|Home | About | Journals | Submit | Contact Us | Français|
Stroke patients often display deficits in language function such as correctly naming objects. Our aim was to evaluate the reliability and the patterns of post-stroke language recovery using a picture identification task during fMRI at 4T.
4 healthy and 4 left MCA stroke subjects with chronic (>1 year) aphasia. Ten fMRI scans were performed for each subject over a 10-week period using a picture identification task. Active condition involved presenting subjects with a panel of 4 figures (e.g., drawings of 4 animals) every 6 seconds; subjects indicated which figure matched the written name in the center. Control condition was same/different judgment task of pairs of geometric figures (squares, octagons or combination) presented every 6 seconds. Thirty-second active/control blocks were repeated 5 times each; responses were recorded.
Patients and controls exhibited similar demographic characteristics: age (46 vs. 53 years), personal handedness (EHI; 89 vs. 95), familial handedness (93 vs. 95) or years of education (14.3 vs. 14.8). For the active condition, controls performed better than patients (97.7% vs. 89.1%, p<0.001); performance was similar for the control condition (99.5% vs. 98.8%, p=0.23). During fMRI, controls exhibited bilateral, L>R positive blood oxygenation-level dependent (BOLD) activations in frontal and temporal language areas and symmetric retro-splenial and posterior cingulate areas and symmetric negative BOLD activations in bilateral fronto-temporal language networks. However, the patient group showed positive BOLD activations predominantly in peri-stroke areas and negative BOLD activations in the unaffected (right) hemisphere. Both the control and patient groups displayed high activation reliability (as measured by the ICC) in left frontal and temporal language areas, although the ICC in frontal regions of the patients was spread over a much larger peri-stroke area.
This study documents the utility of the picture identification task for post-stroke language recovery evaluation. Study data suggest that adult stroke patients utilize functional peri-stroke areas to perform language functions.
Up to 270,000 new patients with stroke-related aphasia are diagnosed every year (1, 2). Although their aphasia frequently improves during the first few weeks and months after the acute stroke, about half of these patients remain aphasic at the time of discharge (2). The presence of aphasia at the time of acute stroke is suggestive of poor long-term prognosis leading to high mortality and severe motor, social, and cognitive disability (3–7). Spontaneous recovery of aphasia is usually highest during the first 3 months after the stroke (8, 9); however, with therapy late recovery up to several years after stroke has been observed (10–13). Although the initial severity of aphasia is the only known clinically relevant predictor of language outcome after acute stroke (2), some postulate that acute severely aphasic patients, when appropriately treated, may recover their language functions better than moderately aphasic patients (14). Given its prevalence and widely appreciated impact, improved strategies for aphasia evaluation and recovery monitoring are needed.
Functional magnetic resonance imaging (fMRI) has shown promise for post-stroke aphasia recovery evaluation. Several studies have evaluated fMRI patterns of aphasia recovery utilizing various language tasks. (15–20). These studies usually show BOLD signal patterns associated with post-stroke language recovery in the dominant or non-dominant hemispheres. In a recent study, inter-scan variability measures for fMRI activation patterns were reported in response to verb generation and semantic decision/tone decision tasks (15). In that study, group composite and intraclass correlation coefficient (ICC) maps showed consistently high correlation for individual tasks among both control and aphasic subjects in the left lateral frontal and temporo-parietal regions. These results indicate that both of these tasks consistently and reliably delineate cortical areas involved in language processing in healthy and stroke subjects and support their use in future longitudinal studies of post-stroke language recovery. In the present study we examine the post-stroke aphasia recovery in adult stroke victims using repetitive fMRI at 4T for two purposes: 1) to establish the reliability of a picture identification task not previously used for studying post-stroke aphasia and 2) to evaluate the patterns of language recovery in patients with chronic aphasia with this fMRI task..
After obtaining consent as part of a larger study we enrolled 4 healthy controls and 4 subjects with history of left middle artery stroke (LMCA) and resultant chronic (more than 1 year after the incident stroke) post-stroke aphasia. Demographics and medical histories of all subjects are included in Table 1. This study was approved by the Institutional Review Board at the University of Cincinnati Academic Health Center in Cincinnati, Ohio
All stroke subjects completed their aphasia rehabilitation protocols and were more than 1 year since the incident stroke (Table 1). The extent of the LMCA stroke in the aphasic subjects can be seen in the anatomical images of Figure 1. Over the course of 10 weeks each control subject underwent 5 fMRI sessions during which they performed several language tasks. Here we report only data on the picture identification task; data on other tasks are reported elsewhere (15). Data for this task were also acquired from aphasic subjects over the course of 5 fMRI scanning sessions over 10 weeks, with the exception of one subject who only completed 3 sessions (total of 36 stroke datasets). Subject 3 developed a spontaneous subdural hematoma that was diagnosed at the time of the third scanning session and was subsequently excluded from the study. For each subject, the picture identification task was performed at each fMRI session and repeated twice per session. Prior to first scanning session all subjects received a pure tone hearing screening and a brief language evaluation battery (data not presented here) (15).
The design of the active condition of the picture identification fMRI task was similar to the Peabody Picture Vocabulary Test III (PPVT-III) (21) and to a “picture word matching” task (20, 22) recently used for evaluation of aphasia recovery. The task consisted of alternating 30 second blocks of active and control conditions starting with control condition. Five sets of black and white figures were presented for 6 seconds per set in each 30 second block. Each run of the task began with 5 “dummy” scans in which data was not collected to allow for scanner signal to equilibrate. With the sixth whole brain volume the presentation software was triggered to start the task. During the active condition, subjects were presented with a panel of 4 figures (e.g., drawings of 4 animals) – each figure was located in a different quadrant of the screen with a name of one of the figures (e.g., elephant) placed in the center of the screen. Subjects were asked to indicate which figure matched the name in the center by pressing a corresponding button on an MRI-compatible response pad using a non-dominant (unaffected) hand. During the control condition, the subjects saw drawings of two geometric figures (squares, octagons, or combination) and they were asked to respond by indicating whether the two figures were the same or different by pressing a corresponding button on the response pad using the unaffected (left) hand. This condition was designed to control for working memory, attention, visual processing and motor responses associated with this type of fMRI task. All responses were recorded for further analysis.
Prior to entering the scanner, all subjects learned the fMRI task. Their understanding of the picture identification task was tested by performing a mock run that included 5 sets of 4 figures with descriptor in the middle (active condition) and 5 sets of two geometric figures (control condition); these figures were not used during the testing condition. Subjects were allowed to proceed to the scanner only if they responded correctly to all 10 items. This procedure was repeated each time the subjects returned for scanning.
All scans were performed on a 4T Varian Unity INOVA Whole Body MRI/MRS scanner based on a 92.5 cm Oxford 4T actively-shielded superconducting magnet (Oxford Magnet Technology, Oxford, England). For detailed description of the scanning procedures and data collection environment see our recent publications (15, 23, 24). Processing of 3D anatomical and fMRI image data was done using routines written in-house in Interactive Data Language (IDL; ITT Visual Information Solutions, Boulder, CO) programming language and the Cincinnati Children’s Hospital Image Processing Software (CCHIPS©) using methods similar to those used in our previous studies (25–27). Briefly, prior to statistical parameter mapping of activations from the picture identification task, several pre-processing steps were performed including removal of ghosting and geometric distortion artifacts using a multi-echo technique, reduction of truncation artifacts at the edges of k-space via Hamming-windowing, motion correction using a pyramid iterative algorithm, then affine spatial transformation of the anatomical and functional images with brain rotated in to the AC-PC coordinate frame followed by linear scaling into the Talairach reference frame prior to statistical analysis. The images were then averaged together and statistical parametric maps for the t statistic were computed using the GLM (Generalized Linear Model) algorithm implemented within IDL (28). Sets of cosine basis functions were used as covariates to account for possible signal drift and aliased respiratory and cardiac signals. The individual Z-score activation maps were thresholded at 2.58; group maps were thresholded at either Z=4.00 or Z=6.00 (P = 0.05 or lower) to create maps of significant activation.
An intraclass correlation coefficient (ICC, (29, 30)) was used to quantify the reliability of activation by measuring the degree of inter-scan variability relative to the degree of inherent inter-subject variability (15, 31). The methods for computing the ICC are detailed in Eaton et al. (15). Briefly, the z-score activation maps were first thresholded at 1.96 (Puncorrected ≤ 0.05). This created maps of significant activation that had either a ”0” (less than the significance threshold) or a ”1” (greater than or equal to the significance threshold) for each voxel. ICCs were then computed in MATLAB (The MathWorks, Inc., Natick, MA) on a voxel-by-voxel basis across all subjects and all trials. The resulting maps were thresholded at ICC = 0.4 and limited to clusters of size greater than or equal to 25 contiguous voxels to correct for the occurrence of spurious individual voxels with high reliability.
Demographics and clinical characteristics of all study subjects are included in Table 1. There were no demographic differences between healthy controls and stroke subjects in their age (46 vs. 53), personal handedness measured with Edinburgh Handedness Inventory (89 vs. 95); in the case of stroke subjects they were asked to rate their premorbid handedness (32)), familial handedness (93 vs. 95) or years of education (14.3 vs. 14.8). Medical histories and stroke risk factors were present in both groups of subjects and were relatively similar. Neurolinguistic results of this cohort were published previously and are not presented here (15). Figure 1 depicts anatomical location of left MCA strokes in patients enrolled in this study. Stroke locations include inferior frontal, superior temporal, and temporo-parietal cortical areas with extension into the adjacent white matter and deep brain regions.
For the picture identification task both control and aphasic subjects produced consistent results, with higher percentage of correct responses for control subjects relative to aphasic subjects (active condition 97.7% vs. 89.1%, p < 0.001; for the control condition 99.5% vs. 98.8%, p = 0.23).
All healthy control subjects showed strong BOLD signal increases that were quite variable between subjects but, in general, included bilateral frontal and temporal regions (Figure 2; left upper 4 rows). Group analysis of the healthy control data (Figure 2; bottom left) showed clear bilateral, left more than right, BOLD signal increases (yellow/red) in the frontal and temporal language areas and symmetric retro-splenial and posterior cingulate areas. Healthy controls also exhibited symmetric BOLD signal decreases (blue) in the bilateral fronto-temporal language networks that were adjacent to and inferior in the frontal and anterior in the temporal lobes to the areas of BOLD signal increases (Figure 2; left bottom). Locations of the main BOLD signal increases and decreases, including spatial correlates of the centroids are listed in Table 2. As all subjects were right-handed, it is not surprising to note left-lateralized activation with an fMRI task that involves language processing.
In contrast to the healthy controls, different activation patterns were noted in stroke subjects with BOLD signal increases seen predominantly in the peri-stroke areas (Figure 2; right upper 4 rows); only minimal activations noted in the non-dominant (right) hemisphere. Group activation images (Figure 2; bottom right) showing only left hemispheric BOLD signal increases (in yellow) reinforce the notion that in stroke subjects performing visual lexical processing recovered left-hemispheric peri-stroke areas are necessary for generating responses. The limited number of subjects included in this study precludes analyses taking into account the percentage of correct answers and testing the hypothesis that improved responses are associated with increased recruitment of language areas either in the dominant or non-dominant hemispheres. Further, these group activation maps show a pattern clearly different from healthy controls – there is positive activation in the peri-stroke areas and negative activation in midline and right hemispheric structures. Therefore, in this study, stroke subjects performing the visual picture identification task demonstrated a shift of activation to the language-dominant left hemisphere and a shift of deactivation to the contralateral hemisphere unaffected by the stroke. This pattern suggests that reorganization occurs in the stroke patients. Anterior and posterior midline regions that healthy controls use more for the active condition are more active for the control condition in stroke patients. The lateral fronto-temporal activation for control condition is diminished in patients and they are using the affected left fronto-temporal regions (that controls activate for the control condition) for the active condition. This functional reorganization seems to allow the stroke patients to compensate for decreased neurocognitive capacity for the control condition in that performance is comparable between groups. This compensation is inadequate for the active condition and there are obvious deficits in performance for the stroke patients during picture naming task.
The ICC maps for the healthy controls and stroke subjects are shown in Figure 3, and the regions of reliable activation are summarized in Table 3. Healthy controls displayed a number of regions of highly reliable (i.e. consistent, ICC>0.4) activation from scan to scan within typical language-related areas (Figure 3; left), which included left inferior/middle frontal cortex, left middle/superior temporal cortex, and left inferior parietal lobe. In addition, reliable bilateral activation was noted in posterior cingulate cortex, middle/superior occipital cortex, and cuneus, as well as reliable right-sided activation in middle frontal cortex and precuneus. Stroke subjects (Figure 3; right) displayed regions of highly reliable (ICC>0.4) activation which coincided with some of the areas of reliable activation in the controls, specifically left inferior/middle frontal cortex, left middle temporal cortex, left inferior parietal lobe, and right middle occipital cortex and cuneus. However, the exact position and extent of these regions differed between the two groups. In patients, the region of reliable activation in left inferior/middle frontal cortex extends much further in the inferior-superior direction, covering much of the anterior peri-stroke area. Also, reliable activation in the inferior parietal lobe had a focus that was more anterior and superior relative to the controls, placing it near the superior and anterior extents of the affected cortex in some patients. High values of the ICC in these brain regions suggest that these areas are consistently used by the stroke patients to perform the task from scan to scan, and that reorganization of language functions to these regions is stable in the patient group.
Studies of language began with the reports by Broca and Wernicke, who introduced the concept of unilateral left hemispheric control of language functions (33, 34). Their “classical model” of language organization based on data from aphasic patients with brain lesions, popularized in the 19th century, remains in common use. The general principle of this “classical model” is supported by studies of individuals who have lost language secondary to a focal brain lesion. Unilateral cerebral lesions provide a useful approach to the study of early and late hemispheric specialization and offer a context for the investigation of language plasticity (35). The question remains, however, as to how recovery from aphasia due to stroke fits this “classical model.”
Before attempting to explain post-stroke language recovery, it is important to understand the anatomy of language networks in healthy subjects. Several recent neuroimaging studies have evaluated the relative distribution of language dominance in healthy dextral and non-dextral children and adults (26, 36–44). These studies demonstrate that the cortical language distribution is not dichotomous (left or right) but rather that there is a continuum between left- and right-hemispheric language distribution (as also seen in this study with picture identification task). Although phonological and semantic language activation in healthy right-handed subjects is lateralized to the left-hemisphere in 94–96% of subjects, almost all activate homologous right hemispheric areas in response to fMRI and PET language tasks (39, 44, 45).
Two main mechanisms of language recovery after stroke have been proposed: repair of damaged language networks and/or activation of compensatory areas/recruitment of preexisting alternative networks (e.g., homologous areas in the non-dominant for language hemisphere)(46–48). Both mechanisms of recovery have been documented in animal models of motor stroke (49–52). While several studies have evaluated language recovery in children and adults with acute or chronic brain injury, quantitative comparisons between children and adults or between dextral and non-dextral individuals have not been made, and no consensus has been reached as to what mechanisms underlie language recovery after stroke or how long these mechanisms remain accessible following stroke (46–48, 53–56). In the present study, we applied fMRI to studying language recovery after stroke and have shown that the peri-stroke areas are important for language recovery. This is in agreement to our previous adult study using different fMRI tasks (verb generation and semantic/tone decision) which also showed significant contribution of the peri-stroke areas to language production (15). However in children with history of perinatal and early postnatal stroke, it has previously been shown that there is a greater trend to recruit homologous contralateral regions (right inferior frontal more so than posterior temporal) to a greater extent than the peri-stroke areas involved in language tasks (16, 57). Further, the observed shifts in language lateralization, when comparing healthy controls and stroke subjects may indicate that it is the peri-stroke areas and not the non-dominant homologues that are needed for stroke recovery in adults included in this study. The significant ICC values we found in this study suggest that fMRI picture identification task is a valid and reliable marker for functional post-stroke language recovery. Such a task used with fMRI may aid in evaluating the optimal post-stroke language rehabilitation protocols, including newly developed strategies like constraint-induced aphasia therapy (12, 13, 58). Validation of fMRI for this purpose could place a useful tool in the hands of clinicians and researchers investigating optimum strategies for rehabilitation following stroke.
A few neuroimaging studies of children and adults with unilateral lesions have evaluated recovery from aphasia and demonstrated that there is not one pattern of redistributed function that uniformly subserves language recovery. This work has shown that children with a relatively early insult are more likely to demonstrate greater right hemisphere participation in language than those with late onset aphasia (16, 47, 56, 57). In one post-stroke study, when comparing adult aphasic patients to healthy subjects, the authors found redistribution of activation patterns in response to language tasks (55). There was significant activation in the right (non-dominant) superior temporal gyrus, inferior premotor, and lateral prefrontal cortex that was homotopic to the left hemispheric language areas. In another study, Thulborn et al. provided additional evidence supporting the cortical reorganization and migration of language functions to the non-dominant hemisphere’s homologues after a dominant hemisphere insult (53). During a pre-surgical evaluation of an adult epilepsy patient, these authors performed an fMRI study of language that was concordant with subsequent cortical mapping. The patient suffered from severe post-surgical receptive aphasia due to stroke. As the aphasia improved, fMRI studies at 3 and 9 months after stroke showed language migration to the homotopic areas in the non-dominant hemisphere (53). A similar re-distribution pattern using PET and fMRI language tasks was found in another study, though a negative association was observed between increased non-dominant inferior frontal gyrus activation and recovery after an adult ischemic stroke (48). Our small study using a different language activation fMRI task seems to confirm that the peri-stroke areas in the adult dominant hemisphere may be more important for post-stroke recovery than the contralateral homologues and the ability of these areas to recover may have a direct impact on language recovery.
Other fMRI and PET studies have suggested that better language recovery is observed in patients with peri-infarct activation akin our findings with the picture identification task. A previous study by Cao et al. postulated that restoration of the left-hemisphere language networks is associated with best post-stroke recovery (46). To test their theory, they evaluated post-stroke aphasic patients with fMRI and compared their findings to those from normal subjects matched for handedness. In patients who attained excellent language recovery, there was almost no change in activation in the dominant hemisphere compared to the normal subjects; stroke patients also had a significant increase in activation in the homotopic non-dominant hemisphere regions when compared to controls. Patients who failed to restore left-hemispheric language functions had predominantly contralateral fMRI activation, but this did not correlate with good recovery as seen in patients with bilateral response to the language fMRI tasks (46). In a study of repetitive Transcranial Magnetic Stimulation (rTMS) in adults, Winhuisen et al. postulated that post-stroke language recovery is dependent on the preservation of the left-hemispheric language centers rather than recruitment of the non-dominant homologues (59) and that the post-stroke recovery could be related to or be dependent on adequate brain perfusion (60). Breier et al. tested the effect of white matter tract injury on post-stroke language recovery using diffusion tensor imaging (DTI) and found that a higher degree of superior longitudinal tract injury correlated with less language recovery (61). Finally, a small study showed that the laterality of the fMRI activations may be dependent on the phase of post-stroke recovery; early in recovery right-hemispheric upregulation of the BOLD signal changes correlates with language recovery, but later in recovery consolidation of the activation in the left-hemispheric language centers is observed (18). We suspect that the BOLD signal increases in the peri-stroke areas of the dominant hemisphere seen in our study are in fact a reflection of the “consolidation” observed by Saur et al., as our subjects were imaged in the chronic phase of the recovery. These and other studies support the presence of preexisting language pathways in both, the dominant and non-dominant hemispheres. Normally, the circuitry in the non-dominant hemisphere is inhibited by the active circuitry, but when the preferred pathway is interrupted (as in a stroke), the non-dominant circuitry becomes uninhibited, hence activated. However, the contribution of these unmasked pathways to the language recovery process remains unclear and their involvement or activation in fMRI studies may be a sign of maladaptation rather than recovery.
There are multiple reasons for the division in the literature about whether language recovery is associated with ipsilateral or contralateral language restoration. To date, no large comprehensive longitudinal studies comparing the neurophysiological and neuroimaging post-stroke recovery data are available. Furthermore, available imaging studies either involve a very small number of patients or correlate neuroimaging and psychological measures of recovery at only one time point after the stroke (in many cases, several months or years after the stroke). Therefore, generalizations from the available data and comparisons between studies are difficult if possible at all. Conclusions about optimal post-stroke recovery patterns for language recovery will require neuroimaging studies with substantially more power (more subjects) that have been performed to-date. Furthermore, an adequately powered study that includes right and left handed subjects as well as a group of subjects before and after intensive aphasia therapy would provide the most conclusive answers about the neuroplasticity and recovery from aphasia in the adult stroke patients.
In this study we have shown that post-stroke language recovery is associated with increased BOLD signal responses in the peri-stroke areas. This study also reaffirms that the modern imaging techniques provide a reliable tool to examine the brain’s activity, are relatively easy to standardize, and may be quantitative in nature. Validated against clinical outcome measures, fMRI and other functional brain imaging methods may serve as good biomarkers for functional brain recovery and predict the effect of specific therapeutic modalities on a patient’s ultimate clinical status. Such techniques may be used in the future to evaluate the current and emerging post-stroke restorative therapies. Finally, using non-invasive brain mapping techniques including multimodality imaging that combines structural and functional recovery measures will allow us to develop a better understanding of post-stroke aphasia recovery and subsequently lead to the development of better, more optimized and individualized restorative interventions.
This study was in part supported in part by funds from The Neuroscience Institute in Cincinnati, OH (JPS) and in part by R01 NS048281 (JPS).