Original Paper Received: November 5, 2014 Accepted: February 18, 2015 Published online: March 25, 2015
Cerebrovasc Dis 2015;39:232–241 DOI: 10.1159/000381105
Contralesional Thalamic Surface Atrophy and Functional Disconnection 3 Months after Ischemic Stroke Nawaf Yassi a Charles B. Malpas a, b Bruce C.V. Campbell a Bradford Moffat c Christopher Steward c Mark W. Parsons d Patricia M. Desmond c Geoffrey A. Donnan e Stephen M. Davis a Andrew Bivard a, d
a Departments of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, b Melbourne School of Psychological Sciences, and c Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Vic., d Priority Research Centre for Translational Neuroscience and Mental Health, University of Newcastle and Hunter Medical Research Institute, Newcastle, N.S.W., and e Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Vic., Australia
Abstract Background: Remote structural and functional changes have been previously described after stroke and may have an impact on clinical outcome. We aimed to use multimodal MRI to investigate contralesional subcortical structural and functional changes 3 months after anterior circulation ischemic stroke. Methods: Fifteen patients with acute ischemic stroke had multimodal MRI imaging (including high resolution structural T1-MPRAGE and resting state fMRI) within 1 week of onset and at 1 and 3 months. Seven healthy controls of similar age group were also imaged at a single time point. Contralesional subcortical structural volume was assessed using an automated segmentation algorithm in FMRIB’s Integrated Registration and Segmentation Tool (FIRST). Functional connectivity changes were assessed using the intrinsic connectivity contrast (ICC), which was calculated using the functional connectivity toolbox for correlated and anticorrelated networks (Conn). Results: Contralesional thalamic vol-
© 2015 S. Karger AG, Basel 1015–9770/15/0394–0232$39.50/0 E-Mail [email protected] www.karger.com/ced
ume in the stroke patients was significantly reduced at 3 months compared to baseline (median change –2.1%, interquartile range [IQR] –3.4–0.4, p = 0.047), with the predominant areas demonstrating atrophy geometrically appearing to be the superior and inferior surface. The difference in volume between the contralesional thalamus at baseline (mean 6.41 ml, standard deviation [SD] 0.6 ml) and the mean volume of the 2 thalami in controls (mean 7.22 ml, SD 1.1 ml) was not statistically significant. The degree of longitudinal thalamic atrophy in patients was correlated with baseline stroke severity with more severe strokes being associated with a greater degree of atrophy (Spearman’s rho –0.54, p = 0.037). There was no significant difference between baseline contralesional thalamic ICC in patients and control thalamic ICC. However, in patients, there was a significant linear reduction in the mean ICC of the contralesional thalamus over the imaging time points (p = 0.041), indicating reduced connectivity to the remainder of the brain. Conclusions: These findings highlight the importance of remote brain areas, such as the
Subject-Codes: [44] Acute Cerebral Infarction, [58] Computerized tomography and magnetic resonance imaging.
Dr. Nawaf Yassi Department of Neurology The Royal Melbourne Hospital Grattan St., Parkville, VIC 3050 (Australia) E-Mail nawaf.yassi @ mh.org.au
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Key Words Stroke · Ischemic stroke · Magnetic resonance imaging · fMRI · Stroke recovery · Thalamus
© 2015 S. Karger AG, Basel
Introduction
Methods Study Participants In this exploratory pilot study, patients with acute internal carotid territory (predominantly middle cerebral artery) ischemic stroke presenting to The Royal Melbourne Hospital were prospectively recruited. Patients underwent multimodal MRI scanning within one week of stroke onset, and subsequently at one and three months. All patients were managed according to the discretion of the treating stroke physician and based on local guidelines. Clinical data collected included baseline demographics and stroke risk factors, National Institutes of Health Stroke Score (NIHSS) and modified Rankin Scale (mRS) at baseline and 3 months. Seven healthy controls of similar age group underwent imaging at a single time point on the same MRI scanner and with an identical acquisition protocol. The study was approved by the Melbourne Health Research Ethics Committee.
Structural and metabolic brain changes remote from ischemic stroke lesions have long been recognized and may have an impact on clinical recovery [1, 2], as well as implications for potential brain restorative therapies after stroke. The concept of remote metabolic and functional derangement (diaschisis) occurring after cerebral ischemia has been studied predominantly using SPECT, PET, dynamic susceptibility contrast MR perfusion, CT Perfusion, and T2*-weighted imaging during hyperoxia (oxygen challenge imaging) [1, 3–8], whereas global and regional changes in brain volume after stroke have been studied using a variety of MRI-based methods such as voxel-based morphometry [9–12]. Advances in MRI technology and the more widespread availability of such techniques on clinical scanners allows for the potential use of these methods in clinical decision-making or in monitoring response to treatment. However, these approaches have inherent limitations, which may bring into question some conclusions derived from post-stroke functional and volumetric studies. Specifically, it has been suggested that significant technical issues related to focal infarct lesions and surrounding edema can potentially distort volumetric measurements and lead to inaccurate tissue segmentation and conclusions regarding longitudinal volume change [13]. Moreover, the interpretation of perilesional changes observed in fMRI studies in the acute and sub-acute period after stroke can be difficult due to similar issues related to focal lesions, as well as post-stroke vascular reorganization and neurovascular uncoupling and their subsequent effects on the blood oxygenation level-dependent (BOLD) signal [14, 15]. We therefore aimed to investigate longitudinal contralesional subcortical structural changes after ischemic stroke and to validate significant findings using a seed-based functional connectivity analysis. In this pilot study, we chose to investigate changes in the contralesional hemisphere only in order to minimize the confounding effect of the stroke lesion and perilesional edema on the analysis. We hypothesized that changes in volume and shape of contralesional subcortical structures would be detectable and that structures with significant volumetric changes would also demonstrate longitudinal changes in functional connectivity.
Subcortical Structural Segmentation and Vertex Analysis Change in volume of the subcortical structures was measured as percentage change between baseline and 3 months. Subcortical structural segmentation was performed using FMRIB’s Integrated Registration and Segmentation Tool (FIRST) [16] which is part of FMRIB’s Software Library (FSL) [17, 18]. Each individual registration and segmentation result was inspected manually. FIRST is a model-based segmentation and registration tool, which generates automated segmentations of 15 subcortical structures based on manually labeled training data. The manual labels in the training data are parameterized as surface meshes and modeled as a point distribution model. The deformable surfaces are constrained to preserve vertex correspondence across the training data. Furthermore, normalized intensities along the surface normal are sampled and modeled. The shape and appearance model is based on multi-
Contralesional Thalamic Changes Post Stroke
Cerebrovasc Dis 2015;39:232–241 DOI: 10.1159/000381105
Imaging Acquisition All patients and controls underwent 3-Tesla MRI examination on the same Siemens Trio Clinical Scanner (Siemens, Erlangen, Germany), with a Siemens 12-channel phased-array head-coil. Acquired sequences included diffusion-weighted imaging (DWI) (slice thickness 5 mm, 1.2 mm × 1.2 mm voxels, TR 4,200 ms, TE 93 ms, resolution matrix 192 × 192, b = 1,000), T1-weighted axial MPRAGE (slice thickness 1 mm, 0.5 mm × 0.5 mm voxels, TR 1,900 ms, TE 2.82 ms, resolution matrix 256 × 246), T2-weighted axial FLAIR (slice thickness 5 mm, 0.7 mm × 0.7 mm voxels, TR 9,000 ms, TE 92 ms, resolution matrix 320 × 240), and resting state functional MRI (fMRI) with visual fixation (slice thickness, 3.4 mm × 3.4 mm voxels, TR 2,500 ms, TE 30 ms, resolution matrix 64 × 64). All image reconstructions included the manufacturer’s automatic corrections for coil sensitivity profiles to minimize background image nonuniformity. Stroke Lesion Masking In order to measure baseline infarct volume, stroke lesions were manually segmented by a stroke neurologist (NY) using visual assessment of the acute DWI. Segmentations were checked for accuracy by a second stroke neurologist (BC). Prior to running the structural segmentation pipeline, 6 patients with left hemispheric infarcts had their MPRAGE image orientations inverted to normalize infarct hemisphere across the group and allow uniform comparison of the non-infarct hemisphere.
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contralesional thalamus, in stroke recovery. Similar methods have the potential to be used in the prediction of stroke outcome or as imaging biomarkers of stroke recovery.
Functional Connectivity Analysis Functional connectivity changes over time were assessed using the functional connectivity toolbox for correlated and anticorrelated brain networks (Conn; [21]). Prior to processing of functional images, each participant’s MPRAGE volume was segmented into grey-matter, white-matter, and cerebrospinal fluid (CSF) tissue classes in order to generate a whole brain mask, and for use in extracting confounding factors related to physiological noise. Slice timing correction was performed and all volumes were realigned to the first volume using a six-parameter (rigid body) spatial transformation. Realignment transformation matrices and global signal intensities were then analyzed using the Artifact Detection Tool (ART; www.nitrc.org/projects/artifact_detect/) to identify signal and motion outliers. Functional volumes were subsequently coregistered to the MPRAGE volumes, and were then smoothed with an 8 mm full-width, half-maximum kernel. Temporal confounding factors, such as cardiac, respiratory, and other physiological noise, were removed using the aComp Cor method [22]. This approach removes such noise by identifying significant principal components derived from regions of interest that are unlikely to contain any signal modulated by neural activity (in this case, white-matter and CSF regions). Motion parameters and outliers were also removed at this stage. Finally, the residual time series were band pass filtered (0.008–0.09 Hz). Voxel-to-voxel connectivity was calculated in the form of the intrinsic connectivity contrast (ICC) metric, which measures the absolute strength of the global connectivity pattern between each voxel and the rest of the brain [23]. The ICC value for each voxel was normalized by transforming to Z-scores. We specifically targeted the mean ICC within a region of interest corresponding to the contralesional thalamus in native subject space as an indicator of the connectivity between this structure and the rest of the brain. Thalamic ICC was extracted using the subject-specific regions of
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Cerebrovasc Dis 2015;39:232–241 DOI: 10.1159/000381105
interest (ROI) derived from the subcortical segmentation described earlier. As this analysis produces a single metric, correction for multiple comparisons was not required. Other Statistical Analysis General statistical analyses were performed using IBM SPSS Statistics for Macintosh Version 21.0.0.1 (IBM Corp., Armonk, N.Y., USA). The Mann-Whitney U test was used to compare thalamic volume and ICC between controls and patients at baseline. The Wilcoxon signed rank test was used to assess the differences in the volume of subcortical structure between baseline and 3-month in stroke patients. Based on the results of the volumetric analysis, the mean ICC from the contralesional thalamus at each time point was entered into a one-way repeated measures general linear model (GLM) analysis. The distributions of thalamic normalized ICC were checked for normality using the Kolmogorov-Smirnov test prior to analysis. The main effect for time was reported, along with the interaction with infarct hemisphere. Planned linear contrasts were performed for time. Mauchly’s test was used to assess the assumption of sphericity. Effect sizes were calculated as η2 where a small effect = 0.01, medium effect = 0.06, and large effect = 0.14 [24]. Finally, as a post-hoc analysis in order to compare the observed longitudinal functional changes with longitudinal changes in volume, we performed a similar GLM analysis on the volume of the contralesional thalamus over the 3 imaging time points. In all analyses, a p value of 0.05) and sphericity (W(2) = 0.80, p = 0.262) were again not violated, and a linear contrast was statistically significant (F(1,13) = 6.65, p = 0.023, η2 = 0.338). The trend is shown 238
6.34
0 –0.25
–0.27
–0.37
–0.54
Controls
Baseline
1 month
3 months
–1 –2
visually in figure 5. There was no significant interaction with infarct hemisphere (F(2,26) = 0.58, p = 0.568, η2 = 0.043).
Discussion and Conclusions
In this pilot study, we have demonstrated contralesional thalamic atrophy, predominantly localized to the superior and inferior surfaces, 3 months after middle cerebral artery territory ischemic stroke. The degree of atrophy was found to correlate with initial stroke severity, but interestingly not with the baseline DWI volume (within 1 week of onset). This is likely to reflect variations in the timing of the baseline DWI scan, whereas baseline NIHSS more accurately reflected stroke severity at the time of initial medical assessment. We also demonstrated a statistically significant linear reduction over 3 months in functional connectivity between the contralesional thalamus and the rest of the brain after stroke. This pattern was corroborated post-hoc when exploring volume changes over the imaging time-points. Both the connectivity and volumetric changes were of a large effect size and there was no interaction with infarct hemisphere, suggesting that the findings are not purely an artifact of asymmetry in baseline connectivity or volume between hemispheres. These changes may represent longitudinal structural and functional changes occurring during the period of stroke reYassi/Malpas/Campbell/Moffat/Steward/ Parsons/Desmond/Donnan/Davis/Bivard
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ity contrast (ICC) in controls and in the contralateral thalamus in stroke patients showing decline over time (light grey bars). Mean thalamic volume in controls and in the contralateral thalamus in stroke patients also demonstrating decline over time (dark grey bars). Error bars represent 95% confidence interval.
ICC
Thalamic volume (ml)
8
ing the subcortex may allow the investigation of the ipsilesional thalamus more robustly using similar methodology. There were no significant differences in thalamic ICC or thalamic volume between controls and patients at baseline in this study, although there was an obvious trend toward larger thalami in controls compared with patients. While this may reflect a chance finding given the modest sample size of the study, there may also be an association between vascular risk factors (which were not matched between patients and controls) and thalamic volume [37, 38]. This study does have some limitations, most notably the modest sample size. A larger study would not only allow the validation of the present result but may also allow correlation of volumetric and functional measures with clinical endpoints in order to allow the use of these parameters as baseline predictors of outcome or surrogate treatment response markers. However, despite the modest sample size, we have utilized fairly robust and conservative statistical methods, particularly in correcting for multiple comparisons in the vertex analysis, and therefore the probability that these findings are due to chance is low, especially given that contemporaneous changes have been detected using two different modalities. Furthermore, the limited follow-up period of 3 months may have been insufficient to allow changes in other structures to be detected. A study with additional imaging at a later time point (e.g., 12 months later) may therefore allow the detection of more subtle or gradual changes as well as changes in other areas which may not be readily apparent at the 3-month time point. In addition, although thalamic shape changes were localized to the superior and inferior surfaces, the spatial resolution of this study is insufficient to arrive at more concrete conclusions regarding the specific thalamic nuclei most affected, whereas a study at higher field (e.g., 7T) may allow this to be further explored. It is worth noting that the model used in the automated segmentation process in FIRST relies on the MNI standard brain, which has been derived in healthy young subjects, and therefore, the process may be prone to errors in registration and segmentation when older patients with diseased brains are studied. However, the results were systematically visually inspected and there were no cases of obvious misregistration or erroneous segmentation. Finally, the functional connectivity changes reported in post-stroke fMRI studies usually assume limited confounding effects from altered neurovascular reactivity and coupling. Unfortunately, we did not collect routine perfusion imaging in order to assess whether this was a valid assumption in our study, although no patients had
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Cerebrovasc Dis 2015;39:232–241 DOI: 10.1159/000381105
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covery, which may potentially have some impact on clinical outcome, although our study was not powered to detect these clinical changes. In particular, the observed functional connectivity disruption may represent diaschisis, the phenomenon of functional impairment remote from a site of focal neuronal injury [1, 25], which after stroke, has been classically described in the contralateral cerebellum as crossed cerebellar diaschisis [1, 3–8]. Interestingly, reduced ipsilateral and contralateral cortical metabolic rate on PET has also been described after thalamic stroke, hemorrhage, or surgical thalamotomy [26]. Conversely, hypometabolism and hypoperfusion have been demonstrated in the ipsilateral thalamus after cortical infarction in both animal models and in humans [27–29]. A study of 7 patients also identified networks involved in motor recovery after ischemic stroke using principal component analysis of regional cerebral blood flow derived from PET, and noted the involvement of the contralateral thalamus in these networks [30] suggesting that changes in such areas may have an impact on clinical outcome. There is also evidence that task-related (touch discrimination paradigm) activation fMRI in the contralesinal thalamus demonstrates negative correlation with the clinical degree of touch discrimination after stroke [31]. Similarly, thalamic atrophy in the stroke hemisphere has previously been described longitudinally in both animal models and in humans [2, 32]. However, to our knowledge, the present study is the first to concurrently demonstrate reduced contralesional thalamic connectivity and atrophy after stroke. The thalamus is a central hub in multiple neuronal functional networks spanning both hemispheres [33, 34]. It therefore stands to reason that it would be a site of structural and functional change after stroke, even when the inciting lesion is in a remote location in the contralateral hemisphere (so called transcallosal or transhemispheric diaschisis) [35]. The notion of stroke lesions inciting changes in the contralateral hemisphere is further supported by diffusion tensor imaging studies demonstrating callosal degeneration after stroke [36]. Although other studies have demonstrated changes in the ipsilesional thalamus, the systematic assessment of longitudinal changes in volume and functional connectivity in the stroke hemisphere, particularly in the early stages, is likely to be confounded by the highly dynamic stroke lesion and peri-infarct edema as well as issues related to abnormal vascular reactivity and neurovascular uncoupling. Therefore, we opted to investigate only the contralesional changes in this study. A future study focusing on stroke lesions confined only to the cortex and not involv-
any significant flow-limiting stenoses in the contralesional hemisphere. Despite these limitations, the present study has identified significant contralesional thalamic atrophy in the first 3 months after anterior circulation stroke. Furthermore, this finding was underscored by the observation of functional disconnection between the contralesional thalamus and the rest of brain. These results highlight the importance of the thalamus as a central hub in multiple brain functional networks, and also reflect the complexity of stroke recovery and the likely contribution of remote brain areas to the recovery process. Correlation of these findings with clinical endpoints would raise the possibility of a novel surrogate marker of stroke recovery as well a target for potential neuroprotective treatments
focused on the attenuation or prevention of longitudinal maladaptive changes in remote brain areas, such as the contralesional thalamus, after stroke.
Funding N.Y. is supported by University of Melbourne, Neurosciences Victoria, and the Royal Melbourne Hospital Neurosciences Foundation. The study was also funded by the National Stroke Foundation, Australia.
Disclosure Statement None declared.
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Cerebrovasc Dis 2015;39:232–241 DOI: 10.1159/000381105
Contralesional Thalamic Surface Atrophy and Functional Disconnection 3 Months after Ischemic Stroke Nawaf Yassi a Charles B. Malpas a, b Bruce C.V. Campbell a Bradford Moffat c Christopher Steward c Mark W. Parsons d Patricia M. Desmond c Geoffrey A. Donnan e Stephen M. Davis a Andrew Bivard a, d
a Departments of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, b Melbourne School of Psychological Sciences, and c Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Vic., d Priority Research Centre for Translational Neuroscience and Mental Health, University of Newcastle and Hunter Medical Research Institute, Newcastle, N.S.W., and e Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Vic., Australia
Abstract Background: Remote structural and functional changes have been previously described after stroke and may have an impact on clinical outcome. We aimed to use multimodal MRI to investigate contralesional subcortical structural and functional changes 3 months after anterior circulation ischemic stroke. Methods: Fifteen patients with acute ischemic stroke had multimodal MRI imaging (including high resolution structural T1-MPRAGE and resting state fMRI) within 1 week of onset and at 1 and 3 months. Seven healthy controls of similar age group were also imaged at a single time point. Contralesional subcortical structural volume was assessed using an automated segmentation algorithm in FMRIB’s Integrated Registration and Segmentation Tool (FIRST). Functional connectivity changes were assessed using the intrinsic connectivity contrast (ICC), which was calculated using the functional connectivity toolbox for correlated and anticorrelated networks (Conn). Results: Contralesional thalamic vol-
© 2015 S. Karger AG, Basel 1015–9770/15/0394–0232$39.50/0 E-Mail [email protected] www.karger.com/ced
ume in the stroke patients was significantly reduced at 3 months compared to baseline (median change –2.1%, interquartile range [IQR] –3.4–0.4, p = 0.047), with the predominant areas demonstrating atrophy geometrically appearing to be the superior and inferior surface. The difference in volume between the contralesional thalamus at baseline (mean 6.41 ml, standard deviation [SD] 0.6 ml) and the mean volume of the 2 thalami in controls (mean 7.22 ml, SD 1.1 ml) was not statistically significant. The degree of longitudinal thalamic atrophy in patients was correlated with baseline stroke severity with more severe strokes being associated with a greater degree of atrophy (Spearman’s rho –0.54, p = 0.037). There was no significant difference between baseline contralesional thalamic ICC in patients and control thalamic ICC. However, in patients, there was a significant linear reduction in the mean ICC of the contralesional thalamus over the imaging time points (p = 0.041), indicating reduced connectivity to the remainder of the brain. Conclusions: These findings highlight the importance of remote brain areas, such as the
Subject-Codes: [44] Acute Cerebral Infarction, [58] Computerized tomography and magnetic resonance imaging.
Dr. Nawaf Yassi Department of Neurology The Royal Melbourne Hospital Grattan St., Parkville, VIC 3050 (Australia) E-Mail nawaf.yassi @ mh.org.au
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Key Words Stroke · Ischemic stroke · Magnetic resonance imaging · fMRI · Stroke recovery · Thalamus
© 2015 S. Karger AG, Basel
Introduction
Methods Study Participants In this exploratory pilot study, patients with acute internal carotid territory (predominantly middle cerebral artery) ischemic stroke presenting to The Royal Melbourne Hospital were prospectively recruited. Patients underwent multimodal MRI scanning within one week of stroke onset, and subsequently at one and three months. All patients were managed according to the discretion of the treating stroke physician and based on local guidelines. Clinical data collected included baseline demographics and stroke risk factors, National Institutes of Health Stroke Score (NIHSS) and modified Rankin Scale (mRS) at baseline and 3 months. Seven healthy controls of similar age group underwent imaging at a single time point on the same MRI scanner and with an identical acquisition protocol. The study was approved by the Melbourne Health Research Ethics Committee.
Structural and metabolic brain changes remote from ischemic stroke lesions have long been recognized and may have an impact on clinical recovery [1, 2], as well as implications for potential brain restorative therapies after stroke. The concept of remote metabolic and functional derangement (diaschisis) occurring after cerebral ischemia has been studied predominantly using SPECT, PET, dynamic susceptibility contrast MR perfusion, CT Perfusion, and T2*-weighted imaging during hyperoxia (oxygen challenge imaging) [1, 3–8], whereas global and regional changes in brain volume after stroke have been studied using a variety of MRI-based methods such as voxel-based morphometry [9–12]. Advances in MRI technology and the more widespread availability of such techniques on clinical scanners allows for the potential use of these methods in clinical decision-making or in monitoring response to treatment. However, these approaches have inherent limitations, which may bring into question some conclusions derived from post-stroke functional and volumetric studies. Specifically, it has been suggested that significant technical issues related to focal infarct lesions and surrounding edema can potentially distort volumetric measurements and lead to inaccurate tissue segmentation and conclusions regarding longitudinal volume change [13]. Moreover, the interpretation of perilesional changes observed in fMRI studies in the acute and sub-acute period after stroke can be difficult due to similar issues related to focal lesions, as well as post-stroke vascular reorganization and neurovascular uncoupling and their subsequent effects on the blood oxygenation level-dependent (BOLD) signal [14, 15]. We therefore aimed to investigate longitudinal contralesional subcortical structural changes after ischemic stroke and to validate significant findings using a seed-based functional connectivity analysis. In this pilot study, we chose to investigate changes in the contralesional hemisphere only in order to minimize the confounding effect of the stroke lesion and perilesional edema on the analysis. We hypothesized that changes in volume and shape of contralesional subcortical structures would be detectable and that structures with significant volumetric changes would also demonstrate longitudinal changes in functional connectivity.
Subcortical Structural Segmentation and Vertex Analysis Change in volume of the subcortical structures was measured as percentage change between baseline and 3 months. Subcortical structural segmentation was performed using FMRIB’s Integrated Registration and Segmentation Tool (FIRST) [16] which is part of FMRIB’s Software Library (FSL) [17, 18]. Each individual registration and segmentation result was inspected manually. FIRST is a model-based segmentation and registration tool, which generates automated segmentations of 15 subcortical structures based on manually labeled training data. The manual labels in the training data are parameterized as surface meshes and modeled as a point distribution model. The deformable surfaces are constrained to preserve vertex correspondence across the training data. Furthermore, normalized intensities along the surface normal are sampled and modeled. The shape and appearance model is based on multi-
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Imaging Acquisition All patients and controls underwent 3-Tesla MRI examination on the same Siemens Trio Clinical Scanner (Siemens, Erlangen, Germany), with a Siemens 12-channel phased-array head-coil. Acquired sequences included diffusion-weighted imaging (DWI) (slice thickness 5 mm, 1.2 mm × 1.2 mm voxels, TR 4,200 ms, TE 93 ms, resolution matrix 192 × 192, b = 1,000), T1-weighted axial MPRAGE (slice thickness 1 mm, 0.5 mm × 0.5 mm voxels, TR 1,900 ms, TE 2.82 ms, resolution matrix 256 × 246), T2-weighted axial FLAIR (slice thickness 5 mm, 0.7 mm × 0.7 mm voxels, TR 9,000 ms, TE 92 ms, resolution matrix 320 × 240), and resting state functional MRI (fMRI) with visual fixation (slice thickness, 3.4 mm × 3.4 mm voxels, TR 2,500 ms, TE 30 ms, resolution matrix 64 × 64). All image reconstructions included the manufacturer’s automatic corrections for coil sensitivity profiles to minimize background image nonuniformity. Stroke Lesion Masking In order to measure baseline infarct volume, stroke lesions were manually segmented by a stroke neurologist (NY) using visual assessment of the acute DWI. Segmentations were checked for accuracy by a second stroke neurologist (BC). Prior to running the structural segmentation pipeline, 6 patients with left hemispheric infarcts had their MPRAGE image orientations inverted to normalize infarct hemisphere across the group and allow uniform comparison of the non-infarct hemisphere.
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contralesional thalamus, in stroke recovery. Similar methods have the potential to be used in the prediction of stroke outcome or as imaging biomarkers of stroke recovery.
Functional Connectivity Analysis Functional connectivity changes over time were assessed using the functional connectivity toolbox for correlated and anticorrelated brain networks (Conn; [21]). Prior to processing of functional images, each participant’s MPRAGE volume was segmented into grey-matter, white-matter, and cerebrospinal fluid (CSF) tissue classes in order to generate a whole brain mask, and for use in extracting confounding factors related to physiological noise. Slice timing correction was performed and all volumes were realigned to the first volume using a six-parameter (rigid body) spatial transformation. Realignment transformation matrices and global signal intensities were then analyzed using the Artifact Detection Tool (ART; www.nitrc.org/projects/artifact_detect/) to identify signal and motion outliers. Functional volumes were subsequently coregistered to the MPRAGE volumes, and were then smoothed with an 8 mm full-width, half-maximum kernel. Temporal confounding factors, such as cardiac, respiratory, and other physiological noise, were removed using the aComp Cor method [22]. This approach removes such noise by identifying significant principal components derived from regions of interest that are unlikely to contain any signal modulated by neural activity (in this case, white-matter and CSF regions). Motion parameters and outliers were also removed at this stage. Finally, the residual time series were band pass filtered (0.008–0.09 Hz). Voxel-to-voxel connectivity was calculated in the form of the intrinsic connectivity contrast (ICC) metric, which measures the absolute strength of the global connectivity pattern between each voxel and the rest of the brain [23]. The ICC value for each voxel was normalized by transforming to Z-scores. We specifically targeted the mean ICC within a region of interest corresponding to the contralesional thalamus in native subject space as an indicator of the connectivity between this structure and the rest of the brain. Thalamic ICC was extracted using the subject-specific regions of
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interest (ROI) derived from the subcortical segmentation described earlier. As this analysis produces a single metric, correction for multiple comparisons was not required. Other Statistical Analysis General statistical analyses were performed using IBM SPSS Statistics for Macintosh Version 21.0.0.1 (IBM Corp., Armonk, N.Y., USA). The Mann-Whitney U test was used to compare thalamic volume and ICC between controls and patients at baseline. The Wilcoxon signed rank test was used to assess the differences in the volume of subcortical structure between baseline and 3-month in stroke patients. Based on the results of the volumetric analysis, the mean ICC from the contralesional thalamus at each time point was entered into a one-way repeated measures general linear model (GLM) analysis. The distributions of thalamic normalized ICC were checked for normality using the Kolmogorov-Smirnov test prior to analysis. The main effect for time was reported, along with the interaction with infarct hemisphere. Planned linear contrasts were performed for time. Mauchly’s test was used to assess the assumption of sphericity. Effect sizes were calculated as η2 where a small effect = 0.01, medium effect = 0.06, and large effect = 0.14 [24]. Finally, as a post-hoc analysis in order to compare the observed longitudinal functional changes with longitudinal changes in volume, we performed a similar GLM analysis on the volume of the contralesional thalamus over the 3 imaging time points. In all analyses, a p value of 0.05) and sphericity (W(2) = 0.80, p = 0.262) were again not violated, and a linear contrast was statistically significant (F(1,13) = 6.65, p = 0.023, η2 = 0.338). The trend is shown 238
6.34
0 –0.25
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–0.37
–0.54
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visually in figure 5. There was no significant interaction with infarct hemisphere (F(2,26) = 0.58, p = 0.568, η2 = 0.043).
Discussion and Conclusions
In this pilot study, we have demonstrated contralesional thalamic atrophy, predominantly localized to the superior and inferior surfaces, 3 months after middle cerebral artery territory ischemic stroke. The degree of atrophy was found to correlate with initial stroke severity, but interestingly not with the baseline DWI volume (within 1 week of onset). This is likely to reflect variations in the timing of the baseline DWI scan, whereas baseline NIHSS more accurately reflected stroke severity at the time of initial medical assessment. We also demonstrated a statistically significant linear reduction over 3 months in functional connectivity between the contralesional thalamus and the rest of the brain after stroke. This pattern was corroborated post-hoc when exploring volume changes over the imaging time-points. Both the connectivity and volumetric changes were of a large effect size and there was no interaction with infarct hemisphere, suggesting that the findings are not purely an artifact of asymmetry in baseline connectivity or volume between hemispheres. These changes may represent longitudinal structural and functional changes occurring during the period of stroke reYassi/Malpas/Campbell/Moffat/Steward/ Parsons/Desmond/Donnan/Davis/Bivard
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ity contrast (ICC) in controls and in the contralateral thalamus in stroke patients showing decline over time (light grey bars). Mean thalamic volume in controls and in the contralateral thalamus in stroke patients also demonstrating decline over time (dark grey bars). Error bars represent 95% confidence interval.
ICC
Thalamic volume (ml)
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ing the subcortex may allow the investigation of the ipsilesional thalamus more robustly using similar methodology. There were no significant differences in thalamic ICC or thalamic volume between controls and patients at baseline in this study, although there was an obvious trend toward larger thalami in controls compared with patients. While this may reflect a chance finding given the modest sample size of the study, there may also be an association between vascular risk factors (which were not matched between patients and controls) and thalamic volume [37, 38]. This study does have some limitations, most notably the modest sample size. A larger study would not only allow the validation of the present result but may also allow correlation of volumetric and functional measures with clinical endpoints in order to allow the use of these parameters as baseline predictors of outcome or surrogate treatment response markers. However, despite the modest sample size, we have utilized fairly robust and conservative statistical methods, particularly in correcting for multiple comparisons in the vertex analysis, and therefore the probability that these findings are due to chance is low, especially given that contemporaneous changes have been detected using two different modalities. Furthermore, the limited follow-up period of 3 months may have been insufficient to allow changes in other structures to be detected. A study with additional imaging at a later time point (e.g., 12 months later) may therefore allow the detection of more subtle or gradual changes as well as changes in other areas which may not be readily apparent at the 3-month time point. In addition, although thalamic shape changes were localized to the superior and inferior surfaces, the spatial resolution of this study is insufficient to arrive at more concrete conclusions regarding the specific thalamic nuclei most affected, whereas a study at higher field (e.g., 7T) may allow this to be further explored. It is worth noting that the model used in the automated segmentation process in FIRST relies on the MNI standard brain, which has been derived in healthy young subjects, and therefore, the process may be prone to errors in registration and segmentation when older patients with diseased brains are studied. However, the results were systematically visually inspected and there were no cases of obvious misregistration or erroneous segmentation. Finally, the functional connectivity changes reported in post-stroke fMRI studies usually assume limited confounding effects from altered neurovascular reactivity and coupling. Unfortunately, we did not collect routine perfusion imaging in order to assess whether this was a valid assumption in our study, although no patients had
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covery, which may potentially have some impact on clinical outcome, although our study was not powered to detect these clinical changes. In particular, the observed functional connectivity disruption may represent diaschisis, the phenomenon of functional impairment remote from a site of focal neuronal injury [1, 25], which after stroke, has been classically described in the contralateral cerebellum as crossed cerebellar diaschisis [1, 3–8]. Interestingly, reduced ipsilateral and contralateral cortical metabolic rate on PET has also been described after thalamic stroke, hemorrhage, or surgical thalamotomy [26]. Conversely, hypometabolism and hypoperfusion have been demonstrated in the ipsilateral thalamus after cortical infarction in both animal models and in humans [27–29]. A study of 7 patients also identified networks involved in motor recovery after ischemic stroke using principal component analysis of regional cerebral blood flow derived from PET, and noted the involvement of the contralateral thalamus in these networks [30] suggesting that changes in such areas may have an impact on clinical outcome. There is also evidence that task-related (touch discrimination paradigm) activation fMRI in the contralesinal thalamus demonstrates negative correlation with the clinical degree of touch discrimination after stroke [31]. Similarly, thalamic atrophy in the stroke hemisphere has previously been described longitudinally in both animal models and in humans [2, 32]. However, to our knowledge, the present study is the first to concurrently demonstrate reduced contralesional thalamic connectivity and atrophy after stroke. The thalamus is a central hub in multiple neuronal functional networks spanning both hemispheres [33, 34]. It therefore stands to reason that it would be a site of structural and functional change after stroke, even when the inciting lesion is in a remote location in the contralateral hemisphere (so called transcallosal or transhemispheric diaschisis) [35]. The notion of stroke lesions inciting changes in the contralateral hemisphere is further supported by diffusion tensor imaging studies demonstrating callosal degeneration after stroke [36]. Although other studies have demonstrated changes in the ipsilesional thalamus, the systematic assessment of longitudinal changes in volume and functional connectivity in the stroke hemisphere, particularly in the early stages, is likely to be confounded by the highly dynamic stroke lesion and peri-infarct edema as well as issues related to abnormal vascular reactivity and neurovascular uncoupling. Therefore, we opted to investigate only the contralesional changes in this study. A future study focusing on stroke lesions confined only to the cortex and not involv-
any significant flow-limiting stenoses in the contralesional hemisphere. Despite these limitations, the present study has identified significant contralesional thalamic atrophy in the first 3 months after anterior circulation stroke. Furthermore, this finding was underscored by the observation of functional disconnection between the contralesional thalamus and the rest of brain. These results highlight the importance of the thalamus as a central hub in multiple brain functional networks, and also reflect the complexity of stroke recovery and the likely contribution of remote brain areas to the recovery process. Correlation of these findings with clinical endpoints would raise the possibility of a novel surrogate marker of stroke recovery as well a target for potential neuroprotective treatments
focused on the attenuation or prevention of longitudinal maladaptive changes in remote brain areas, such as the contralesional thalamus, after stroke.
Funding N.Y. is supported by University of Melbourne, Neurosciences Victoria, and the Royal Melbourne Hospital Neurosciences Foundation. The study was also funded by the National Stroke Foundation, Australia.
Disclosure Statement None declared.
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