Influence of Stroke Infarct Location on Functional Outcome Measured by the Modified Rankin Scale
Abstract
Background and Purpose—
In the early days after ischemic stroke, information on structural brain damage from MRI supports prognosis of functional outcome. It is rated widely by the modified Rankin Scale that correlates only moderately with lesion volume. We therefore aimed to elucidate the influence of lesion location from early MRI (days 2–3) on functional outcome after 1 month using voxel-based lesion symptom mapping.
Methods—
We analyzed clinical and MRI data of patients from a prospective European multicenter stroke imaging study (I-KNOW). Lesions were delineated on fluid-attenuated inversion recovery images on days 2 to 3 after stroke onset. We generated statistic maps of lesion contribution related to clinical outcome (modified Rankin Scale) after 1 month using voxel-based lesion symptom mapping.
Results—
Lesion maps of 101 patients with middle cerebral artery infarctions were included for analysis (right-sided stroke, 47%). Mean age was 67 years, median admission National Institutes of Health Stroke Scale was 11. Mean infarct volumes were comparable between both sides (left, 37.5 mL; right, 43.7 mL). Voxel-based lesion symptom mapping revealed areas with high influence on higher modified Rankin Scale in regions involving the corona radiata, internal capsule, and insula. In addition, asymmetrically distributed impact patterns were found involving the right inferior temporal gyrus and left superior temporal gyrus.
Conclusions—
In this group of patients with stroke, characteristic lesion patterns in areas of motor control and areas involved in lateralized brain functions on early MRI were found to influence functional outcome. Our data provide a novel map of the impact of lesion localization on functional stroke outcome as measured by the modified Rankin Scale.
Introduction
Prognosis of functional outcome after ischemic stroke is influenced by a variety of factors already assessable in the acute phase and within the first days after symptom onset. In clinical trials, stroke outcome is most commonly rated by the modified Rankin Scale (mRS)1 because of the validity and rapid application of this rating scale and its ability to discriminate clinically relevant levels of disability and recovery.2–4 Brain imaging in the early phase after stroke onset provides valuable information related to individual functional recovery.5,6 In particular, structural MRI identifies injured brain regions and allows for assessment of extent and location, both known to influence and predict functional outcome measured by the mRS.3 However, infarct volume from early MRI correlates only moderately with the mRS at later time points,7,8 indicating that additional factors, such as lesion location, influence functional outcome. It is therefore of major interest to elucidate the relationship between early lesion patterns and functional impairment in the later course of stroke.
Clinical impact of lesion locations can be inferred from voxel-based lesion symptom mapping (VLSM). This statistical method examines effects of brain lesions on behavioral scores on a voxel-by-voxel base. Therefore, a statistical test is conducted for each voxel to detect differences in a behavioral score based on the presence or absence of injury.9 VLSM produces statistical results that map structural lesions to a behavioral scale. In patients with chronic stroke, it has been applied to identify areas critical for motor recovery,10 spatial neglects,11 and language comprehension.12
In this study, we examined stroke lesion pattern from early MRI (days 2–3) to identify lesion locations that influence clinical outcome measured by the mRS after 1 month. We hypothesized that (1) brain areas linked to physical disability will show a strong association with higher mRS values (ie, worse clinical outcome) and (2) different lesion locations would characterize individual contribution to functional outcome depending on hemisphere side.
Methods
Patients and Clinical Assessment
We analyzed MRI and clinical data from the I-KNOW database (http://www.i-know-stroke.eu). I-KNOW was an European multicenter study aiming at collecting a large sample of patients with anterior circulation stroke, who underwent both admission and follow-up MRI to derive maps of infarct prediction based on clinical and imaging variables. In I-KNOW, patients with first-ever stroke and a National Institutes of Health Stroke Scale (NIHSS) >4, MRI ≤12 hours of witnessed stroke onset, and either conservative or intravenous thrombolytic treatment were included. Among other clinical parameters, patient age, sex, side of ischemic lesion, severity of neurological deficit on admission assessed by the NIHSS, and functional deficit (measured by the mRS) before stroke and after 1 month were recorded.
The mRS consists of 7 grades rated as follows: 0, no symptoms at all; 1, no significant disability: despite symptoms, able to perform all usual duties and activities; 2, slight disability: unable to perform all previous activities but able to look after own affairs without assistance; 3, moderate disability: requiring some help but able to walk without assistance; 4, moderately severe disability: unable to walk without assistance and unable to attend to own bodily needs without assistance; 5, severe disability: bedridden, incontinent, and requiring constant nursing care and attention; and 6, death.
In addition to the original inclusion criteria, we selected only patients without previous functional deficits (mRS before stroke, 0), MRI data on days 2 to 3, and mRS after 1 month. The study was approved by the local ethics committees and institutional review boards (University Centre Hamburg-Eppendorf, Germany).
Imaging Data
Fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging data were acquired on 1.5 magnets according to the I-KNOW imaging protocol. Data were acquired at days 2 to 3 after stroke onset. Typical imaging parameters for FLAIR sequences were echo time, 100 ms; repetition time, 8000 ms; inversion time, 2300 ms; field of view, 250; and slice thickness, 5 mm. For diffusion-weighted imaging: b value, 1000 s/mm2; echo time, 100 ms; repetition time, 5000 ms; field of view, 250; and slice thickness, 3 mm. Stroke lesions were segmented on FLAIR imaging data using an in-house developed software tool for the analysis of stroke image sequences (AnToNIa, Analysis Tool for Neuro Image Data)13: first, a rough region of interest (ROI) surrounding the FLAIR lesion was drawn manually with a generous margin at each affected slice. The single ROIs were then combined to a volume of interest and refined by manually applying and adjusting a lower threshold of FLAIR signal intensity. Voxel exhibiting signal intensities below this threshold were rejected from the initial lesion volume of interest. Accuracy of lesion delineation was inspected visually at each slice, and the corresponding diffusion-weighted imaging images were consulted for confirming plausibility and extent of infarct ROI. If required, manual correction was performed. It has been shown that FLAIR images provide high sensitivity for acute cerebral infarcts with high interobserver and intertechnique reproducibility for the detection of ischemic lesions.14–16 Lesion volumes were calculated for each refined volume of interest. After this, the FLAIR data set of each patient was registered to the standard Montreal Neurological Institute (MNI)17 brain atlas. Therefore, the individual optimal affine transformation of each FLAIR data set to the reference atlas was calculated using the mutual information metric and linear interpolation. The resulting affine transformation was then used to align the segmented FLAIR lesion in the MNI atlas space using a nearest-neighbor interpolation.
For VLSM, we used the nonparametric mapping toolbox included in the MRIcron software package18 (MRIcron, Version 6.6.2013). All lesion volume of interest (n=101) were flipped onto the left hemisphere to increase statistical power identifying lesion pattern with significant contribution to functional outcome independent of lesioned hemisphere. Lesion overlap was calculated to create a color-coded overlay map of injured voxel across all patients to provide an overview of all lesioned brain areas and areas with highest lesion frequency. We then performed a group comparison for each voxel (lesioned or nonlesioned) using the mRS as dependent variable and the Brunner and Munzel Rank order test implemented in the nonparametric mapping toolbox.18 This test provides a Z score map where higher values indicate higher impact on (worse) recovery. To correct for multiple comparisons, we used a permutation-based familywise error (FWE) correction with 2000 permutations. Only voxel affected in ≥10 individuals (10%) were tested. A FWE correction threshold of 5% was applied. In the resulting figures, the color range indicates Z scores resulting from Brunner–Munzel testing corrected for multiple comparison.
In a second step, we investigated hemisphere-specific influences. Therefore, the Brunner and Munzel Rank order test was calculated for each hemisphere so that 2 separate tests were performed for right- and left-sided lesions (n=47 right and n=54 left). Accounting for the lower sample size and exploratory nature of this analysis, we choose a false discovery rate (FDR) of 1% (0.01) to correct for FWEs. Although the FDR is a more liberal method then conventional FWE correction, this threshold ensures that false-positive results do not exceed >1% of all true-positive results.
Resulting statistical maps were processed using imaging tools of the Functional MRI of the Brain Software Library (FMRIB Software Library; http://www.fmrib.ox.ac.uk/fsl).19 Therefore, Z score maps were masked with anatomic ROIs provided by the Harvard-Oxford Cortical Structural Atlas20 and Johns Hopkins University International Consortium of Brain Mapping Diffusion Tensor Imaging (JHU ICBM-DTI)-81 White Matter Labels21 implemented in FMRIB Software Library. Median, minimum, and maximum Z score values were calculated in each anatomic ROI and voxel coordinates of peak values located automatically using imaging tools implemented in FMRIB Software Library.
Statistical Analysis
Clinical data were described with mean and 95% confidence intervals for continuous data and numbers and percentage for categorical data. Group comparison of clinical and imaging data between patients with right- and left-hemispheric stroke was performed using an independent t test or Wilcoxon rank-sum test as appropriate. Correlation of lesion volumes with clinical outcome (mRS) was analyzed using Spearman ρ correlation coefficient. Statistical analysis was done using SPSS version 20.0 (IBM Co, Somers, NY).
Results
Patient Characteristics
Of 168 patients included in the I-KNOW database, 67 patients were excluded from analysis because of MRI data of insufficient quality or missing data at days 2 to 3. In total, clinical and MRI data of 101 patients were analyzed. Details of clinical data are given in Table 1.
| Left Hemisphere Stroke | Right Hemisphere Stroke | P Value | |
|---|---|---|---|
| Frequency, n | 54 | 47 | … |
| Mean age, y (95% CI) | 70 (67–72) | 64 (60–68) | 0.023 |
| Mean NIHSS at admission (95% CI) | 12.1 (10.5–13.7) | 10.8 (9.1–12.4) | 0.33 |
| Median NIHSS at admission (IQR) | 11 (9) | 11 (9) | … |
| FLAIR lesion volume at days 2–3 (95% CI) | 37.7 (23.6–51.7) | 43.2 (27.6–58.9) | 0.89 |
| Mean mRS at day 30 (95% CI) | 2.1 (1.6–2.6) | 2.1 (1.7–2.5) | 0.85 |
| Median mRS at day 30 (IQR) | 2 (4) | 2 (2) | … |
| Frequency of mRS subscores, n | |||
| 0 | 15 | 6 | … |
| 1 | 11 | 14 | … |
| 2 | 9 | 10 | … |
| 3 | 4 | 8 | … |
| 4 | 9 | 7 | … |
| 5 | 6 | 2 | … |
| 6 | 0 | 0 | … |
P values are shown resulting from group comparisons between patients with left- and right-hemispheric stroke lesions. CI indicates confidence interval; FLAIR, fluid-attenuated inversion recovery; IQR, interquartile range; mRS, modified Rankin Scale; and NIHSS, National Institutes of Health Stroke Scale.
The right hemisphere was affected in 47 patients (47%). Mean values of individual NIHSS items on admission are shown in Figure I and Table I in the online-only Data Supplement according to affected hemisphere. Baseline characteristics depending on lesion side are shown in Table 1. In group comparison, mean age was higher in patients with left-sided infarction (P=0.023). There were no significant differences between groups as to clinical impairment measured by the NIHSS at admission or mRS after 1 month. Lesion volumes were comparable between both sides (left side, 37.7 mL; 95% confidence interval, 23.6–51.7 mL and right side, 43.2 mL; 95% confidence interval, 27.6–58.9 mL). Overall mean lesion volume on days 2 to 3 was 40.1 mL (95% confidence interval, 30–50.1). Lesion volume on days 2 to 3 correlated moderately with functional outcome after 1 month as measured by the mRS (r=0.624; P<0.001).
Voxel-Based Lesion Symptom Mapping
Color-coded overlays of FLAIR stroke lesion distribution on days 2 to 3 of all patients after flipping onto the left hemisphere (n=101) are shown in Figure 1. Highest frequency of injury was observed in the deep territory of the middle cerebral artery (MCA) with lesion distribution concentrating at the striatocapsular region and insula and decreasing toward the borders of the MCA territory.
Results of VLSM are shown in Figure 2 by color-coded overlays. A permutation FWE correction (threshold=0.05) resulted in a Z score value of 4.8. Z values and anatomic MNI coordinates of voxels with highest Z score values are given in Table 2. A full list of minimal, maximal, mean, and median Z score values of all template ROIs is provided in Table II in the online-only Data Supplement. Mapping of the mRS revealed significant contribution of brain regions comprising the motor pathway, namely the posterior limb of the internal capsule and corona radiata. Moreover, injury involving the insular and opercular cortex was associated strongly with higher mRS values.
| Region | MNI Coordinates | Max Z Score | Mean Z Score | Median Z Score | SD |
|---|---|---|---|---|---|
| Central opercular cortex | −54, −4, 12 | 8.0 | 4.4 | 4.4 | 1.1 |
| Corona radiata (posterior part) | −26, −28, 22 | 7.1 | 4.3 | 3.9 | 1.3 |
| Corona radiata (superior part) | −24, −18, 3 | 8.2 | 4.2 | 4.0 | 1.0 |
| Capsula externa | −32, −4, 4 | 8.0 | 4.1 | 4.2 | 1.3 |
| Capsula interna (posterior limb) | −26, −26, 18 | 6.9 | 3.6 | 3.5 | 0.7 |
| Insular cortex | −40, −12, 8 | 7.2 | 3.3 | 3.2 | 1.4 |
All coordinates are given in MNI space. Mean, median, and SD of Z scores in selected regions are shown. Familywise error correction (0.05) resulted in a threshold for Z score of 4.8. JHU ICBM-DTI indicates Johns Hopkins University International Consortium of Brain Mapping Diffusion Tensor Imaging; and MNI, Montreal Neurological Institute.
Results of VLSM for each separate hemisphere (right, n=47; left, n=54) are shown in Figure 3. Lesion overlays for both hemispheres are shown in Figure II in the online-only Data Supplement. A FDR correction (threshold=0.01) resulted in Z score values of 3.1 (right hemisphere) and 2.7 (left hemisphere). On visual inspection, VLSM showed lateralized influences of stroke lesions on the mRS reflected by mean and maximal z values (Table III in the online-only Data Supplement). In the right hemisphere, this asymmetry was prominent in the inferior parietal lobe, specifically in the angular gyrus (MNI coordinates of peak value, 54, −52, 26; Z score, 3.9). In the left hemisphere, a cluster of injured voxel in the middle and superior temporal gyrus influenced mRS values (MNI coordinates of peak value, −48, −34, 2; Z score, 3.54). See also Figure 4 for an annotated version of the VLSM map.
Discussion
Using VLSM, we examined the influence of lesion localization from early MRI on functional outcome as assessed by the mRS after 1 month. We studied a representative group of patients with moderate to severe stroke reflected by a mean NIHSS score of 11. Lesions were distributed throughout the MCA territory showing a typical distribution overlap pattern similar to previous observation.22 Our results illustrate the complex relationship between spatial pattern of injury and functional deficits in patients with stroke. In addition to the known impact of lesion volume on functional outcome, we present a novel map linking structural brain damage with the mRS.
Assessment of lesion symptom maps yielded 2 main findings: first, injury to areas of the corticospinal tract related to higher functional impairment as measured by the mRS. In our group, patients recovered less well depending on damage to the corona radiata (and lack thereof, see Figure 2). These intuitive findings are in line with previous studies mapping corticospinal tract lesions to motor impairment and motor function recovery in patients with ischemic stroke.23–27 Using a similar methodological approach, Lo et al10 identified areas in the corona radiata critical for motor function recovery measured by the Arm Motor Ability Test. The mRS broadly assesses the degree of disability or dependence in the daily activities, which strongly depend on intact motor functions.4 Results from validity studies show that specific clinical impairments, such as limb weakness, contribute significantly to short- and long-term disability measured by the mRS.28 This aspect of our findings is, therefore, plausible and highlights the clinical meaning of the mRS from a structural and anatomic perspective.
A considerably high impact on functional outcome was also found at the insula and surrounding opercular cortex. There are several aspects to this finding: insular lesions are common in nonlacunar strokes and have found in up to half of all patients with MCA infarcts.29 This is also the case in our group of patients as shown by the overlap map of lesion distribution (Figure 1). Moreover, insular involvement often occurs in proximal occlusion of MCA causing large infarct volumes and damage to the lenticulostriate subcortical territory of the MCA, both of which result in severe motor deficits and low functional outcome.30 However, the exact means by which damage to the insula influences clinical outcome is not known. In recent years, a variety of clinical deficits are being attributed to insular injury, including speech and language, hand-and-eye motor movement, space and body perception, and cardiovascular regulation.31 Impairment of some of these functions has also been shown in patients with ischemic stroke.32–34 Insular lesion influence on clinical outcome measured by the mRS is, however, less clear and interpretation of our results have to remain speculative in this regard.
The second finding of our study illustrates the distinct influence of brain lesions depending on hemisphere side. Although lesion symptom mapping patterns seem fairly evenly distributed in the striatocapsular regions in both hemispheres, asymmetrical patterns were detected involving the right inferior parietal lobe and left superior/middle temporal lobe (Figures 3 and 4). About the right hemisphere, one might speculate that damage to the inferior parietal lobule leads to neglect, which in turn disturbs a wide range of activities of daily living captured by the mRS. In our group, half of all patients with right-sided infarctions (n=24; 51%) showed clinical signs of neglect on admission measured by the NIHSS (item extinction and inattention >0 points; Figure 1). The right inferior parietal lobe is anatomically and functionally linked to frontal and temporal areas creating a perisylvian neural network proposed to represent the anatomic basis for functions involving spatial orientation and exploration.35 Furthermore, damage to the right inferior parietal lobe was associated with visual–spatial components of neglect in a VLSM study of 80 patients with right hemisphere stroke.36 From a clinical point of view, neglect strongly influences functional outcome after stroke by either interfering with correct processing of external stimuli37 or in its negative effect on motor rehabilitation,38 which is also reflected by higher mRS scores.
With regard to the left hemisphere, an additional asymmetrical lesion pattern was apparent in the superior and middle temporal cortex (Figures 3 and 4). In analogy to the common functional right-sided lateralization of neglect, these findings in the left hemisphere could point to the influence of aphasia on functional rehabilitation. Both, the superior and middle temporal gyrus, have been found to facilitate auditory language comprehension39 and have been highlighted as critical regions in patients with poststroke aphasia by VLSM and voxel-based morphometry.40 Global aphasia has been demonstrated previously to represent a significant risk factor for higher mRS values.41
Left-to-right asymmetry in lesion impact maps underscores that the mRS as a global disability scale is weighted toward functions of the dominant hemisphere. A similar result has been found accounting for functional deficits measured by the NIHSS.42 Previous studies have reported an impact of hemisphere side on clinical characteristics at baseline, treatment outcome, and functional recovery of patients with stroke.43–45 However, studies of clinical outcome comparing patients with right- or left-sided lesions have been inconclusive possibly because of selection bias introduced at different time points starting from symptom recognition to selection for rehabilitation admission.46 Our findings highlight the fact that impact of structural lesions on recovery involves specific brain regions depending on hemisphere side. Thus, we extend previous findings by providing localized maps that add to information gained by clinical examination (clinical score) or basic imaging (stroke lesion side and volume).
We have studied findings from a representative group of moderately to severely affected patients with stroke. However, exclusion of mildly affected patients (NIHSS <4) limits interpretation of our results. An additional selection bias is introduced by inclusion of patients with MRI examinations that might not have been tolerated by patients with severe clinical deficits. Similarly, patients with posterior territory stroke, especially patients with isolated visual field defects, are not represented in our results.
Lesion mapping can identify brain areas that are critical for clinical functions. However, it is not possible to infer causality. In our work, we used FDR to correct for multiple comparisons from VLSM separated by hemisphere side. This liberal correction controls the rate of false alarms to true hits, as previously applied in lesion analysis.9,47 Given the large number of brain voxels and the fact of cross-dependency with regard to function, FDR correction seems a reasonable approach for an exploratory analysis without dramatically increasing the rate of false-positive results. In addition, our analysis is limited by the lack of factors that have been shown to predict functional outcome after stroke, most notably the initial NIHSS, patient age, and lesion volume. We have chosen FLAIR imaging for lesion delineation in accordance with previous VLSM studies in stroke population at similar time points.11,48 Although accuracy of lesion localization and extent was checked in corresponding diffusion-weighted imaging datasets, we cannot exclude a confounding influence of FLAIR hyperintensities resulting from pre-existing white matter lesions. Finally, we acknowledge the arbitrary and limited nature of clinical scores selected in this study. Although the mRS is currently the most commonly used outcome scale in clinical stroke studies, selection of other available outcome measures (NIHSS, Barthel Index, and Glasgow Outcome Scale) will most likely result in different results and should be examined in future studies.
Conclusions
Our study provides a novel atlas of structural lesion impact on functional outcome after stroke using early MRI at days 2 to 3 after stroke onset. Lesion-symptom maps demonstrate specific influence of motor pathway injury on the mRS and reflect lateralized functions such as neglect and aphasia. Our results provide insight into the impact of structural brain injury on functional outcome as captured by the mRS as the most commonly used outcome rating scale in clinical stroke research.
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© 2014 American Heart Association, Inc.
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History
Received: 13 February 2014
Revision received: 26 March 2014
Accepted: 31 March 2014
Published online: 29 April 2014
Published in print: June 2014
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Sources of Funding
This work was supported by the Deutsche Forschungsgemeinschaft (DFG), Sonderforschungsbereich (SFB) 936, Project C2 and by the European Union (EU) Grant I-KNOW (027294). Dr Hilgetag received research grant from the DFG, SFB 936, Project A1 (no compensation). Dr Gerloff received research grant from the DFG, SFB 936, Project C1 (no compensation) and the EU, Seventh Framework Project WAKE-UP, Grant No. 278276 (no compensation). Dr Thomalla received research grant from the EU, Seventh Framework Project WAKE-UP, Grant No. 278276 (no compensation).
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