Sage Journals: Discover world-class research

Abstract

Despite promising results in preclinical stroke research, translation of experimental data into clinical therapy has been difficult. One reason is the heterogeneity of the disease with outcomes ranging from complete recovery to continued decline. A successful treatment in one situation may be ineffective, or even harmful, in another. To overcome this, treatment must be tailored according to the individual based on identification of the risk of damage and estimation of potential recovery. Neuroimaging, particularly magnetic resonance imaging (MRI), could be the tool for a rapid comprehensive assessment in acute stroke with the potential to guide treatment decisions for a better clinical outcome. This review describes current MRI techniques used to characterize stroke in a preclinical research setting, as well as in the clinic. Furthermore, we will discuss current developments and the future potential of neuroimaging for stroke outcome prediction.

Keywords

stroke magnetic resonance imaging perfusion diffusion fMRI outcome prediction

Introduction

Stroke is the third leading cause of death and the leading cause of disability in developed countries globally. The major obstacle to effective acute stroke management is time. It is estimated that fewer than 10% of all stroke patients receive the only approved treatment, thrombolysis with recombinant tissue plasminogen activator (rtPA; Cocho et al, 2005). There are several reasons for this, the primary of which is that thrombolysis is only approved for use within 3 h after symptom onset, although recent studies have suggested benefit beyond that from 4.5 (Hacke et al, 2008) to as long as 6 h (Davis et al, 2008; Rother et al, 2002). Other potential reasons include lack of public awareness, intrahospital delays, or precaution on account of the increased risk (7%) of intracerebral hemorrhage (ICH) that accompanies rtPA (Bambauer et al, 2006; Kleindorfer et al, 2004). In addition, it is controversial whether small vessel occlusions (lacunar stroke) respond as well to thrombolysis as territorial strokes (Cocho et al, 2006; Hsia et al, 2003; Hwang et al, 2008; rtPA for minor strokes: the National Institute of Neurological Disorders and Stroke rt-PA Stroke Study Experience, 2005). Nevertheless, when successful, early recanalization is highly correlated with reduced infarct volume and improved outcome scores (Felberg et al, 2002; Uchino et al, 2005). Because acute neuroimaging is not consistently performed, it is difficult to estimate the number of patients that exhibit spontaneous recanalization. Reports vary between 77% in patients with cortical infarcts using computed tomography (CT) and 32% in patients with middle cerebral artery occlusion (MCAO), using magnetic resonance angiography (MRA; Jorgensen et al, 1994; Neumann-Haefelin et al, 2004). Clearly, the heterogeneity of the patient population makes the decision to treat a difficult one. Therefore, effective neuroimaging strategies are essential to improve the standard of patient care.

Although CT is still the most prevalent imaging modality in acute stroke, magnetic resonance imaging (MRI) is starting to measure up. The slightly longer acquisition times required for MRI represent a disadvantage. However, in less than 15 mins several different scans can be obtained that provide much more information regarding different tissue parameters. Magnetic resonance imaging can identify preexisting lesions and/or diseases, locate the thrombus, recognize ICH, classify stroke subtype, assess blood supply, and provide information about the approximate time of ischemia onset and the extent of injury. The function of MRI in acute stroke is to confirm the clinical diagnosis and to assess the risks and benefits for therapy. In an ideal situation, MRI would provide information that would assist with stratification of patients based on most likely outcome. In the acute clinical setting, important scenarios to differentiate for the clinician are: (1) spontaneous improvement, (2) improvement with therapy, and (3) no improvement despite therapy (Figure 1). In this review, we describe the MRI techniques currently used as surrogate markers and predictors of outcome in patients and experimental animal models of stroke. Future challenges of MRI-based outcome prediction in stroke will be discussed.

Figure 1

Magnetic resonance imaging (MRI)-guided stroke therapy. Three clinical scenarios are indicated in this diagram: (1) spontaneous improvement, (2) improvement in response to therapy, and (3) no spontaneous improvement or response to therapy Only in scenario 2 is therapy really effective, whereas side effects could worsen outcome in 1 and 3.

Surrogates for outcome assessment

One of the key issues in stroke assessment is how to best choose study end points that appropriately indicate outcome. Ideally, the end point should reflect the functional impairments caused by the disease and/or their effect on the quality of life. Therefore, the most common end points in the clinic are neurologic scales. Several neurologic scales have been used as surrogates for outcome, among them the modified Rankin scale, Glasgow Outcome Scale, and Barthel Index (Kasner, 2006). The modified Rankin scale and Glasgow Outcome Scale are used as indicators of functional independence for daily activities; and although both have been shown to be extremely reliable and reproducible (Banks and Marotta, 2007), they are not as comprehensive as the Barthel Index, which provides a more detailed examination of self-care abilities (Sulter et al, 1999). However, these measures are usually only performed out to 3 months because most spontaneous recovery is maximal by 10 weeks (Schiemanck et al, 2006). Therefore, these outcome surrogates have not been sufficiently studied long term, despite the fact that the aged brain may be capable of recovery many years after stroke.

In experimental animal research functional outcome surrogates are referred to as behavioral testing. Unfortunately, as most end point measures are collected within the first week of the ischemic event it is difficult to identify potential surrogates of functional outcome in the chronic setting. Nevertheless, several approaches have been used to assess functional outcome. A wide range of neurologic scores have been developed that attempt to mimic the clinical situation. They range from a simple 0 to 5 score based primarily on forelimb retraction (Bederson et al, 1986) to a slightly more detailed assessment that includes sensory response to stimuli (Garcia et al, 1995). Often this approach is preferred because neurologic scores are easy to perform, fast, and require very little equipment or expertise. However, the scores are not particularly sensitive to specific functional impairments and animals show a great deal of recovery. Other tests are designed to maximize the difference between the intact and impaired side of the body, typically, sensory capabilities of the forepaws. These are collectively referred to as asymmetry tests (Barth et al, 1990; Schallert et al, 2000). Ideally, tests designed to monitor skilled motor function in rodents should provide better comparability to the clinical situation. Challenging tests for skilled motor function exist, for example, skilled reaching for food in trays, on staircases (Montoya et al, 1991), or single food items (Whishaw et al, 1992). However, the highly labor-intensive and interpretive nature of these tests means they are often excluded from the literature.

Imaging surrogates

Infarct Size

Magnetic-resonance-assessed final infarct size has been consistently used as an outcome surrogate based on the notion that the size of the insult is correlated with outcome severity. Indeed, a recent meta-analysis of the clinical literature—not part of any randomized clinical trial—reported a correlation between MRI-based lesion size and functional outcome parameters (Schiemanck et al, 2006). This analysis included studies that used several different methods to estimate acute lesion size including diffusion and perfusion weighted imaging (DWI and PWI, respectively), as well as T₂-weighted imaging. The T₂-weighted volume estimations are typically smaller than the initial DWI or PWI lesion size calculations, and are more reliable for subacute and long-term detection than they are for acute detection. As such, they are often used as a surrogate for final infarct size (Kane et al, 2007). Diffusion weighted imaging and PWI for acute lesion size will be discussed later about their potential to predict final lesion size.

Despite the use of T₂-weighted imaging to estimate final infarct size, debate exists regarding whether it is the most reliable measure. Fluid attenuation inversion recovery (FLAIR) is superior to conventional T2-weighted imaging regarding lesion conspicuity in the subacute stages (Ricci et al, 1999) because of its high sensitivity to very small accumulations of fluid by effectively nulling the signal from the cerebral spinal fluid. Fluid attenuation inversion recovery is currently included into the routine clinical acquisition scan package. Furthermore, interrater agreement using fluid attenuation inversion recovery has been reported to be better than for T₂-weighted imaging (Neumann et al, 2009). Manual delineation is still the most common approach to estimate infarct size, despite the significant measurement error (Davis et al, 2008), because automated volumetry is confounded by preexisting disease, individual variances in shape, location, and severity of signal change.

Final infarct size has been used consistently as an outcome surrogate in the experimental animal setting. Infarct size has traditionally been measured with 2,3,5-triphenyltetra-zolium chloride, hematoxylin–eosin, or nissl-stained brain sections, though the increasing availability of MRI in the experimental research environment has started to produce studies in which T₂-weighted imaging has been used to estimate final infarct size (Ashioti et al, 2007; Farr et al, 2007; Palmer et al, 2001). Infarct sizes assessed by T₂-weighted imaging have been shown to correlate well by some (Palmer et al, 2001) and to underestimate histologic damage by others (Neumann-Haefelin et al, 2000). Unfortunately, infarct size has been the primary, and often only, end point measure collected in many experimental stroke studies for quite some time. There are hundreds of potential compounds/drugs that were perceived as potential neuroprotective agents because of their ability to reduce infarct size in rodent models of stroke. However, all have failed to provide any benefits in clinical trials, a comprehensive list of clinical drug trials can be found at the Stroke Trials Registry website of the Internet Stroke Centre (Goldberg). Some of the most popular examples that have made it to phase III clinical trials without evidence of clinical efficacy include glutamate antagonists (for example, Selfotel: Acute Stroke Studies Involving Selfotel Treatment) (Davis et al, 2000), sodium or calcium channel blockers (for example, Lubeluzole: Lubeluzole in Ischemic Stroke) (Diener et al, 2000), or the recently highly publicized free radical scavenger Cerovive: Stroke Acute Ischemic NXY-059 Treatment (SAINT I and II) (Diener et al, 2008). It is therefore likely that the criterion of infarct size alone is insufficient to be used as a sole outcome surrogate. Functional connectivity of adjacent brain regions can be affected by a stroke through retrograde degeneration between existing neuronal networks. This is not observable using infarct size estimations, but could be inferred with other imaging modalities.

Diffusion Tensor Imaging

Anisotropy is the direction-dependent diffusion of water, which is faster in the direction of fiber tracts than perpendicular to them. Therefore, diffusion tensor imaging (DTI) was developed to visualize the orientation and properties of white matter (Basser et al, 1994). In principle, DTI could thus be used to detect some degree of physical connectivity between brain regions, which could be used as an outcome surrogate in the long-term setting. Typically, DTI data are presented as two-dimensional fractional anisotropy (FA) maps. Although FA has consistently been shown to decrease after stroke as gray and white matter disintegrate (Buffon et al, 2005), some variability in FA has been observed acutely. Decreases (Morita et al, 2006; Zelaya et al, 1999) and increases (Bhagat et al, 2008; Ozsunar et al, 2004) have been observed, and though the exact mechanism of the increase remains unclear, it is possible that perpendicular diffusion is restricted hyperacutely. Recovery of FA values 3 years after stroke has been observed in the internal capsule of patients with upper limb impairments subjected to 30 days of motor training (Stinear et al, 2007). If a sufficient number of diffusion directions and gradient strengths are used, DTI data can be reconstructed as three-dimensional maps that are color coded for directional sensitivity and continuous virtual tracts can be traced based on the largest principal diffusivity between voxels (tractography). This strategy has been used to observe changes in the corticospinal tract after stroke (Moller et al, 2007) and to correlate DTI signals in certain fiber tracts of the ischemic hemisphere to the likelihood of outcome improvement (Pannek et al, 2009).

In agreement with the clinical reports, FA values also decrease in the ischemic territory of the rat brain over time (depicted in Figure 2). However, some groups have reported increases in FA values near the lesion boundary between 3 and 9 weeks after stroke (van der Zijden et al, 2008), which is enhanced with neural progenitor cell treatment (Jiang et al, 2006), as well as in the ipsilateral striatum around 21 days after stroke (Granziera et al, 2007). The latter two studies also used ex vivo DTI measurements to obtain tractography. Abnormal fiber trajectories were identified that originated in the ischemic and projected to the contralateral striatum in a small subset of animals with subcortical infarcts (Granziera et al, 2007), and increased numbers of tracts were observed projecting from the corpus callosum into the injured tissue (Jiang et al, 2006). However, conclusions regarding white matter reorganization must be interpreted cautiously on account of the sensitivity of the measurements and drawbacks with the analysis methods. In addition, the long acquisition times required for tractography represent a major drawback for in vivo experiments, particularly in the experimental animal setting. Scan times depend on resolution requirements, hardware capabilities, and sequence parameters. For example, to obtain an in-plane resolution of 400 μm² using 30 diffusion directions and a single gradient strength, acquisition time is estimated to be approximately 30 mins. This would double with each additional gradient strength and/or average. Time can also be gained with hardware improvements, for example, parallel imaging, which is common in the clinic, and future improvements in analysis strategies could increase the potential of DTI as an imaging surrogate.

Figure 2

Changes in diffusion tensor imaging (DTI) in rats after transient middle cerebral artery occlusion (MCAO). Fractional anisotropy (FA) maps at different time points (DO–D14) averaged from eight animals, overlaid onto averaged apparent diffusion coefficient (ADC) maps. In the acute stages, there is a local FA increase (arrow on D0) in the ischemic territory. Subsequently, anisotropy decreases and fiber tracts degenerate ipsilateral to the lesion (arrow in D14). Corresponding ADC increases with tissue necrosis and liquefaction.

Functional MRI

Connectivity between brain regions can also be inferred by measuring brain activity in stroke patients using functional MRI (fMRI). Depending on the kind of functional deficit, individual tasks can be designed to pinpoint where brain activity is impaired and how the ischemic brain has adapted to the injury, which makes fMRI a complementary imaging surrogate to infarct size measurements. As to reorganization of motor function after stroke, several general patterns of fMRI activity changes have been observed, reviewed elsewhere (Calautti and Baron, 2003; Carey and Seitz, 2007; Cramer and Bastings, 2000; Grefkes and Fink, 2009). Activity significantly increases in motor-related and peri-infarct areas, and tasks performed by the impaired hand produce bilateral cortical activation, including regions not activated in intact patients. The heterogeneity of the patient population requires stratification of lesion types to identify trends. Subcortical lesions often recruit independently connected cortical regions, whereas patients with cortical lesions show recruitment of peri-infarcted cortices. In general, recruitment of peri-infarct tissue is associated with improved recovery.

The availability of only a few stimulus/response fMRI paradigms in rodents means that this field is relatively unexplored in the preclinical research environment. The most well-characterized paradigm is the detection of either a cerebral blood flow (CBF) or blood-oxygen-level-dependent response in the primary somatosensory cortex (S1) after electrical stimulation of the forelimbs (Mandeville et al, 1998; Silva et al, 1999). In general, blood-oxygen-level-dependent and cerebral blood volume responses to forelimb stimulation are decreased after MCAO, and become more variable when compared with an intact response in healthy control animals (Butcher et al, 2005). However, a few groups have observed changes in the fMRI response, which correlate with the clinical literature. Stimulation of the impaired limbs produced activation in the intact sensorimotor cortex, and formerly unresponsive regions in the peri-infarcted tissue (Abo et al, 2001; Dijkhuizen et al, 2001; Rother et al, 2002). Interestingly, when repetitive fMRI sessions were performed in the same animals, three types of responders were characterized: those that retained, those that lost, and those that exhibited only a transient loss of the blood-oxygen-level-dependent response that was independent of infarct size measurements (Weber et al, 2008). As is the case with DTI, fMRI could offer complimentary information to the standard infarct size estimations and could thus be considered a surrogate.

Outcome predictors

In contrast to surrogates, which are useful in the long-term setting to assess end point measures, outcome predictors are parameters that may be used in the acute setting of stroke to foresee the course of the disease or the potential benefit of treatment. Arguably the most common clinical predictor of outcome is the National Institutes of Health Stroke Scale (NIHSS), which is used in the acute stroke setting to assess a patient's neurologic symptoms. The National Institutes of Health Stroke Scale score has been shown to be highly correlated with differences in lesion size (Warach et al, 2000), and is an excellent predictor of outcome determined using the modified Rankin scale at 3 months (Johnston et al, 2009; Kasner, 2006). Ideally, as is the case with surrogates, additional predictors would be extremely useful and in this section we discuss several promising MRI predictors.

Magnetic Resonance Angiography

Magnetic resonance angiography is used acutely in the clinic for fast and effective diagnosis of acute stroke, primarily by identifying the location of the thrombus (Yu et al, 2002) and visualizing recanalization either spontaneously or in response to rtPA (Kimura et al, 2009). In terms of its predictive potential, MRA has been used to predict the degree of recanalization, which is highly correlated with outcome. The Thrombolysis In Myocardial Infarction grading system has been applied to assess the degree of the recanalization in patients with MCAOs using time-of-flight (TOF) MRA (Neumann-Haefelin et al, 2004). Patients with complete, and even minimal, recanalization exhibited significantly less lesion growth.

In addition to the success of recanalization therapies, MRA can be used to predict the risk of stroke by evaluating the degree of stenosis, and/or discrete changes in vessel walls, such as arteriovenous malformations or vasculitis (Kuker et al, 2008; reviewed in Latchaw et al, 2009). Although conventional intraarterial angiography is still the gold standard to evaluate the location and severity of vessel stenosis, the risks of this catheter-based procedure are significant. Imaging methods, such as ultrasound, can be preferred. Magnetic resonance angiography has been shown to be comparable and even superior to ultrasound for evaluating vessel stenosis (Nonent et al, 2004). In addition to TOF-MRA where blood flow is visualized noninvasively with short TR images, contrast-enhanced MRA (CE-MRA) is also routinely used. In CE-MRA, a Gadolinium bolus is injected intravenously and filling of the vessel lumen is recorded using T1-weighted images. Disadvantages of TOF-MRA when compared with CE-MRA are significantly longer scan times and less sensitivity to low flow, which potentially overestimates the degree of stenosis (Nederkoorn et al, 2003). Despite the recent suggestion that there is no greater benefit of CE-MRA (Babiarz et al, 2009), a meta-analysis has revealed that CE-MRA is slightly superior to TOF (Debrey et al, 2008). Another interesting application of MRA in stroke is its use to identify several characteristics of the atherosclerotic build up that could provide indications of plaque vulnerability (reviewed in Saam et al, 2007). For example, TOF was able to delineate the boundaries of the inflammatory fibrous cap rupture in atherosclerotic patients (Mitsumori et al, 2003), as well as fresh intraplaque hemorrhage (Yim et al, 2008). In addition, contrast agents, specifically ultrasmall superparamagnetic iron oxide nanoparticles, have been shown to accumulate inside the macrophages contained in the fibrous cap (Kooi et al, 2003), which could also enhance predictability of rupture potential.

Magnetic resonance angiography in the experimental setting can be used in much the same manner as the clinic, to determine thrombus location and recanalization, only when an embolic model is used (Hilger et al, 2002). However, the resolution is currently lacking to obtain images of smaller arteries or main stem branches, which makes implementation of MRA for examination of endothelial disease difficult. The most common model of MCAO in the rodent is the intraluminal filament technique, and model failure is a potential pitfall of this technique (Dittmar et al, 2005). Magnetic resonance angiography has been used to identify and exclude these animals earlier (Gerriets et al, 2004). Although use of MRA is limited in the experimental setting, development of new contrast agents for examination of atherosclerotic plaques can be tested easily.

Relaxometry

The susceptibility effects produced by iron in the blood appear as hypointensities in gradient echo images. Therefore, T₂*-weighted images are used to identify ICH and or subarachnoid hemorrhage. It is generally accepted that CT is more accurate for ICH detection acutely (Warlow et al, 2003). However another study found that the two modalities were equivalent and that MRI was even slightly better (Kidwell et al, 2004). Indeed, a recent review regarding acute stroke imaging recommendations assessed the quality of articles based on level of evidence and suggested that the assumption that CT is more accurate for ICH detection than MR is based on a low level of evidence (Latchaw et al, 2009).

It has also been suggested that T₂*-weighted MRI could be used to predict which patients might exhibit secondary ICH (SICH) after an ischemic stroke (Nighoghossian et al, 2002). Preexisting hypointensities in T₂*-weighted images are often classified as cerebral microbleeds, and regardless of their age could represent increased risk of SICH. As mentioned previously, these patients are often excluded from rtPA treatment, though the prognosis of SICH is not necessarily poor when compared with the potential impact of the initial ischemic event (Derex et al, 2004; von Kummer, 2002). Furthermore, recent evidence suggests that in fact these patients should not be excluded from rtPA treatment. The Bleeding Risk Analysis in Stroke by T₂*-weighted Imaging before thromboLysis study revealed no increased risk of SICH from thrombolysis (Fiehler et al, 2007). In a recent study, fluid attenuation inversion recovery images were able to delineate focal regions of hyperintensity before thrombolysis that were highly correlated with increased risk of SICH (Cho et al, 2008) and could thus be used as an attractive SICH predictor.

In experimental animal research, gradient echo imaging is the most common technique for reliable detection of ICH (Neumann-Haefelin et al, 2001). However, reproducibility of images from day to day represents a major problem with this technique because of the difficulties associated with shimming across the small rodent brain. Another application for T₂*-weighted images is the detection of susceptibility agents such as contrast agents. Systemic intravenous administration of ultrasmall superparamagnetic iron oxide nanoparticles for phagocytosis by activated blood-borne macrophages as a method to image the peripheral inflammatory response after stroke is one such application (Rausch et al, 2002; Wiart et al, 2007). However, evidence indicates this technique may not be so robust (Desestret et al, 2009; Henning et al, 2009), and more variability has been observed in the clinical setting (Cho et al, 2007; Nighoghossian et al, 2007; Saleh et al, 2007). Therefore, albeit offering interesting insights into the poststroke inflammatory reaction, the current potential of these techniques for stroke outcome prediction is poor.

Diffusion-Weighted Imaging

Many ischemic lesions are difficult to detect within 3 h using CT (Roberts et al, 2002), which has caused DWI to become the mainstay of acute stroke imaging (reviewed in Latchaw et al, 2009; Masdeu et al, 2006). Diffusion weighted imaging measures random mobility of water (protons) in tissue. Opposing magnetic field gradients first dephase and then rephase the proton spins. If no net movement has occurred, the signal is attenuated. However, if diffusion is restricted, for example, because of intercompartmental water shift produced by cytotoxic edema during acute stroke, the corresponding diffusion signal is hyperintense, and the quantitative apparent diffusion coefficient (ADC) values (mm²/sec) decrease. Apparent diffusion coefficient maps more clearly discriminate cytotoxic edema from existing pathologic entities produced by the T₂-shine-through effect that can be observed in the DW images (Detre et al, 1994). In general, ADC values do not change much until CBF drops below 20 mL/100 g per min. Subsequently, the most severe ADC reductions are found in the center of the perfusion deficit, indicating that specific ADC values are able to discriminate between infarct or necrotic tissues, and thus predict tissue outcome (Kraemer et al, 2005; Thomalla et al, 2003). When regions of interest were drawn around the initial DWI abnormality (core) and again around the hyperintense T₂ region (final infarct size), both regions, as well as the difference between the two (tissue at risk), showed different ADC values: core, 0.56 ± 0.11; tissue at risk, 0.71 ± 0.11; and final infarct, 0.63 ± 0.11 × 10⁻³ mm²/sec (Na et al, 2004). The most severe ADC decreases (10⁻³ 0.45 to 0.7 10⁻³ mm²/sec) are correlated with low cerebral metabolic rates of oxygen (CMRO₂) (0.4 to 0.5 μmol/100 mL per min), which is consistent with irreversible tissue damage (Guadagno et al, 2006). However, ADC values become much more variable in tissue with CMRO₂ levels that could be associated with either penumbra or benign oligemia (Guadagno et al, 2006). Furthermore, there have been a few reports where ischemic lesions were undetected with DWI (Lefkowitz et al, 1999; Wang et al, 1999), or that severe ADC decreases normalized, depending on the duration and severity of ischemia (Rother et al, 2002). Therefore, the ADC value of a voxel alone is not always sufficient to predict its fate. Recent automated postprocessing methods have tried to overcome this problem by incorporating regional ADC measures and local shape regularity constraints (Rosso et al, 2009). Lesion size estimated by DWI is often used to predict outcome as several studies have observed correlations with functional outcome scales (Barrett et al, 2009; Johnston et al, 2009), though it should be pointed out that a few studies have failed to find a correlation (Hand et al, 2006; Wardlaw et al, 2002).

As is the case in the clinic, ADC abnormalities are preferred for estimation of infarct size in animal research, and manual delineation showed a better correlation with 2,3,5-triphenyltetra-zolium chloride sections than threshold based estimations (Bratane et al, 2009). Nevertheless, several different thresholds have been used to correlate infarct size with histologic measurements. Apparent diffusion coefficient volumes, when expressed as threshold of 77% of control values, were highly correlated with measurements of reduced adenosine triphosphate and glucose consumption (breakdown of energy metabolism). Volumes determined with a threshold of 86% of control values were correlated with measurements of tissue acidosis 24 h later (Olah et al, 2001). An ADC decrease of 33% when compared with the contralateral side was also highly correlated with hemispheric lesion volume at 3 h after MCAO (Kazemi et al, 2004). Another group used semiautomated software to delineate the lesion based on a combination of ADC and T₂-weighted abnormalities at various time points. Infarct size from hematoxylin–eosin sections was highly correlated with the measurements starting around 16 h after MCAO (Jacobs et al, 2000). If reperfusion occurs, the region of ADC abnormality will return to normal or near-normal values, and subsequent expansion in the subacute stages is variable (Li et al, 2000). The eventual extent of the ADC region by 24 h is highly correlated with occlusion duration (Neumann-Haefelin et al, 2000) and several groups have shown with histology that the signal is not solely confined to the neuronal population (Liu et al, 2001; Ringer et al, 2001). A recent review on the potential of DWI to predict infarct size accurately in experimental animal research indicated that there were only 13 reports that achieved quality scores sufficient to draw conclusions from. In general, manual delineation of lesion size from DWI was a better indicator of neuronal damage than lesions defined by using quantitative ADC thresholds (Rivers and Wardlaw, 2005). This implies that although quantitative ADC maps are crucial to diagnose acute ischemic damage unambiguously, ADC-defined thresholds may be too dynamic in the course of the disease to yield a robust outcome predictor.

Perfusion-Weighted Imaging

Perfusion-weighted imaging is of particular importance in stroke, as the drop in CBF (usually specified in mL/100 g per min) is one of the first in the cascade of events that ultimately result in brain damage. The extent, severity, and duration of the misery perfusion are a major determinant of outcome. In addition to confirming the diagnosis of stroke and indicating reperfusion, it has been shown that areas with severely compromised perfusion are more likely to undergo infarction, which makes PWI an interesting outcome prediction parameter (Butcher et al, 2003). When time of symptom onset is not certain, a persistent perfusion deficit on PWI can help stratify patients for therapy. Induced hypertension to avoid a remittance of symptoms because of low perfusion pressure after transient ischemia is also typically guided by PWI.

The most common clinical technique for PWI is dynamic susceptibility contrast (DSC) bolus tracking, which relies on intravenous administration of a contrast agent. The corresponding signal in the blood vessels, and surrounding parenchyma, is subsequently reduced (Villringer et al, 1988) and signal change over time can be used to calculate CBF, cerebral blood volume, and the average time required for any given particle of tracer to pass through the tissue after an ideal bolus injection, mean transit time (Barbier et al, 2001; Calamante et al, 1999; Ostergaard, 2005). Compared with the ‘gold standard’ of positron emission tomography (PET) imaging, DSC-derived CBF values have large standard deviations and tend to overestimate the hypoperfused tissue in stroke patients (Zaro-Weber et al, 2009). An inherent problem with DSC methods is that perfusion quantification algorithms rely on determining an arterial input function, which incorporates the concentration of the tracer over time in a voxel within a major artery, usually the middle cerebral artery. The input into this vessel, however, does not always resemble arterial input into the brain tissue, which can result in large and unsystematic errors (Calamante et al, 2002). In a recent comparison of different postprocessing algorithms and 10 different parameters of perfusion derived from bolus tracking it could be shown that (1) the choice of the parameter critically determines the ability to predict final infarct size and that (2) simple composite parameters such as the time-to-peak or first moment, resembling the arrival time of contrast in the voxel, might be superior to more sophisticated parameters that involve deconvolution of the arterial input function. A prolongation of first moment of 3.5 secs predicted infarction with a 75% sensitivity and 78% specificity (Christensen et al, 2009). Notably, MRI prediction was better in patients without reperfusion, indicating that, probably because of interindividual variance, perfusion thresholds might be even more difficult to determine on the verge of recanalization. In a different study, DSC perfusion maps were predictive of favorable clinical outcome to rtPA treatment when increasing the threshold for the delay of the time-to-peak residue function (T_max) (Olivot et al, 2009).

Recently, a noninvasive alternative has become popular in preclinical research, arterial spin labeling (ASL) (Detre et al, 1994; Williams et al, 1992). Pulsed ASL produces contrast by nonselectively, and then selectively, inverting endogenous protons. The resulting signal difference is proportional to the amount of inflowing protons, or CBF. Magnetically labeling blood means this technique is more robust in situations of blood–brain barrier disruption (Calamante et al, 2002). However, quantification can be difficult as assumptions of the quantification algorithms, such as arterial transit time, are difficult to predict in cerebrovascular disease states (Wegener et al, 2007). As the method is still fairly new and not yet implemented on many clinical scanners, data are lacking to test the predictive value of ASL-PWI in stroke patients. Regardless, promising novel methods, such as velocity-selective ASL (tagging blood based on velocity rather than location) (Wong, 2007) and arterial territory mapping (Hendrikse et al, 2009; van Laar et al, 2008) are promising and currently receiving a great deal of attention, as these methods may predict if a certain vessel stenosis is really of relevance for cerebral perfusion in the individual or if collateral blood supply is compensating sufficiently.

In rodent models of stroke, PWI has not been frequently performed, in part because it is hard to implement because of signal-to-noise constraints. In addition to DSC-based techniques, ASL approaches have been recently introduced to small animal stroke imaging (Leithner et al, 2008; Wegener et al, 2007). There has been less ambiguity as to the value of PWI in outcome prediction in animal models compared with the clinical setting, which is very likely explained by the homogeneity of vascular occlusions in animal models in contrast to patients (location, duration, clot composition and so on). Cerebral blood flow thresholds have been shown to be useful for infarct size prediction. Voxels with a CBF < 30 mL/100 g per min were very likely to be part of the ‘core’ and proceed to infarction despite reperfusion, if ADC values were reduced, too (Shen et al, 2003, 2004).

The Mismatch Concept

Of central importance to stroke outcome is the concept of tissue at risk (Figure 3), which was only touched on in previous sections. Essentially, the region of brain most deprived of CBF (< 12 mL/100 g per min) is thought to be irreversibly damaged and destined for necrosis (infarct), whereas the surrounding areas retain some degree of CBF (12 to 22 mL/100 g per min) and thus represent a combination of tissue that will survive (oligemia) or whose fate is undecided depending on restoration of CBF (penumbra). Many different descriptions and classifications of these regions exist, reviewed elsewhere (Paciaroni et al, 2009; Sharp et al, 2000). Imagingbased identification of these regions is of great importance for outcome prediction and much effort has been made in this respect in the past decade.

Figure 3

The penumbra. Cerebral blood flow (CBF) thresholds have been used to identify tissue that will exhibit irreversible damage (infarct core < 12 mL/100 g per min) and that could be salvageable (penumbra 12 to 22 mL/100 g per min) because some degree of metabolic activity remains. Theoretically, if CBF is not restored the core will gradually expand in the subacute stages as penumbral tissue dies. The magnetic resonance imaging (MRI)-defined diffusion/perfusion weighted imaging (DWI/PWI) ‘mismatch’ is the area of potential lesion growth. It is defined by the initial area of perfusion deficit (which usually includes the area of oligemia) minus the initial area with severe diffusion deficit (core). Growth of the core region can be variable (continuous or dashed arrows) depending on the defined DWI and CBF thresholds, reperfusion, and individual tissue resistance.

Initial observations in patients that the region of DWI was smaller than the region of PWI abnormality lead to the development of the idea that the DWI/PWI ‘mismatch’ could be used to identify tissue at risk (Baird et al, 1997; Neumann-Haefelin et al, 1999). A DWI/PWI mismatch is illustrated in Figure 4. A perfusion deficit encompassing 120% of the size of the DWI lesion is generally accepted as a relevant mismatch (Sims et al, 2009). If the mismatch resembles a correlate of the real penumbra, two important conclusions should be possible with the detection of a large MRI-defined mismatch: (1) infarct growth if reperfusion is not achieved and (2) a large area of salvageable tissue. The latter suggests that patients with a large mismatch should respond better to thrombolytic treatment with rtPA, which has been shown even beyond the 3 h time window (Beaulieu et al, 1999; Lorenz et al, 2006; Ostergaard, 2005). However, the selection of patients for thrombolysis based on an MRI-defined mismatch is controversial (Fiebach and Schellinger, 2009; Schabitz, 2009). Although two phase II trials (the diffusion and perfusion imaging evaluation for understanding stroke evolution (DEFUSE) and the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET)) have indicated that patients with a mismatch might respond better to thrombolytic therapy, the DIAS-2 study did not show any benefit in patients selected for thrombolysis based on the existence of a mismatch (Albers et al, 2006; Davis et al, 2008; Donnan et al, 2009; Hacke et al, 2009). Of note, the mismatch in DIAS-2 was defined as a PWI lesion volume >20% of the DWI lesion volume by visual inspection at each participating stroke center. In DEFUSE and EPITHET, the mismatch (PWI/DWI lesion volume >1.2 and PWI/DWI lesion volume ≥10 ml) was determined by volumetric analysis at a later time point and did not influence stratification of patients into treatment groups. Although a systematic review ascertained that there is insufficient evidence to either provide or withhold thrombolytic treatment based on identification of a mismatch region (Kane et al, 2007), this is expected to change with the implementation of standardized, quantitative MRI analysis tools for ‘ad hoc’ calculation of the mismatch before treatment.

Figure 4

Identification of the diffusion/perfusion weighted imaging (DWI/PWI) mismatch. Diffusion-weighted images (left) and perfusion-weighted images (middle) in an 80-year-old patient at 8 h after the onset of acute aphasia, left-sided sensorimotor hemiparesis, and hemianopsia. Note: the small hyperintense lesion in DWI compared with the large area of hypoperfusion in PWI. Magnetic resonance angiography (MRA) reveals proximal occlusion of the left middle cerebral artery (kindly provided by J. Fiebach, Department of Neurology, Charité Universitätsmedizin Berlin).

As is clear from the previous section, there are many different methods in which to quantify CBF and the choice of which also impact estimation of the mismatch region. As such, there is no consensus regarding the best method to define the mismatch, which represents a problem regarding translation of findings between studies (Bandera et al, 2006). Recent advancements in techniques to estimate metabolic activity such as MRI-based assessment of CMRO₂ are expected to contribute to this (Xu et al, 2009), as well as combined machines such as MR/PET (Beyer and Pichler, 2009). With this technology it would be possible to perform simultaneous measurements, such as the oxygen extraction fraction with PET together with DWI/PWI mismatch to achieve a more precise estimate of the penumbra. Although good agreement has been shown between the relative distributions of the MRI-derived mismatch and the PET-derived penumbra, the mismatch is still prone to errors (Takasawa et al, 2008). Reasons include technical challenges regarding quantification of perfusion-weighted MRI, the fact that the lesion on DWI may recover and that areas with benign oligemia are included into the MRI-defined mismatch definitions (Guadagno et al, 2004; Heiss et al, 2004; Sobesky et al, 2004, 2005). In a study where PET was conducted roughly 1 h after MRI assessment of CBF (using the DSC bolus-tracking technique) in patients with acute ischemic stroke, a CBF threshold of < 20 ml/100 g per min was found to best estimate hypoperfusion within the PET-derived penumbra (Zaro-Weber et al, 2009). The considerable interindividual variance, the influence of vessel disease, and the value of graded CBF ranges (e.g., 12 to 20 ml/100 g per min) for penumbra selection are areas of ongoing research in this field.

The concept of the mismatch has not been so extensively studied in animal stroke research. Mismatch regions have been reported in the acute stages of permanent MCAO, and in accordance with early clinical reports, the region of ADC abnormality gradually expands to encompass the region of perfusion deficit within the first 3 h (Bardutzky et al, 2007; Henninger et al, 2006; Meng et al, 2004). However, once CBF is restored in transient models, both DWI and PWI regions of abnormality are diminished and subsequent expansion is variable. In one study, core pixels were defined by a CBF decrease of more than 87% and an ADC decrease of more than 30%, whereas mismatch pixels were defined by a CBF decrease below and an ADC value above the defined thresholds (Bardutzky et al, 2007). Subsequent pixel fate was highly dependent on the duration of the MCAO. Durations of 35, 60, and 95 mins resulted in recovery of 46%, 28%, and 9% of the core pixels, respectively, whereas 85% of all mismatch pixels recovered regardless of occlusion duration. Again, quantification of these regions is highly dependent on the choices for thresholds, this can be further complicated by partial volume effects, which are present more frequently in high-resolution images (Ren et al, 2004). In addition, differences in the evolution of the mismatch region have also been reported to differ with experimental model (Henninger et al, 2006) and animal strain (Bardutzky et al, 2005), which are important considerations. As is the case with the clinic, alternative strategies may provide a more balanced perspective. For example, pH-weighted MRI applied to a DWI/PWI mismatch data set was able to identify regions that correspond to penumbra and benign oligemia (Sun et al, 2007). Combined PET/MRI (Judenhofer et al, 2008) and MRI/SPECT machines are increasingly used and also expected to make a contribution to a better characterization of the tissue at risk and tissue destined to undergo infarction in animal research.

Outlook

Magnetic resonance imaging can assist to predict the functional outcome of stroke patients. Several MRI parameters are correlated with a favorable outcome: (1) early recanalization on MRA, (2) small tissue defect on DWI, (3) small size and degree of perfusion deficit on PWI, (4) restored functional activity in peri-infarct areas on fMRI and intact descending pathways on DTI. However, the decision regarding whether a patient should receive thrombolysis solely based on MRI assessment remains problematic and controversial.

Many of the problems and open questions of stroke outcome prediction are similar in experimental animal research and in the clinic. However, the quality of preclinical research must be improved to make a better impact in the clinic. Low statistical power, flawed statistical interpretation, reproducibility, masking, randomization, quality control, and publication bias have all been suggested to contribute to the lack of effective translational stroke research (Dirnagl, 2006). Once preclinical knowledge is ready to be applied to patients, multicenter studies are the only way to reach sufficient numbers for relevant conclusions, at which point standardization of MR acquisition and analysis strategies is essential. In addition, more long-term measures are required for ultimate evaluation of attempts at outcome prediction. Nevertheless, the field of experimental neuroimaging with MRI is rapidly expanding. Improvements in hardware and sequences that decrease scan time while maintaining resolution will continue to impact the field. Post-processing strategies must evolve to these increasingly complicated data sets. It also seems clear that multimodal imaging strategies are necessary to develop more detailed patient profiles that can be used to predict outcome. Magnetic resonance imaging prediction of stroke outcome and treatment response will remain an area of exciting research and a realistic goal for the next decade.

Footnotes

The authors declare no conflict of interest.

References

Abo

Chen

Lai

Reese

Bjelke

(2001) Functional recovery after brain lesion—contralateral neuromodulation: an fMRI study. Neuroreport 12:1543–7

Albers

Thijs

Wechsler

Kemp

Schlaug

Skalabrin

Bammer

Kakuda

Lansberg

Shuaib

Coplin

Hamilton

Moseley

Marks

(2006) Magnetic resonance imaging profiles predict clinical response to early reperfusion: the diffusion and perfusion imaging evaluation for understanding stroke evolution (DEFUSE) study. Ann Neurol 60:508–17

Ashioti

Beech

Lowe

Hesselink

Modo

Williams

(2007) Multi-modal characterisation of the neocortical clip model of focal cerebral ischaemia by MRI, behaviour and immunohistochemistry. Brain Res 1145:177–89

Babiarz

Romero

Murphy

Brobeck

Schaefer

Gonzalez

Lev

(2009) Contrast-enhanced MR angiography is not more accurate than unenhanced 2D time-of-flight MR angiography for determining > or = 70% internal carotid artery stenosis. AJNR Am J Neuroradiol 30:761–8

Baird

Benfield

Schlaug

Siewert

Lovblad

Edelman

Warach

(1997) Enlargement of human cerebral ischemic lesion volumes measured by diffusion-weighted magnetic resonance imaging. Ann Neurol 41:581–9

Bambauer

Johnston

Bambauer

Zivin

(2006) Reasons why few patients with acute stroke receive tissue plasminogen activator. Arch Neurol 63:661–4

Bandera

Botteri

Minelli

Sutton

Abrams

Latronico

(2006) Cerebral blood flow threshold of ischemic penumbra and infarct core in acute ischemic stroke: a systematic review. Stroke 37:1334–9

Banks

Marotta

(2007) Outcomes validity and reliability of the modified Rankin scale: implications for stroke clinical trials: a literature review and synthesis. Stroke 38:1091–6

Barbier

Silva

Kim

Koretsky

(2001) Perfusion imaging using dynamic arterial spin labeling (DASL). Magn Reson Med 45:1021–9

10.

Bardutzky

Shen

Henninger

Bouley

Duong

Fisher

(2005) Differences in ischemic lesion evolution in different rat strains using diffusion and perfusion imaging. Stroke 36:2000–5

11.

Bardutzky

Shen

Henninger

Schwab

Duong

Fisher

(2007) Characterizing tissue fate after transient cerebral ischemia of varying duration using quantitative diffusion and perfusion imaging. Stroke 38:1336–44

12.

Barrett

Ding

Wagner

Kallmes

Johnston

(2009) Change in diffusion-weighted imaging infarct volume predicts neurologic outcome at 90 days: results of the Acute Stroke Accurate Prediction (ASAP) trial serial imaging substudy. Stroke 40:2422–7

13.

Barth

Jones

Schallert

(1990) Functional subdivisions of the rat somatic sensorimotor cortex. Behav Brain Res 39:73–95

14.

Basser

Mattiello

LeBihan

(1994) MR diffusion tensor spectroscopy and imaging. Biophys J 66:259–267

15.

Beaulieu

de Crespigny

Tong

Moseley

Albers

Marks

(1999) Longitudinal magnetic resonance imaging study of perfusion and diffusion in stroke: evolution of lesion volume and correlation with clinical outcome. Ann Neurol 46:568–78

16.

Bederson

Pitts

Tsuji

Nishimura

Davis

Bartkowski

(1986) Rat middle cerebral artery occlusion: evaluation of the model and development of a neurologic examination. Stroke 17:472–6

17.

Beyer

Pichler

(2009) A decade of combined imaging: from a PET attached to a CT to a PET inside an MR. Eur J Nucl Med Mol Imaging 36(Suppl 1):S1–2

18.

Bhagat

Hussain

Stobbe

Butcher

Emery

Shuaib

Siddiqui

Maheshwari

Al-Hussain

Beaulieu

(2008) Elevations of diffusion anisotropy are associated with hyper-acute stroke: a serial imaging study. Magn Reson Imaging 26:683–93

19.

Bratane

Bastan

Fisher

Bouley

Henninger

(2009) Ischemic lesion volume determination on diffusion weighted images vs. apparent diffusion coefficient maps. Brain Res 1279:182–8

20.

Buffon

Molko

Herve

Porcher

Denghien

Pappata

Le Bihan

Bousser

Chabriat

(2005) Longitudinal diffusion changes in cerebral hemispheres after MCA infarcts. J Cereb Blood Flow Metab 25:641–50

21.

Butcher

Parsons

Baird

Barber

Donnan

Desmond

Tress

Davis

(2003) Perfusion thresholds in acute stroke thrombolysis. Stroke 34:2159–64

22.

Butcher

Parsons

MacGregor

Barber

Chalk

Bladin

Levi

Kimber

Schultz

Fink

Tress

Donnan

Davis

(2005) Refining the perfusion–diffusion mismatch hypothesis. Stroke 36:1153–9

23.

Calamante

Thomas

Pell

Wiersma

Turner

(1999) Measuring cerebral blood flow using magnetic resonance imaging techniques. J Cereb Blood Flow Metab 19:701–35

24.

Calamante

Gadian

Connelly

(2002) Quantification of perfusion using bolus tracking magnetic resonance imaging in stroke: assumptions, limitations, and potential implications for clinical use. Stroke 33:1146–51

25.

Calautti

Baron

(2003) Functional neuroimaging studies of motor recovery after stroke in adults: a review. Stroke 34:1553–66

26.

Carey

Seitz

(2007) Functional neuroimaging in stroke recovery and neurorehabilitation: conceptual issues and perspectives. Int J Stroke 2:245–64

27.

Cho

Kim

Yun

Choi

Kim

Kwon

Lee

Kim

Suh

Kang

(2008) Focal fluid-attenuated inversion recovery hyperintensity within acute diffusion-weighted imaging lesions is associated with symptomatic intracerebral hemorrhage after thrombolysis. Stroke 39:3424–6

28.

Cho

Nighoghossian

Wiart

Desestret

Cakmak

Berthezene

Derex

Louis-Tisserand

Honnorat

Froment

Hermier

(2007) USPIO-enhanced MRI of neuroinflammation at the sub-acute stage of ischemic stroke: preliminary data. Cerebrovasc Dis 24:544–6

29.

Christensen

Mouridsen

Hjort

Karstoft

Thomalla

Rother

Fiehler

Kucinski

Ostergaard

(2009) Comparison of 10 perfusion MRI parameters in 97 sub-6-hour stroke patients using voxel-based receiver operating characteristics analysis. Stroke 40:2055–61

30.

Cocho

Belvis

Marti-Fabregas

Molina-Porcel

Diaz-Manera

Aleu

Pagonabarraga

Garcia-Bargo

Mauri

Marti-Vilalta

(2005) Reasons for exclusion from thrombolytic therapy following acute ischemic stroke. Neurology 64:719–20

31.

Cocho

Belvis

Marti-Fabregas

Bravo

Aleu

Pagonabarraga

Molina-Porcel

Diaz-Manera

San Roman

Martinez-Lage

Martinez

Moreno

Marti-Vilalta

(2006) Does thrombolysis benefit patients with lacunar syndrome? Eur Neurol 55:70–3

32.

Cramer

Bastings

(2000) Mapping clinically relevant plasticity after stroke. Neuropharmacology 39:842–51

33.

Davis

Lees

Albers

Diener

Markabi

Karlsson

Norris

(2000) Selfotel in acute ischemic stroke: possible neurotoxic effects of an NMDA antagonist. Stroke 31:347–54

34.

Davis

Donnan

Parsons

Levi

Butcher

Peeters

Barber

Bladin

De Silva

Byrnes

Chalk

Fink

Kimber

Schultz

Hand

Frayne

Hankey

Muir

Gerraty

Tress

Desmond

(2008) Effects of alteplase beyond 3 h after stroke in the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET): a placebo-controlled randomised trial. Lancet Neurol 7:299–309

35.

Debrey

Lynch

Lovblad

Wright

Janket

Baird

(2008) Diagnostic accuracy of magnetic resonance angiography for internal carotid artery disease: a systematic review and meta-analysis. Stroke 39:2237–48

36.

Derex

Nighoghossian

Hermier

Adeleine

Philippeau

Honnorat

Yilmaz

Dardel

Froment

Trouillas

(2004) Thrombolysis for ischemic stroke in patients with old microbleeds on pretreatment MRI. Cerebrovasc Dis 17:238–41

37.

Desestret

Brisset

Moucharrafie

Devillard

Nataf

Honnorat

Nighoghossian

Berthezene

Wiart

(2009) Early-stage investigations of ultrasmall superparamagnetic iron oxide-induced signal change after permanent middle cerebral artery occlusion in mice. Stroke 40:1834–41

38.

Detre

Zhang

Roberts

Silva

Williams

Grandis

Koretsky

Leigh

(1994) Tissue specific perfusion imaging using arterial spin labeling. NMR Biomed 7:75–82

39.

Diener

Cortens

Ford

Grotta

Hacke

Kaste

Koudstaal

Wessel

(2000) Lubeluzole in acute ischemic stroke treatment: a double-blind study with an 8-hour inclusion window comparing a 10-mg daily dose of lubeluzole with placebo. Stroke 31:2543–51

40.

Diener

Lees

Lyden

Grotta

Davalos

Davis

Shuaib

Ashwood

Wasiewski

Alderfer

Hardemark

Rodichok

(2008) NXY-059 for the treatment of acute stroke: pooled analysis of the SAINT I and II trials. Stroke 39:1751–8

41.

Dijkhuizen

Ren

Mandeville

Ozdag

Moskowitz

Rosen

Finklestein

(2001) Functional magnetic resonance imaging of reorganization in rat brain after stroke. Proc Natl Acad Sci USA 98:12766–71

42.

Dirnagl

(2006) Bench to bedside: the quest for quality in experimental stroke research. J Cereb Blood Flow Metab 26:1465–78

43.

Dittmar

Fehm

Vatankhah

Bogdahn

Schlachetzki

(2005) Adverse effects of the intraluminal filament model of middle cerebral artery occlusion. Stroke 36:530–2; author reply 532

44.

Donnan

Baron

Davis

(2009) Penumbral selection of patients for trials of acute stroke therapy. Lancet Neurol 8:261–9

45.

Farr

Carswell

Gsell

Macrae

(2007) Estrogen receptor beta agonist diarylpropiolnitrile (DPN) does not mediate neuroprotection in a rat model of permanent focal ischemia. Brain Res 1185:275–82

46.

Felberg

Okon

El-Mitwalli

Burgin

Grotta

Alexandrov

(2002) Early dramatic recovery during intravenous tissue plasminogen activator infusion: clinical pattern and outcome in acute middle cerebral artery stroke. Stroke 33:1301–7

47.

Fiebach

Schellinger

(2009) MR mismatch is useful for patient selection for thrombolysis: yes. Stroke 40:2906–7

48.

Fiehler

Albers

Boulanger

Derex

Gass

Hjort

Kim

Liebeskind

Neumann-Haefelin

Pedraza

Rother

Rothwell

Rovira

Schellinger

Trenkler

(2007) Bleeding Risk Analysis in Stroke Imaging before thromboLysis (BRASIL): pooled analysis of T2*-weighted magnetic resonance imaging data from 570 patients. Stroke 38:2738–44

49.

Garcia

Wagner

Liu

(1995) Neurological deficit and extent of neuronal necrosis attributable to middle cerebral artery occlusion in rats. Statistical validation. Stroke 26:627–34; discussion 35

50.

Gerriets

Stolz

Walberer

Muller

Rottger

Kluge

Kaps

Fisher

Bachmann

(2004) Complications and pitfalls in rat stroke models for middle cerebral artery occlusion: a comparison between the suture and the macrosphere model using magnetic resonance angiography. Stroke 35:2372–7

51.

Goldberg

. Stroke Trials Registry. Internet Stroke Center. www.strokecenter.org

52.

Granziera

D'Arceuil

Zai

Magistretti

Sorensen

de Crespigny

(2007) Long-term monitoring of post-stroke plasticity after transient cerebral ischemia in mice using in vivo and ex vivo diffusion tensor MRI. Open Neuroimag J 1:10–7

53.

Grefkes

Fink

(2009) Functional reorganization and neuromodulation. In: Sensorimotor Control of Grasping: Physiology and Pathophysiology ( Nowak

Hermsdörfer

, eds), Cambridge University Press: UK, 425–437

54.

Guadagno

Warburton

Aigbirhio

Smielewski

Fryer

Harding

Price

Gillard

Carpenter

Baron

(2004) Does the acute diffusion-weighted imaging lesion represent penumbra as well as core? A combined quantitative PET/MRI voxel-based study. J Cereb Blood Flow Metab 24:1249–54

55.

Guadagno

Jones

Fryer

Barret

Aigbirhio

Carpenter

Price

Gillard

Warburton

Baron

(2006) Local relationships between restricted water diffusion and oxygen consumption in the ischemic human brain. Stroke 37:1741–8

56.

Hacke

Kaste

Bluhmki

Brozman

Davalos

Guidetti

Larrue

Lees

Medeghri

Machnig

Schneider

von Kummer

Wahlgren

Toni

(2008) Thrombolysis with alteplase 3 to 4.5 h after acute ischemic stroke. N Engl J Med 359:1317–29

57.

Hacke

Furlan

Al-Rawi

Davalos

Fiebach

Gruber

Kaste

Lipka

Pedraza

Ringleb

Rowley

Schneider

Schwamm

Leal

Sohngen

Teal

Wilhelm-Ogunbiyi

Wintermark

Warach

(2009) Intravenous desmoteplase in patients with acute ischaemic stroke selected by MRI perfusion–diffusion weighted imaging or perfusion CT (DIAS-2): a prospective, randomised, double-blind, placebo-controlled study. Lancet Neurol 8:141–50

58.

Hand

Wardlaw

Rivers

Armitage

Bastin

Lindley

Dennis

(2006) MR diffusion-weighted imaging and outcome prediction after ischemic stroke. Neurology 66:1159–63

59.

Heiss

Sobesky

Smekal

Kracht

Lehnhardt

Thiel

Jacobs

Lackner

(2004) Probability of cortical infarction predicted by flumazenil binding and diffusion-weighted imaging signal intensity: a comparative positron emission tomography/magnetic resonance imaging study in early ischemic stroke. Stroke 35:1892–8

60.

Hendrikse

Petersen

Cheze

Chng

Venketasubramanian

Golay

(2009) Relation between cerebral perfusion territories and location of cerebral infarcts. Stroke 40:1617–22

61.

Henning

Ruetzler

Gaudinski

Latour

Hallenbeck

Warach

(2009) Feridex preloading permits tracking of CNS-resident macrophages after transient middle cerebral artery occlusion. J Cereb Blood Flow Metab 29:1229–39

62.

Henninger

Sicard

Schmidt

Bardutzky

Fisher

(2006) Comparison of ischemic lesion evolution in embolic versus mechanical middle cerebral artery occlusion in Sprague Dawley rats using diffusion and perfusion imaging. Stroke 37:1283–7

63.

Hilger

Niessen

Diedenhofen

Hossmann

Hoehn

(2002) Magnetic resonance angiography of thromboembolic stroke in rats: indicator of recanalization probability and tissue survival after recombinant tissue plasminogen activator treatment. J Cereb Blood Flow Metab 22:652–62

64.

Hsia

Sachdev

Tomlinson

Hamilton

Tong

(2003) Efficacy of IV tissue plasminogen activator in acute stroke: does stroke subtype really matter? Neurology 61:71–5

65.

Hwang

Seo

Lee

Park

Suh

(2008) Early neurological deterioration following intravenous recombinant tissue plasminogen activator therapy in patients with acute lacunar stroke. Cerebrovasc Dis 26:355–9

66.

Jacobs

Knight

Soltanian-Zadeh

Zheng

Goussev

Peck

Windham

Chopp

(2000) Unsupervised segmentation of multiparameter MRI in experimental cerebral ischemia with comparison to T2, diffusion, and ADC MRI parameters and histopathological validation. J Magn Reson Imaging 11:425–37

67.

Jiang

Zhang

Ding

Silver

Zhang

Meng

Pourabdillah-Nejed

Wang

Savant-Bhonsale

Bagher-Ebadian

Arbab

Vanguri

Ewing

Ledbetter

Chopp

(2006) MRI detects white matter reorganization after neural progenitor cell treatment of stroke. Neuroimage 32:1080–9

68.

Johnston

Barrett

Ding

Wagner

(2009) Clinical and imaging data at 5 days as a surrogate for 90-day outcome in ischemic stroke. Stroke 40:1332–3

69.

Jorgensen

Sperling

Nakayama

Raaschou

Olsen

(1994) Spontaneous reperfusion of cerebral infarcts in patients with acute stroke. Incidence, time course, and clinical outcome in the Copenhagen Stroke Study. Arch Neurol 51:865–73

70.

Judenhofer

Wehrl

Newport

Catana

Siegel

Becker

Thielscher

Kneilling

Lichy

Eichner

Klingel

Reischl

Widmaier

Rocken

Nutt

Machulla

Uludag

Cherry

Claussen

Pichler

(2008) Simultaneous PET-MRI: a new approach for functional and morphological imaging. Nat Med 14:459–65

71.

Kane

Sandercock

Wardlaw

(2007) Magnetic resonance perfusion diffusion mismatch and thrombolysis in acute ischaemic stroke: a systematic review of the evidence to date. J Neurol Neurosurg Psychiatry 78:485–91

72.

Kasner

(2006) Clinical interpretation and use of stroke scales. Lancet Neurol 5:603–12

73.

Kazemi

Silva

Fisher

Sotak

(2004) Investigation of techniques to quantify in vivo lesion volume based on comparison of water apparent diffusion coefficient (ADC) maps with histology in focal cerebral ischemia of rats. Magn Reson Imaging 22:653–9

74.

Kidwell

Chalela

Saver

Starkman

Hill

Demchuk

Butman

Patronas

Alger

Latour

Luby

Baird

Leary

Tremwel

Ovbiagele

Fredieu

Suzuki

Villablanca

Davis

Dunn

Todd

Ezzeddine

Haymore

Lynch

Davis

Warach

(2004) Comparison of MRI and CT for detection of acute intracerebral hemorrhage. JAMA 292:1823–30

75.

Kimura

Iguchi

Shibazaki

Aoki

Uemura

(2009) Early recanalization rate of major occluded brain arteries after intravenous tissue plasminogen activator therapy using serial magnetic resonance angiography studies. Eur Neurol 62:287–92

76.

Kleindorfer

Kissela

Schneider

Woo

Khoury

Miller

Alwell

Gebel

Szaflarski

Pancioli

Jauch

Moomaw

Shukla

Broderick

(2004) Eligibility for recombinant tissue plasminogen activator in acute ischemic stroke: a population-based study. Stroke 35:e27–9

77.

Kooi

Cappendijk

Cleutjens

Kessels

Kitslaar

Borgers

Frederik

Daemen

van Engelshoven

(2003) Accumulation of ultrasmall superparamagnetic particles of iron oxide in human atherosclerotic plaques can be detected by in vivo magnetic resonance imaging. Circulation 107:2453–8

78.

Kraemer

Thomalla

Soennichsen

Fiehler

Knab

Kucinski

Zeumer

Rother

(2005) Magnetic resonance imaging and clinical patterns of patients with ‘spectacular shrinking deficit’ after acute middle cerebral artery stroke. Cerebrovasc Dis 20:285–90

79.

Kuker

Gaertner

Nagele

Dopfer

Schoning

Fiehler

Rothwell

Herrlinger

(2008) Vessel wall contrast enhancement: a diagnostic sign of cerebral vasculitis. Cerebrovasc Dis 26:23–9

80.

Latchaw

Alberts

Lev

Connors

Harbaugh

Higashida

Hobson

Kidwell

Koroshetz

Mathews

Villablanca

Warach

Walters

(2009) Recommendations for imaging of acute ischemic stroke. A scientific statement from the American Heart Association. Stroke 40:3646–78

81.

Lefkowitz

LaBenz

Nudo

Steg

Bertoni

(1999) Hyperacute ischemic stroke missed by diffusion-weighted imaging. AJNR Am J Neuroradiol 20:1871–5

82.

Leithner

Gertz

Schrock

Priller

Prass

Steinbrink

Villringer

Endres

Lindauer

Dirnagl

Royl

(2008) A flow sensitive alternating inversion recovery (FAIR)-MRI protocol to measure hemispheric cerebral blood flow in a mouse stroke model. Exp Neurol 210:118–27

83.

Silva

Liu

Helmer

Omae

Fenstermacher

Sotak

Fisher

(2000) Secondary decline in apparent diffusion coefficient and neurological outcomes after a short period of focal brain ischemia in rats. Ann Neurol 48:236–44

84.

Liu

Tatlisumak

Garcia

Sotak

Fisher

Fenstermacher

(2001) Regional variations in the apparent diffusion coefficient and the intracellular distribution of water in rat brain during acute focal ischemia. Stroke 32:1897–905

85.

Lorenz

Benner

Lopez

Zhu

Aronen

Karonen

Liu

Nuutinen

Sorensen

(2006) Effect of using local arterial input functions on cerebral blood flow estimation. J Magn Reson Imaging 24:57–65

86.

Mandeville

Marota

Kosofsky

Keltner

Weissleder

Rosen

Weisskoff

(1998) Dynamic functional imaging of relative cerebral blood volume during rat forepaw stimulation. Magn Reson Med 39:615–24

87.

Masdeu

Irimia

Asenbaum

Bogousslavsky

Brainin

Chabriat

Herholz

Markus

Martinez-Vila

Niederkorn

Schellinger

Seitz

(2006) EFNS guideline on neuroimaging in acute stroke. Report of an EFNS task force. Eur J Neurol 13:1271–83

88.

Meng

Fisher

Shen

Sotak

Duong

(2004) Characterizing the diffusion/perfusion mismatch in experimental focal cerebral ischemia. Ann Neurol 55:207–12

89.

Mitsumori

Hatsukami

Ferguson

Kerwin

Cai

Yuan

(2003) In vivo accuracy of multisequence MR imaging for identifying unstable fibrous caps in advanced human carotid plaques. J Magn Reson Imaging 17:410–20

90.

Moller

Frandsen

Andersen

Gjedde

Vestergaard-Poulsen

Ostergaard

(2007) Dynamic changes in corticospinal tracts after stroke detected by fibretracking. J Neurol Neurosurg Psychiatry 78:587–92

91.

Montoya

Campbell-Hope

Pemberton

Dunnett

(1991) The ‘staircase test’: a measure of independent forelimb reaching and grasping abilities in rats. J Neurosci Methods 36:219–28

92.

Morita

Harada

Uno

Furutani

Nishitani

(2006) Change of diffusion anisotropy in patients with acute cerebral infarction using statistical parametric analysis. Radiat Med 24:253–9

93.

Thijs

Albers

Moseley

Marks

(2004) Diffusion-weighted MR imaging in acute ischemia: value of apparent diffusion coefficient and signal intensity thresholds in predicting tissue at risk and final infarct size. AJNR Am J Neuroradiol 25:1331–6

94.

National Institute of Neurological Disorders Stroke rt-PA Stroke Study Group (2005) Recombinant tissue plasminogen activator for minor strokes: the National Institute of Neurological Disorders and Stroke rt-PA Stroke Study experience. Ann Emerg Med 46:243–52

95.

Nederkoorn

Elgersma

van der Graaf

Eikelboom

Kappelle

Mali

(2003) Carotid artery stenosis: accuracy of contrast-enhanced MR angiography for diagnosis. Radiology 228:677–82

96.

Neumann-Haefelin

Wittsack

Wenserski

Siebler

Seitz

Modder

Freund

(1999) Diffusion- and perfusion-weighted MRI. The DWI/PWI mismatch region in acute stroke. Stroke 30:1591–7

97.

Neumann-Haefelin

Kastrup

de Crespigny

Yenari

Ringer

Sun

Moseley

(2000) Serial MRI after transient focal cerebral ischemia in rats: dynamics of tissue injury, blood–brain barrier damage, and edema formation. Stroke 31:1965–72; discussion 72–3

98.

Neumann-Haefelin

Kastrup

de Crespigny

Ringer

Sun

Yenari

Moseley

(2001) MRI of subacute hemorrhagic transformation in the rat suture occlusion model. Neuroreport 12:309–11

99.

Neumann-Haefelin

du Mesnil de Rochemont

Fiebach

Gass

Nolte

Kucinski

Rother

Siebler

Singer

Szabo

Villringer

Schellinger

(2004) Effect of incomplete (spontaneous and postthrombolytic) recanalization after middle cerebral artery occlusion: a magnetic resonance imaging study. Stroke 35:109–14

100.

Neumann

Jonsdottir

Mouridsen

Hjort

Gyldensted

Bizzi

Fiehler

Gasparotti

Gillard

Hermier

Kucinski

Larsson

Sorensen

Ostergaard

(2009) Interrater agreement for final infarct MRI lesion delineation. Stroke 40:3768–71

101.

Nighoghossian

Hermier

Adeleine

Blanc-Lasserre

Derex

Honnorat

Philippeau

Dugor

Froment

Trouillas

(2002) Old microbleeds are a potential risk factor for cerebral bleeding after ischemic stroke: a gradient-echo T2*-weighted brain MRI study. Stroke 33:735–42

102.

Nighoghossian

Wiart

Cakmak

Berthezene

Derex

Cho

Nemoz

Chapuis

Tisserand

Pialat

Trouillas

Froment

Hermier

(2007) Inflammatory response after ischemic stroke: a USPIO-enhanced MRI study in patients. Stroke 38:303–7

103.

Nonent

Serfaty

Nighoghossian

Rouhart

Derex

Rotaru

Chirossel

Guias

Heautot

Gouny

Langella

Buthion

Jars

Pachai

Veyret

Gauvrit

Lamure

Douek

(2004) Concordance rate differences of 3 noninvasive imaging techniques to measure carotid stenosis in clinical routine practice: results of the CARMEDAS multicenter study. Stroke 35:682–6

104.

Olah

Wecker

Hoehn

(2001) Relation of apparent diffusion coefficient changes and metabolic disturbances after 1 h of focal cerebral ischemia and at different reperfusion phases in rats. J Cereb Blood Flow Metab 21:430–9

105.

Olivot

Mlynash

Thijs

Kemp

Lansberg

Wechsler

Bammer

Marks

Albers

(2009) Optimal Tmax threshold for predicting penumbral tissue in acute stroke. Stroke 40:469–75

106.

Ostergaard

(2005) Principles of cerebral perfusion imaging by bolus tracking. J Magn Reson Imaging 22:710–7

107.

Ozsunar

Koseoglu

Huisman

Koroshetz

Sorensen

(2004) MRI measurements of water diffusion: impact of region of interest selection on ischemic quantification. Eur J Radiol 51:195–201

108.

Paciaroni

Caso

Agnelli

(2009) The concept of ischemic penumbra in acute stroke and therapeutic opportunities. Eur Neurol 61:321–30

109.

Palmer

Peeling

Corbett

Del Bigio

Hudzik

(2001) T2-weighted MRI correlates with long-term histopathology, neurology scores, and skilled motor behavior in a rat stroke model. Ann NY Acad Sci 939:283–96

110.

Pannek

Chalk

Finnigan

Rose

(2009) Dynamic corticospinal white matter connectivity changes during stroke recovery: a diffusion tensor probabilistic tractography study. J Magn Reson Imaging 29:529–36

111.

Rausch

Baumann

Neubacher

Rudin

(2002) In-vivo visualization of phagocytotic cells in rat brains after transient ischemia by USPIO. NMR Biomed 15:278–83

112.

Ren

Shen

Bardutzky

Fisher

Duong

(2004) Partial-volume effect on ischemic tissue-fate delineation using quantitative perfusion and diffusion imaging on a rat stroke model. Magn Reson Med 52:1328–35

113.

Ricci

Burdette

Elster

Reboussin

(1999) A comparison of fast spin-echo, fluid-attenuated inversion-recovery, and diffusion-weighted MR imaging in the first 10 days after cerebral infarction. AJNR Am J Neuroradiol 20:1535–42

114.

Ringer

Neumann-Haefelin

Sobel

Moseley

Yenari

(2001) Reversal of early diffusion-weighted magnetic resonance imaging abnormalities does not necessarily reflect tissue salvage in experimental cerebral ischemia. Stroke 32:2362–9

115.

Rivers

Wardlaw

(2005) What has diffusion imaging in animals told us about diffusion imaging in patients with ischaemic stroke? Cerebrovasc Dis 19:328–36

116.

Roberts

Dillon

Furlan

Wechsler

Rowley

Fischbein

Higashida

Kase

Schulz

Firszt

(2002) Computed tomographic findings in patients undergoing intra-arterial thrombolysis for acute ischemic stroke due to middle cerebral artery occlusion: results from the PROACT II trial. Stroke 33:1557–65

117.

Rosso

Hevia-Montiel

Deltour

Bardinet

Dormont

Crozier

Baillet

Samson

(2009) Prediction of infarct growth based on apparent diffusion coefficients: penumbral assessment without intravenous contrast material. Radiology 250:184–92

118.

Rother

Schellinger

Gass

Siebler

Villringer

Fiebach

Fiehler

Jansen

Kucinski

Schoder

Szabo

Junge-Hulsing

Hennerici

Zeumer

Sartor

Weiller

Hacke

(2002) Effect of intravenous thrombolysis on MRI parameters and functional outcome in acute stroke < 6 h. Stroke 33:2438–45

119.

Saam

Hatsukami

Takaya

Chu

Underhill

Kerwin

Cai

Ferguson

Yuan

(2007) The vulnerable, or high-risk, atherosclerotic plaque: noninvasive MR imaging for characterization and assessment. Radiology 244:64–77

120.

Saleh

Schroeter

Ringelstein

Hartung

Siebler

Modder

Jander

(2007) Iron oxide particle-enhanced MRI suggests variability of brain inflammation at early stages after ischemic stroke. Stroke 38:2733–7

121.

Schabitz

(2009) MR mismatch is useful for patient selection for thrombolysis: no. Stroke 40:2908–9

122.

Schallert

Fleming

Leasure

Tillerson

Bland

(2000) CNS plasticity and assessment of forelimb sensorimotor outcome in unilateral rat models of stroke, cortical ablation, parkinsonism and spinal cord injury. Neuropharmacology 39:777–87

123.

Schiemanck

Kwakkel

Post

Prevo

(2006) Predictive value of ischemic lesion volume assessed with magnetic resonance imaging for neurological deficits and functional outcome poststroke: a critical review of the literature. Neurorehabil Neural Repair 20:492–502

124.

Sharp

Tang

Millhorn

(2000) Multiple molecular penumbras after focal cerebral ischemia. J Cereb Blood Flow Metab 20:1011–32

125.

Shen

Meng

Fisher

Sotak

Duong

(2003) Pixel-by-pixel spatiotemporal progression of focal ischemia derived using quantitative perfusion and diffusion imaging. J Cereb Blood Flow Metab 23:1479–88

126.

Shen

Fisher

Sotak

Duong

(2004) Effects of reperfusion on ADC and CBF pixel-by-pixel dynamics in stroke: characterizing tissue fates using quantitative diffusion and perfusion imaging. J Cereb Blood Flow Metab 24:280–90

127.

Silva

Lee

Yang

Iadecola

Kim

(1999) Simultaneous blood oxygenation level-dependent and cerebral blood flow functional magnetic resonance imaging during forepaw stimulation in the rat. J Cereb Blood Flow Metab 19:871–9

128.

Sims

Gharai

Schaefer

Vangel

Rosenthal

Lev

Schwamm

(2009) ABC/2 for rapid clinical estimate of infarct, perfusion, and mismatch volumes. Neurology 72:2104–10

129.

Sobesky

Zaro Weber

Lehnhardt

Hesselmann

Thiel

Dohmen

Jacobs

Neveling

Heiss

(2004) Which time-to-peak threshold best identifies penumbral flow? A comparison of perfusion-weighted magnetic resonance imaging and positron emission tomography in acute ischemic stroke. Stroke 35:2843–7

130.

Sobesky

Zaro Weber

Lehnhardt

Hesselmann

Neveling

Jacobs

Heiss

(2005) Does the mismatch match the penumbra? Magnetic resonance imaging and positron emission tomography in early ischemic stroke. Stroke 36:980–5

131.

Stinear

Barber

Smale

Coxon

Fleming

Byblow

(2007) Functional potential in chronic stroke patients depends on corticospinal tract integrity. Brain 130:170–80

132.

Sulter

Steen

De Keyser

(1999) Use of the Barthel index and modified Rankin scale in acute stroke trials. Stroke 30:1538–41

133.

Sun

Zhou

Sun

Huang

van Zijl

(2007) Detection of the ischemic penumbra using pH-weighted MRI. J Cereb Blood Flow Metab 27:1129–36

134.

Takasawa

Jones

Guadagno

Christensen

Fryer

Harding

Gillard

Williams

Aigbirhio

Warburton

Ostergaard

Baron

(2008) How reliable is perfusion MR in acute stroke? Validation and determination of the penumbra threshold against quantitative PET. Stroke 39:870–7

135.

Thomalla

Kucinski

Schoder

Fiehler

Knab

Zeumer

Weiller

Rother

(2003) Prediction of malignant middle cerebral artery infarction by early perfusion- and diffusion-weighted magnetic resonance imaging. Stroke 34:1892–9

136.

Uchino

Alexandrov

Garami

El-Mitwalli

Morgenstern

Grotta

(2005) Safety and feasibility of a lower dose intravenous TPA therapy for ischemic stroke beyond the first three hours. Cerebrovasc Dis 19:260–6

137.

van der Zijden

van der Toorn

van der Marel

Dijkhuizen

(2008) Longitudinal in vivo MRI of alterations in perilesional tissue after transient ischemic stroke in rats. Exp Neurol 212:207–12

138.

van Laar

van der Grond

Hendrikse

(2008) Brain perfusion territory imaging: methods and clinical applications of selective arterial spin-labeling MR imaging. Radiology 246:354–64

139.

Villringer

Rosen

Belliveau

Ackerman

Lauffer

Buxton

Chao

Wedeen

Brady

(1988) Dynamic imaging with lanthanide chelates in normal brain: contrast due to magnetic susceptibility effects. Magn Reson Med 6:164–74

140.

von Kummer

(2002) Brain hemorrhage after thrombolysis: good or bad? Stroke 33:1446–7

141.

Wang

Barker

Wityk

Ulug

van Zijl

Beauchamp

Jr (1999) Diffusion-negative stroke: a report of two cases. AJNR Am J Neuroradiol 20:1876–80

142.

Warach

Pettigrew

Dashe

Pullicino

Lefkowitz

Sabounjian

Harnett

Schwiderski

Gammans

(2000) Effect of citicoline on ischemic lesions as measured by diffusion-weighted magnetic resonance imaging. Citicoline 010 Investigators. Ann Neurol 48:713–22

143.

Wardlaw

Keir

Bastin

Armitage

Rana

(2002) Is diffusion imaging appearance an independent predictor of outcome after ischemic stroke? Neurology 59:1381–7

144.

Warlow

Sudlow

Dennis

Wardlaw

Sandercock

(2003) Stroke. Lancet 362:1211–24

145.

Weber

Ramos-Cabrer

Justicia

Wiedermann

Strecker

Sprenger

Hoehn

(2008) Early prediction of functional recovery after experimental stroke: functional magnetic resonance imaging, electrophysiology, and behavioral testing in rats. J Neurosci 28:1022–9

146.

Wegener

Perthen

Wong

(2007) Quantification of rodent cerebral blood flow (CBF) in normal and high flow states using pulsed arterial spin labeling magnetic resonance imaging. J Magn Reson Imaging 26:855–62

147.

Whishaw

Pellis

Gorny

(1992) Skilled reaching in rats and humans: evidence for parallel development or homology. Behav Brain Res 47:59–70

148.

Wiart

Davoust

Pialat

Desestret

Moucharaffie

Cho

Mutin

Langlois

Beuf

Honnorat

Berthezene

(2007) MRI monitoring of neuroinflammation in mouse focal ischemia. Stroke 38:131–7

149.

Williams

Detre

Leigh

Koretsky

(1992) Magnetic resonance imaging of perfusion using spin inversion of arterial water. Proc Natl Acad Sci USA 89:212–6

150.

Wong

(2007) Vessel-encoded arterial spin-labeling using pseudocontinuous tagging. Magn Reson Med 58:1086–91

151.

(2009) Noninvasive quantification of whole-brain cerebral metabolic rate of oxygen (CMRO₂) by MRI. Magn Reson Med 62:141–8

152.

Yim

Choe

Kim

Jeon

Byun

Kim

(2008) High signal intensity halo around the carotid artery on maximum intensity projection images of time-of-flight MR angiography: a new sign for intraplaque hemorrhage. J Magn Reson Imaging 27:1341–6

153.

Schaefer

Rordorf

Gonzalez

(2002) Magnetic resonance angiography in acute stroke. Semin Roentgenol 37:212–8

154.

Zaro-Weber

Moeller-Hartmann

Heiss

Sobesky

(2009) The performance of MRI-based cerebral blood flow measurements in acute and subacute stroke compared with 15O-water positron emission tomography. Identification of penumbral flow. Stroke 40:2413–21

155.

Zelaya

Flood

Chalk

Wang

Doddrell

Strugnell

Benson

Ostergaard

Semple

Eagle

(1999) An evaluation of the time dependence of the anisotropy of the water diffusion tensor in acute human ischemia. Magn Reson Imaging 17:331–48

Use of Magnetic Resonance Imaging to Predict Outcome after Stroke: A Review of Experimental and Clinical Evidence

Abstract

Keywords

Introduction

Surrogates for outcome assessment

Imaging surrogates

Infarct Size

Diffusion Tensor Imaging

Functional MRI

Outcome predictors

Magnetic Resonance Angiography

Relaxometry

Diffusion-Weighted Imaging

Perfusion-Weighted Imaging

The Mismatch Concept

Outlook

Footnotes

References