lesion size and location variation. We also reported changes in individual patient's interconnectivity over time in each group. The average connectivity was analyzed to determine whether it differed from zero levels of the control group, with the p-values signifying the false discovery rate (p-FDR). A linear regression analysis was used to establish an association between the change in connectivity and NIHSS scores.

Results

Demographics and clinical information

Imaging data from a total of 20 stroke patients and 10 healthy volunteers (70 scans) were used in this analysis. Each ischemic (4 male/6 female) and hemorrhagic (6 male/4 female) stroke group consisted of 10 participants with an average age of 55.9 ± 10.8 (range 35–75) and 55.3 ± 17.6 (range 29–78) years, respectively. Ten healthy volunteers (7 male/3 female) with an average age of 35.0 ± 12.1 (range 25–61) years were used as control at all the three time points. The median NIHSS of the ischemic group was significantly (p < 0.05) decreased from 5 (interquartile range [IQR] 3, 7) to 1 (IQR 0, 2) over 1 year. The median NIHSS of the ICH group was also significantly decreased (p < 0.001) from 4 (IQR 2, 11) to 1 (IQR 0, 2) over 12M. Only one ICH patient underwent hemicraniectomy.

Table 1 summarizes individual participant demographic data, overall lesion volume and hematoma volume at 1M, NIHSS (NIHSS) at 1M, lesion/hemorrhage location, and lesion laterality.

Table 1.

Demographics of Sample Groups

	ID	Age	Gender	NIHSS	1M lesion volume, mm³	Lesion location
Ischemic	1	35	F	7	43.60	Left mesial temporal, occipital, posterior left thalamus
	2	59	F	3	0.38	Pontine
	3	62	F	2	6.64	Right occipital, right PCA
	4	53	F	7	3.38	Left external capsule
	5	46	M	3	6.93	Left putamen
	6	59	F	11	80.20	Right posterior temporal lobe
	7	57	M	5	0.55	Left aspect of the medulla
	8	61	M	6	3.95	Left, FL, PL, pre/postcentral gyri
	9	76	M	5	16.79	Left occipital lobe
	10	51	F	8	9.68	Right caudate, external capsule
Hemorrhagic	1	69	M	0	49.90	Left parietal, temporal lobe
	2	64	M	4	7.85	Left lentiform nucleus, ischemic insult right pontine
	3	67	F	13	7.42	Left thalamus, PLIC, centrum semiovale
	4	54	M	3	13.98	Right ventral thalamus
	5	52	M	4	24.03	Left, FL, PL, pre/postcentral gyri
	6	33	M	14	68.24	Left posterior limb of internal capsule extending superiorly and involving the left corona radiata
	7	35	M	15	112.39	Left posterior temporal lobe and anterior parietal lobe
	8	29	F	2	99.38	Left occipital lobe
	9	72	F	2	5.58	Right basal ganglia
	10	78	F	6	10.50	Left temporal-occipital lobe

FL, frontal lobe; M, months; PCA, posterior cerebral artery; PL, parietal lobe; PLIC, posterior limb of internal capsule.

Rehabilitation

All patients underwent in-patient rehabilitation for 60–90 min for 5 days per week during their stay, with an average hospitalization period ranging 5–23 days. Only five patients with ischemic and four with hemorrhagic stroke had out-patient therapy for 2–3 days per week for 60 min per session. All patients underwent physical therapy that included treadmill, constrain-induced therapy, and upper and lower extremity exercises. During in-patient, all patients also received language and speech therapy of various durations. Only three ischemic and four hemorrhagic stroke patients had occupational therapy.

Lesion volume

There was no statistically significant difference between the hematoma and ischemic lesion volume (p = 0.13 at 1M) between the two groups at all three time points. The average lesion volume of the ischemic group decreased from 17.2 ± 25.5 to 8.8 ± 11.2 mL (p = 0.11) over 1 year, whereas in the ICH group, the hematoma volume decreased from 39.9 ± 40.7 to 5.1 ± 7.9 mL (p < 0.01) over the same period. Figure 1 illustrates the average lesion size measured at 1M of onset, with all lesions flipped to the left hemisphere (ipsilesional).

FIG. 1.

Average lesion volume mask in the ischemic and hemorrhagic stroke patients. The color bar represents variation in lesion signal intensities.

Connectivity

The changes in connectivity between the DMN and SMN either within or between network ROIs are summarized in Figure 2. The connectivity correlations are color-coded, where warm colors represent positively correlated connections, while cool colors represent negatively correlated connections. The healthy control group showed significant connectivity between the DMN and SMN (Fig. 2A), whereas at 1M, both IS and ICH patients displayed no interaction between the two networks (Fig. 2B, E). However, at 3M, both IS and ICH patients exhibited a significant (p-FDR >0.01) interaction, through which the IS group showed an increase among all three regions of the SMN to the ipsilesional and contralesional parietal regions of the DMN (Fig. 2C), while ICH patients only displayed an increase in connectivity between the lateral contralesional region of the SMN to the posterior cingulate cortex and ipsilesional parietal regions of the DMN (Fig. 2F).

FIG. 2.

Summary of changes in the connectivity between DMN and SMN at 1M, 3M, and 12M in ischemic and hemorrhagic stroke patients. The color bar represents the magnitude of t-statistics between the seed and ROI illustrated by the range of positive (warm color) and negative (cool color) correlation changes between the two networks over time. The first row (A) illustrates the interconnectivity between DMN and SMN in healthy volunteers at one time point, whereas rows 2 (B–D) and 3 (E–G) are displaying temporal change in connectivity between the DMN and SMN in the ischemic and hemorrhagic stroke patients, respectively. Bottom row (H–J) illustrating change in connectivity between IS and ICH patients over time. When compared with healthy controls, both ischemic and hemorrhagic stroke patients showed a significant (p-FDR <0.05) increase in correlation between these two networks over 1 year. DMN-LPR, default mode network lateral parietal right; DMN, default mode network; DMN-LPL, default mode network lateral parietal left; DMN-MPC, default mode network medial prefrontal cortex; DMN-PCC, default mode network posterior cingulate cortex; FDR, false discovery rate; ICH, intracerebral hemorrhage; IS, ischemic stroke; M, month; ROI, region of interest; SMN, sensorimotor network; SMN-LL, sensorimotor network lateral left; SMN-LR, sensorimotor network lateral right; SMN-S, sensorimotor network superior.

After 1 year, the IS group exhibited increased correlations in connectivity between the posterior cingulate cortex and ipsilesional lateral motor cortex of the DMN, between the SMN contralesional cortex to the DMN ipsilesional and contralesional parietal lobe, and between the SMN superior motor cortex to the DMN posterior cingulate cortex (Fig. 2D). In comparison, the ICH patients at 12M exhibited increased interconnectivity between the superior SMN to ipsilesional and contralesional lateral parietal regions of DMN, the medial prefrontal cortex of DMN to ipsilesional and contralesional lateral SMN, and lastly, the posterior cingulate cortex of DMN to lateral contralesional of SMN (Fig. 2G). Serial differences between the two patient groups revealed a significant difference in connectivity at 3M, with the IS group showing significantly greater correlations in connectivity between the ipsilesional and contralesional lateral SMN (Fig. 2I).

No significant differences were observed between the two patient groups at the 1M and 12M time points (Fig. 2H, J). The localized qualitative changes in the connectivity between DMN and SMN over time are displayed by brain surface mapping, as shown in Figure 3. Compared with 1M where each group exhibited no connectivity between DMN and SMN, at 12M, both IS and ICH patients showed an increase in connectivity between the DMN and SMN. The quantitative changes in connectivity between these two networks in each group are summarized in Table 2.

FIG. 3.

A surface plot of the lateral and medial view of the left (ipsilesional) hemisphere in ischemic and hemorrhagic stroke patients at 1M, 3M, and 12M. Colored areas represent regions of significant connectivity seeded from the DMN parietal region of the right (contralesional) hemisphere. The color bar scale represents the positive and negative correlation z-scores. Compared with 1M, the negative correlation between the DMN and SMN was significantly (p-FDR <0.05) increased in both the ischemic and hemorrhagic stroke patients at 12M.

Table 2.

Significant Connectivity Clusters Among Ischemic and Hemorrhagic Stroke Patients (Computed at the Zero Level of a Healthy Control Group)

	Ischemic patients		Hemorrhagic patients
	F-Statistic	p-FDR	F-Statistic	p-FDR
1M
SMN	29.79	0.000008	14.21	0.000354
DMN	25.95	0.000010	22.95	0.000044
3M
SMN	103.08	0.000000	27.38	0.000011
DMN	22.05	0.000028	25.52	0.000011
Interconnectivity	5.06	0.018832	5.88	0.011429
12M
SMN	129.62	0.000000	34.07	0.000003
DMN	27.88	0.000006	19.34	0.000063
Interconnectivity	12.63	0.000435	6.50	0.008014

DMN, default mode network; FDR, false discovery rate; SMN, sensorimotor network.

The average connectivity z-score change in individual ischemic and ICH patients over time is shown in Figure 4A and B, respectively. Most of the patients in both IS and ICH exhibited a slight increase in z-scores between 1M and 3M, except for one IS and one ICH patient. However, the interconnectivity changes between 3M and 12M varied among individual participants. The overall average connectivity z-scores of three regions of the SMN in the IS group were higher than ICH patients at 1M (red), which slightly decreased between 1M and 3M and then stabilized between 3M and 12M, as shown in Figure 4C and D. Whereas ICH patients showed no change in average connectivity z-scores among the SMN regions. There was no significant temporal change exhibited by either IS or ICH patients in the average connectivity z-scores of the five DMN regions (blue).

FIG. 4.

Changes in average connectivity z-scores in three regions of SMN, five regions of DMN, and interconnectivity in individual patients and overall at 1M, 3M, and 12M of both ischemic and hemorrhagic stroke patients. The change in individual patients' interconnectivity varies in both IS and ICH groups as shown in (A, B), respectively. Overall, the IS patients (C) had a higher (p < 0.05) average connectivity z-score in the SMN compared with the ICH (D) patients at 1M, but decreased at 3M and then stabilized. The changes in average connectivity z-scores in five regions of DMN remain unchanged in both the IS and ICH patients. The interconnectivity between SMN and DMN increased in both the IS and ICH patients. *Significant difference (p < 0.05) between time points. Interconnectivity, connectivity between DMN and SMN ROIs; NIHSS, National Institutes of Health Stroke Scale.

However, compared with 1M, both IS and ICH patients showed a significant increase in interconnectivity between the DMN and SMN at 3 and 12M. There was no significant correlation (IS, R = 0.23, p = 0.31; R = 0.14, p = 0.55) between the change in interconnectivity and clinical outcome as measured on the NIHSS.

Discussion and Conclusions

In this longitudinal neuroimaging study, we compared poststroke changes in neuronal connectivity in patients with ischemic versus hemorrhagic stroke. Several cross-sectional and serial connectivity imaging studies have been reported in patients with IS (Dhand et al, 2019; Grefkes and Fink, 2011; Grefkes and Ward, 2014; Rehme et al, 2011b; Tuladhar et al, 2013). However, to the best of our knowledge, this is the first longitudinal imaging study that evaluated DMN and SMN connectivity in both hemorrhagic and IS patients. Our results showed that regardless of stroke type, every patient exhibited not only significant disruption in connectivity between the DMN and SMN but also a global reduction among several brain networks.

Compared with healthy controls, both ischemic and hemorrhagic stroke patients did not have the expected negative correlations between the DMN and SMN at 1M. Furthermore, the decrease in connectivity in the positively correlated regions in the SMN and DMN was different between the two stroke types. For example, connectivity strength in the superior, ipsilesional, and contralesional lateral SMN attenuated in the hemorrhagic patients, whereas it increased in IS patients when compared with the healthy controls at 1M, as shown in Figure 2. Compared with healthy controls, both IS and ICH patients exhibited a reduction in connectivity in most of the DMN regions at 1M.

However, when comparing the two types of strokes, the ischemic patients had no connectivity between the medial prefrontal cortex and ipsilesional lateral parietal regions of the DMN. The connectivity between the medial prefrontal cortex and posterior cingulate cortex was not affected in hemorrhage patients, but it decreased in ischemic patients. Connectivity between the ipsilesional and contralesional parietal regions was unaffected in the IS patients, but it decreased in hemorrhagic stroke. Our findings are in line with several poststroke connectivity studies that reported acute decline or disruption in global connectivity regardless of ischemic or hemorrhagic stroke severity.

However, Liu et al (2020) reported that this disruption in connectivity varies with ischemic lesion location (Bonkhoff et al, 2020; Lipson et al, 2005; Tuladhar et al, 2013). In addition to lesion location, we are suspecting Wallerian degeneration (remote brain injury from a lesion), a well-documented phenomenon observed in both ischemic and hemorrhagic stroke patients that could be one of the contributing factors for connectivity differences.

The variance in interconnectivity change in individual participants substantiates the role of lesion size and location as shown in one of the IS patients (P06) with the biggest lesion volume who exhibited no improvement in interconnectivity over time. Another IS patient (P02) with the smallest pontine lesion showed a significant improvement in interconnectivity between 1M and 3M and then declined between 3M and 12M. Interestingly, one of the ICH patients (P2), who also developed an ischemic pontine lesion between 1M and 3M showed an opposite interconnectivity change compared with the IS patient (P02). It is difficult to explain or speculate about the reasons for these changes due to pontine lesions. Temporally, both IS and ICH patients displayed an increase in negatively correlated connectivity between the DMN and SMN.

However, this increase varied between the two types of stroke. The IS patients displayed far more interconnectivity between the two networks compared with hemorrhagic patients. The IS patients exhibited strong connectivity between the ipsilesional and contralesional parietal region of the DMN to the ipsilesional lateral sensory motor, which was not observed in hemorrhagic stroke patients at 12M. The hemorrhagic patents also lacked a connection between the contralesional parietal and contralesional sensory motor cortex. Interestingly, compared with IS patients, despite a significant reduction in hematoma volume, ICH patients exhibited a lesser magnitude of connectivity at 12M. However, our results are in contrast with a previous serial study that reported a significant increase in interhemispheric connectivity in hemorrhagic stroke compared with IS over 6M (Lee et al, 2018). These differences could be due to lesion size, location, or different seed regions.

A prior study investigated connectivity between the interior frontal cortex and motor-related regions, whereas we investigated changes between the SMN and DMN. Several previous studies have reported a greater functional impairment and poorer recovery in patients with hemorrhagic stroke (Wang et al, 2010; Wu et al, 2020; Xu et al, 2014). However, this variation in connectivity among studies could be due to several key factors such as age, gender, stroke severity, the inclusion of both hemorrhagic and IS, lesion size, and location. Most of these studies including ours have small sample sizes.

In patients with IS, our results are consistent with a previous longitudinal study that reported an increase in synchronization between the DMN and SMN after rehabilitation (Wu et al, 2020). Overall, the most consistent finding was the significant disruption in both local and global brain network connectivity in the acute phase, which strengthens during poststroke recovery (Bonkhoff et al, 2020; Chen et al, 2019; Grefkes and Ward, 2014; Tuladhar et al, 2013); however, the role of interhemispheric connectivity remains controversial. Our data showed an increase in both inter- and intrahemispheric connectivity, whereas Park et al (2011) reported higher ipsilesional connectivity in the frontal and parietal cortices, while Lee et al (2018) reported no change in intrahemispheric connectivity after stroke (Buetefisch, 2015).

In conclusion, both IS and ICH stroke patients exhibited interconnectivity disruption between the DMN and SMN despite differences in pathology and location between the types of injuries. The restoration of the connectivity between these two networks was more prominent in IS patients. Despite a significant decrease in hematoma volume compared with the infarct lesion volume, ICH patients showed a weaker interaction between the DMN and SMN after 1 year. More detailed clinical assessments will be necessary for future studies to assess the clinical impact of disruption and restoration on interconnectivity between the DMN and SMN.

Footnotes

Acknowledgments

The authors thank Mr. Vipulkumar Patel for imaging protocol setup and help with MRI experiments and Ms. Dorothea Parker for recruitment and consenting patients.

Informed Consent

Written informed consent was obtained after a thorough discussion with patients and family members, and provided them adequate time to go over the study.

Ethical Approval

The study was approved by the Institutional Review Board of the University of Texas Health Sciences Center at Houston and by the Memorial Hermann Hospital Office of Research.

Authors' Contributions

S.B.B.: Data analysis, created figures, plots, and drafted the article.

S.I.S.: Financial support, concept, design, data interpretation, and writing the article.

T.M.E.: Reviewed data analysis, interpretation of the results, and edited the article.

O.D.A.: Radiological assessment and data analysis.

J.A.: Edited and reviewed the article.

S.G.: Provision of study and patient recruitment.

C.S.: Statistical analysis.

M.E.H.: Concept and design, data analysis and interpretation, and writing the article.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

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