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Challenging the Ischemic Core Concept in Acute Ischemic Stroke Imaging

Originally published 2020;51:3147–3155


Endovascular treatment is a highly effective therapy for acute ischemic stroke due to large vessel occlusion and has recently revolutionized stroke care. Oftentimes, ischemic core extent on baseline imaging is used to determine endovascular treatment-eligibility. There are, however, 3 fundamental issues with the core concept: First, computed tomography and magnetic resonance imaging, which are mostly used in the acute stroke setting, are not able to precisely determine whether and to what extent brain tissue is infarcted (core) or still viable, due to variability in tissue vulnerability, the phenomenon of selective neuronal loss and lack of a reliable gold standard. Second, treatment decision-making in acute stroke is multifactorial, and as such, the relative importance of single variables, including imaging factors, is reduced. Third, there are often discrepancies between core volume and clinical outcome. This review will address the uncertainty in terminology and proposes a direction towards more clarity. This theoretical exercise needs empirical data that clarify the definitions further and prove its value.

Historical Perspective of the Ischemic Core

The idea of defining an ischemic core threshold by the means of functional imaging dates back to the 1950s when first studies used a nitrous-oxide based method to show that neurological functions were disturbed when cerebral blood flow (CBF) dropped below 29 mL/100 g/min.1 In 1966, Jennet et al described in a carotid endarterectomy patient sample that hemiparesis consistently occurred with relative cortical CBF<30% compared with the baseline level, a threshold which is now commonly used in acute ischemic stroke (AIS) patients to distinguish between ischemic core and penumbra.2 Subsequently, more complex studies in primates were conducted that focused on the temporal and spatial component of infarction. Jones et al3 used a temporary middle cerebral artery occlusion model in macaques in which they showed that CBF thresholds for irreversible tissue damage depend on the duration of occlusion: tissue with a CBF below 18 mL/100 g/min accurately identified infarcted tissue when the vessel occlusion was permanent, while for an ischemia duration of 30 minutes, even tissue with CBF values below 5 mL/100 mg/min did not progress to infarction. Soon, it became obvious that ischemia tolerance also differs between tissue types. Marcoux et al4 showed that gray matter is more vulnerable to ischemia than white matter and coined the term differential neuronal vulnerability.4 Noninvasive positron emission tomography studies in humans were soon to follow in the 1980s and 1990s.5,6 Now, there are ample noninvasive experimental techniques for ischemic core imaging available, among them 15-O2 positron emission tomography, single-photon emission computed tomography, and Xenon CT. Today, magnetic resonance (MR) and computed tomography (CT) perfusion imaging are commonly used in clinical routine for estimation of ischemic core, outcome prediction, and treatment decision-making in the acute stroke setting. For example, the DEFUSE and DEFUSE 2 trials (Magnetic Resonance Imaging Profiles Predict Clinical Response to Early Reperfusion: The Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution) used MR perfusion and diffusion imaging, to show the impact of a target mismatch profile, that is, the presence of a penumbra/tissue at risk on treatment success and clinical outcome in AIS.7,8

Current Role of the Ischemic Core in Imaging and Treatment of AIS

AIS due to large vessel occlusion is a severe and life-threatening disease.9 Endovascular treatment (EVT) is a safe and effective treatment for AIS patients with large vessel occlusion, but it is currently restricted to patients with a small core on baseline imaging based on current guidelines.10,11 Ischemic core volume on baseline noncontrast CT (NCCT), CT perfusion (CTP), or diffusion-weighted magnetic resonance imaging (DWI) is now widely used as a selection criterion and has become a key decision driver in acute stroke treatment both in the early and late (beyond 6 hours after last known well) time window.12 The underlying assumption is that patients with large core volumes have less salvageable tissue and are thus unlikely to benefit from therapy since most parts of the ischemic brain tissue have already been irreversibly injured, that is, they are infarcted. In this paradigm, it is crucial to measure infarcted tissue as accurately and reliably as possible and to acknowledge the uncertainty in these measurements. Measuring infarct core alone does not capture the amount of salvageable tissue (ie, the penumbra volume): a large core volume does not necessarily imply that there is no salvageable tissue that could be rescued by reperfusion therapies. Herein, we review (1) the challenges and limitations in predicting tissue viability using current imaging tools, such as CT, CTP, and DWI-magnetic resonance imaging (MRI) and (2) propose terminology and directions for future research that may help clarify the above issue better. Of note, opinions expressed in this article are based on the clinical experience of the authors and may not always represent those of the broader stroke community.

The Challenge of Accurately Imaging Tissue Death

The Current Working Definition of Ischemic Core Is Ambiguous

Ischemic core refers to the early phase of AIS when tissue fate is not yet 100% determined on baseline imaging. In contrast, infarction is reserved for tissue with histologically confirmed necrosis, which is clearly visible on follow-up imaging (sharply delineated, frank hypodensity on NCCT, or decrease in apparent diffusion coefficient (ADC) values on DWI-MRI imaging, whereby in clinical routine, DWI hyperintensity [rather than quantitative ADC information] is often used to visually assess the extent of the ischemic core). Whether and to what extent baseline ischemic core turns into infarction can only be determined retrospectively. Physicians define core either as (1) brain tissue that is already infarcted at the time of evaluation or (2) tissue that, even if still potentially viable at the time of evaluation, is invariably destined to become infarcted regardless of treatment.

Even brain tissue with CBF as low as 5 to 15 mL/100 g/min can regain function, if CBF is augmented within 30 minutes,3,13 that is, predicting cell death in this tissue requires repeated measurements of CBF over a period of at least 30 minutes. In the fast-paced world of acute clinical practice only one-time measurements are feasible, and they cannot answer the question whether the tissue of interest is already infarcted or potentially salvageable, particularly in cases in which very fast reperfusion is possible. What we currently call core on early CT or MRI imaging is not actually infarcted tissue but rather a probabilistic estimate of tissue that is highly likely to become infarcted, if fast reperfusion does not occur.

The Transition From Severe Ischemia to Tissue Death Is Difficult to Foresee

The transition from ischemic core at baseline imaging (ie, areas of severe ischemia) to actual infarction is nonlinear and complex, not sharp, and clearly demarcated. The chronological progression to infarction is different for different cell types (neurons are already severely damaged at a time and place where astrocytes are only minimally injured14), and it is variable both in time and space. Between central fully infarcted and peripheral fully spared ischemic regions there is a transition zone with incomplete infarction characterized by neuronal dropout but with preservation of other tissue components.15 Tolerance to ischemia varies by tissue and cell type,16 ischemia depth and duration,17 and patient factors such as age,18 preexisting systemic disease, such as diabetes mellitus19 and preexisting brain injury such as leukoaraiosis.20 These multifactorial, complex relationships are summated in what is observed on brain imaging and make exact distinctions between infarcted and noninfarcted tissue in the early stage impossible. It would be highly desirable to develop and refine imaging methods that can more accurately differentiate completed infarcts from incomplete infarction.

There Is No Clinically Available Gold Standard for Ischemic Core Imaging

Increased signal intensity on DWI can be partially reversible, particularly in the early time window,21 as DWI hyperintensity is observed when the CBF falls to 20 to 30 mL/100 g×min, which is far above Astrup’s and Jones’s CBF threshold of irreversible injury.3,22 What is described as the ischemic region on DWI, in fact, contains voxels with a wide range of ADC values on ADC maps. The more severe the decline in CBF, the lower the ADC value on these maps.23 The final infarct volume on follow-up imaging is considered the reference-standard for ischemic core measurements. However, imaging obtained at 24±12 hours may be too early, as infarct growth can continue beyond 24 hours.24 Imaging obtained at 5d±2 is often confounded by vasogenic edema. Follow-up NCCT may underestimate infarct size due to the fogging effect.25 In addition, infarction can be extremely patchy, making both human and automated infarct volume estimation difficult (Figure 1). Automated solutions for infarct volume quantification have been developed, and this may avoid human measurement errors, but it introduces software- and vendor-dependent variability. Even if imaging could precisely define the volume of infarction on follow-up imaging, the validation of core volumes would require immediate and complete recanalization, as has been done in animal MRI experiments.23 Partial recanalization, which is more frequent in clinical stroke, renders retrospective validation of core measurements impossible. Indeed, some patients show a reversible core due to early and complete reperfusion (Figure 2).

Figure 1.

Figure 1. Exemplary diffusion-weighted magnetic resonance imaging (MRI) sequences of 2 acute ischemic stroke patients. Homogeneous infarct pattern (left) in which both gray and white matter are completely affected vs patchy cortical/white matter sparing infarct pattern (right). In the latter one, the patient’s National Institutes of Health Stroke Scale (NIHSS) at the time of the MRI was 3, despite the apparently extensive infarcts.

Figure 2.

Figure 2. Core reversibility on computed tomography (CT) perfusion and noncontrast CT.Top row: Noncontrast CT of a 62-y-old patient presenting 4 h after symptom onset with a severe right hemispheric syndrome (National Institutes of Health Stroke Scale [NIHSS] score 22) shows apparently extensive hypodensity and loss of gray-white matter differentiation in the right M4, M5, and M6 regions (red arrows in [A]). CT perfusion was obtained and postprocessed with different softwares. The thresholded map ([B] generated with MiSTAR, Apollo Medical Imaging Technology, Melbourne, Australia, core threshold: relative cerebral blood flow <30%, penumbra threshold: delay time 2.5 s) shows an apparently large core volume (red) and relatively little penumbra (green). The Tmax>16 s map (C) cerebral blood flow (CBF) map (D), cerebral blood volume (CBV) map ([E] Tmax, CBF, and CBV maps were generated with GE perfusion 4D, GE Healthcare, Milwaukee, WI) all show apparently large core volumes. However, the underlying M2 occlusion was swiftly and completely recanalized, and follow-up magnetic resonance imaging (MRI) after 24 h [F] shows exclusively cortical hyperintensity of the right M4, M5, and M6 regions with complete sparing of the white matter, which, on the initial noncontrast CT, seemed to be severely affected. The patient improved significantly, the NIHSS score at discharge was 5.

We Lack the Ability to Distinguish Between Pan-Necrosis and Incomplete Infarction

There are 2 distinct patterns of cell death in ischemic stroke, namely pan-necrosis (ie, necrosis involving all cell types: neurons, microglia, astroglia, and endothelial cells) and incomplete infarction.15 The former is what physicians commonly refer to as ischemic core on baseline imaging and infarct on follow-up imaging, while the latter term is often used for scattered areas of necrosis, with interposed areas of preserved tissue. Although the above-mentioned interpretation of imaging findings is commonly used, it is not clear whether it is entirely accurate. At a cellular level, selective death of single neurons can occur with preserved glial cells and extracellular matrix structures.26 Reliable imaging of incomplete infarction in the acute stroke setting on MRI or CT is currently not feasible, since it may appear isodense/isointense to normal brain tissue because current CT and MRI are subject to partial volume averaging, limited spatial and tissue resolution.15 It is desirable to develop practical and easy-to-implement imaging techniques that allow for reliable tissue viability assessment, and particularly detection of incomplete infarction, in the acute stroke setting.

The Ischemic Core on Different Imaging Modalities

Ischemic Core on Noncontrast CT

NCCT measures tissue density. Brain tissue experiencing severe ischemia appears hypodense on NCCT, because of increased water content due to ionic edema, a surrogate for deep ischemia.27 These hypodense areas are called core on baseline NCCT images, but they are potentially reversible, especially in the early time window.28 A semiquantitative way to report changes on NCCT is the Alberta Stroke Program Early CT Score (ASPECTS,, which putatively distinguishes between alive and infarcted tissue (core). An ASPECTS region is considered to be abnormal when it is hypodense, but the decrease in density on CT follows a continuous rather than a dichotomous distribution (Figure 3) and is influenced by vasogenic edema, partial volume averaging, and ischemia duration.28,29 Furthermore, assessment of hypodensity on NCCT is subject to interrater variability and external factors such as window settings and room lighting. First, machine learning based attempts to detect early infarction on NCCT (automated ASPECTS) show promising results but are confounded by the imperfect gold standard (DWI-MRI in most studies) that they use as ground truth.30

Figure 3.

Figure 3. Continuum of hypodensity on noncontrast computed tomography (NCCT). In A, there is only mild hypodensity of the caudate and lentiform nucleus, while in (B), the hypodensity is patchy and more conspicuous. In C, there is frank hypodensity of the caudate and lentiform nucleus as well as the insula and M1 region. These qualitative density differences are neither reflected in the Alberta Stroke Program Early CT Score (ASPECTS) nor in core volume.

Ischemic Core on Perfusion Imaging

CTP measures blood flow rather than the consequences of ischemia in tissue and tries to identify regions of severe ischemic stress by applying thresholds for either cerebral blood volume or relative CBF. A brain tissue slab of 8 to 16 cm is continuously scanned over 45 to 90 seconds after contrast injection. Cerebral blood volume, CBF, time-to-peak, and mean-transit-time are then calculated based on tissue-enhancement curves and displayed as color-coded thresholded maps, which have largely replaced qualitative eyeball techniques, to estimate CTP-based ischemic core volume.31 Ischemic core has been operationally defined as severely decreased cerebral blood volume or relative cerebral blood flow.32 A variety of ischemic core and penumbra thresholds are currently in use. A few of these thresholds and criteria have been successfully used for imaging selection in recent endovascular trials.12,33–36 Although automation has helped to reduce heterogeneity in application of these thresholds, differences in CTP-derived ischemic core volumes are substantial when using different software packages, ranging from 50 mL underestimation to >50 mL overestimation of core volumes compared with follow-up infarct volume.37 Applying a single universal CTP core threshold across all time points from stroke onset (as most software packages currently do) seems neither reliable nor reasonable, given the differences in patient and tissue characteristics. While some studies imply that certain CTP thresholds are able to quite accurately predict final infarct volume with little or no overestimation,38,39 others suggest that threshold-derived CTP-maps may substantially overestimate ischemic changes (ghost core), particularly in the early time window, potentially leading to denial of treatment in patients who might still benefit from it.40 Whether, how often and to what extent advanced imaging leads to overestimation of ischemic core in clinical routine and what impact this actually has on patient management is simply not well understood at the time being. This is supported by an analysis of the HERMES collaboration (Highly Effective Reperfusion Using Multiple Endovascular Devices), which showed that penumbral imaging in the 0 to 6 hour time window had prognostic value, but was not helpful in predicting treatment benefit.41 DWI-MRI, which is less frequently used for acute stroke imaging, is similarly vulnerable to this problem.

Ischemic Core on Diffusion-Weighted MRI

DWI-MRI measures cytotoxic edema, which occurs in ischemic brain cells at a CBF between 0 to 30/100 g/min and is manifested as a high DWI-signal.22 Cytotoxic edema can be visible on DWI-MRI within minutes after ischemia onset and is more conspicuous than NCCT signal changes. DWI-MRI has been considered the gold standard for ischemic core estimation. It does not, however, accurately differentiate irreversibly damaged ischemic tissue from salvageable tissue, since the smallest unit of change on a DWI-MRI is a voxel representing (on average) 10 μL, which in neocortex will contain roughly a million neurons with 10 000 associated synapses per neuron. Thus, when we consider that we view summated voxels, at a neuronal level, MR is not able to distinguish between pan-necrosis (cell death) versus selective neuronal loss.15 Depending on the speed and quality of reperfusion, regions affected by cytotoxic edema can evolve to full infarction, partial infarction, or normal tissue outcome, particularly if reperfusion occurs early on.42 Moreover, in areas with heterogeneous, patchy signal abnormalities, it is often impossible to determine which areas constitute the core (Figure 1).

Thus, the concept of core has uncertainty as it currently stands, because (1) there is no uniform definition of ischemic core, (2) standardized and validated quantitative measures of irreversibly injured tissue (core thresholds) are lacking, (3) a reliable gold standard is lacking to validate imaging parameters, and (4) ischemic core is not an adequate proxy for the burden of cell death. To address the prevailing uncertainty in determining exact tissue state while acknowledging its perfusion status, we propose to abandon the term ischemic core and to use the term severely ischemic tissue with uncertain viability (SIT-uv) in place of core for tissue that is severely ischemic but potentially, in part, still salvageable if early reperfusion is achieved. It is expected that in many patients, SIT-uv will eventually progress to infarction because fast and complete reperfusion cannot be achieved. The primary goal of introducing SIT-uv is to acknowledge the limitations of our current technology and understanding, and to encourage further research into the topic.

Potential Applications of SIT-uv to Clinical Decision-Making

In general, the larger the infarct on follow-up imaging, the worse the clinical outcome. This correlation is, however, only moderate.43 Many patients with large infarcts achieve good functional outcome while others with small infarcts do not (Figure 4). Recent studies show that reduced infarct volume explains only a small minority of the treatment effect of EVT43 (Figure 5). Eloquence of the ischemic brain region is an alternative explanation; as clinical outcome depends to some degree on infarct location. Furthermore, preliminary evidence from animal models suggests that the presence of selective neuronal loss might be associated with better outcomes compared with more severe neuronal loss.45 The ratio of gray versus white matter loss may also influence recovery and long-term outcomes, just as patient age, preexisting comorbidities, and prestroke functional status do.46 If all other variables (young age, severely disabling stroke with a proximal occlusion and onset few minutes ago) favor EVT, the importance of the extent of SIT-uv will likely be less and patients with large SIT-uv extent on baseline imaging may still benefit from EVT. This multidimensional nature of treatment decision-making is not adequately reflected in current treatment guidelines.47 An example of the interplay of prognostic and effect modifying variables, is provided in a multivariable decision model based on MR CLEAN (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) and IMS III (Interventional Management of Stroke) data. It includes among others age, sex, ASPECTS, collaterals, time from onset to make an estimate of expected treatment benefit.48 Five ongoing trials, namely, TESLA (Thrombectomy for Emergent Salvage of Large Anterior Circulation Ischemic Stroke; NCT03805308), TENSION (Efficacy and Safety of Thrombectomy in Stroke With Extended Lesion and Extended Time Window; NCT03094715), SELECT 2 (A Randomized Controlled Trial to Optimize Patient's Selection for Endovascular Treatment in Acute Ischemic Stroke; NCT03876457), and IN EXTREMIS and RESCUE-Japan LIMIT (Mechanical Retrieval and Recanalization of Stroke Clots Using Embolectomy; NCT03702413) are investigating if patients with low ASPECTS/large ischemic core may benefit from EVT. These trials will hopefully help to further clarify the relationship between baseline imaging changes and follow-up infarct volume, and their impact on treatment effect. Below, we discuss some imaging features that are potentially helpful when applying the concept of SIT-uv in clinical practice and propose a roadmap for future research in this context. Of note, the purpose of introducing this new term is primarily to encourage critical re-thinking of the ischemic core concept, rather than merely introducing a new term into the stroke imaging vocabulary.

Figure 4.

Figure 4. Follow-up infarct volume and clinical outcome in acute ischemic stroke patients. Some patients achieve good functional outcomes despite large follow-up infarct volumes (green box), while many others suffer from severe disability despite small infarct volumes (red box). mRS indicates modified Rankin Scale. Reproduced from Boers et al43 with permission. Copyright ©2019, BMJ Publishing Group Ltd.

Figure 5.

Figure 5. Follow-up infarct volume for patients treated with endovascular treatment (EVT; gray line) vs the control group (yellow line). Given a certain infarct volume, patients treated with EVT achieve better functional outcomes compared with those who were treated conservatively. This effect is particularly distinct for small infarct volumes and eventually disappears with larger infarct volumes. mRS indicates modified Rankin Scale. Reproduced from Boers et al44 with permission. Copyright ©2019, American Medical Association.

Research Questions to Be Answered in the Context of SIT-uv

Development of Accurate SIT-uv Thresholds Versus Threshold-Free Tissue Characterization Approaches

Tissue density on NCCT lies on a continuous scale. While in some cases, the degree of hypoattenuation is mild and hardly conspicuous, in others there is frank hypodensity (Figure 3). The same principle applies to tissue hyperintensity/ADC values on DWI-MRI and cerebral blood volume/CBF reduction on CTP. It is well-known that DWI and CTP-determined infarct core tissue is more likely to recover in the early time window,21,40 suggesting that SIT-uv thresholds are time-dependent. Other studies have shown that using tissue-specific thresholds for gray and white matter increases accuracy of core estimation, although the area under the curve still did not exceed 80%.49

Given the complexity of imaging, the importance of timing and tissue type, and the phenomenon of selective neuronal loss which further complicates assessment of tissue viability,15 threshold-free, probabilistic approaches rather than uniform fixed thresholds might be more capable of distinguishing SIT-uv from milder forms of ischemia.50 Automated tissue characterization could potentially eliminate inter-reader variability and extract signal patterns that might escape the human eye. Differences in technical acquisition parameters and postprocessing algorithms and the need for coregistration are potential challenges when automatizing tissue viability analysis and should be addressed in future studies.

Speed of Infarct Progression

Imaging is a single-time measurement, which at best, can provide us with an estimate of tissue ischemia at the timepoint of image acquisition. The time from imaging to reperfusion has to be kept in mind when assessing baseline imaging, that is, the time that is needed to transfer the patient from the CT-scanner to the angio-table, gain arterial access, navigate to the site of occlusion and retrieve the blood clot. During this time, brain tissue continues to progress towards infarction. Thus, the burden of cell death at the time of reperfusion will always be greater than what it was at the time when baseline imaging was obtained, particularly when reperfusion is delayed and in case of fast progressors. An ultra-fast progression rate would render EVT futile and only expose the patient to treatment-related harm. Slow infarct progression, however, indicates that the therapeutic window is wider. Patients with little evidence of ischemic changes on imaging who are presenting in the late time window usually fall into the category of slow progressors. Automated image analysis could potentially help to extract imaging features that determine infarct progression rate but are too subtle to be recognized by human readers, which would be crucial for clinical decision-making.


In summary, we are currently unable to accurately determine based on imaging whether tissue—both individual cells and neuronal pathway integrity—is already irreversibly damaged or not. Thus, a critical re-evaluation of the core concept as it is used in clinical practice seems necessary. When evaluating baseline imaging, we should think of severely ischemic tissue as tissue with uncertain viability at the time of imaging (SIT-uv) whose outcome will depend on some combination of the tissue damage already accrued at the time of baseline imaging, the speed and quality of reperfusion, and many other currently poorly understood factors, rather than core. We thereby acknowledge the limitations of current imaging techniques and the potential salvageability of the core tissue. Until we are able to accurately determine the extent of tissue death on imaging, we think that if there is any doubt about the extent or presence of irreversibly damaged tissue on baseline imaging, EVT should be offered.

Nonstandard Abbreviations and Acronyms


apparent diffusion coefficient


acute ischemic stroke


Alberta Stroke Program Early CT Score


cerebral blood flow


computed tomography


CT perfusion


diffusion-weighted imaging


endovascular treatment


magnetic resonance imaging


noncontrast head CT


severely ischemic tissue of uncertain viability


We thank Dr Astrup for his help. Drs Goyal and Ospel performed in drafting and critical revision of the article. The remaining authors participated in critical revision of the article.


For Sources of Funding and Disclosures, see page 3154.

Correspondence to; Mayank Goyal, MD, Departments of Radiology and Clinical Neurosciences, Foothills Medical Centre, University of Calgary, 1403 29th St NW, Calgary, AB T2N2T9, Canada. Email


  • 1. Finnerty FA, Witkin L, Fazekas JF. Cerebral hemodynamics during cerebral ischemia induced by acute hypotension.J Clin Invest. 1954; 33:1227–1232. doi: 10.1172/JCI102997CrossrefMedlineGoogle Scholar
  • 2. Jennett WB, Harper AM, Gillespie FC. Measurement of regional cerebral blood-flow during carotid ligation.Lancet. 1966; 2:1162–1163.MedlineGoogle Scholar
  • 3. Jones TH, Morawetz RB, Crowell RM, Marcoux FW, FitzGibbon SJ, DeGirolami U, Ojemann RG. Thresholds of focal cerebral ischemia in awake monkeys.J Neurosurg. 1981; 54:773–782. doi: 10.3171/jns.1981.54.6.0773CrossrefMedlineGoogle Scholar
  • 4. Marcoux FW, Morawetz RB, Crowell RM, DeGirolami U, Halsey JHDifferential regional vulnerability in transient focal cerebral ischemia.Stroke. 1982; 13:339–346. doi: 10.1161/01.str.13.3.339LinkGoogle Scholar
  • 5. Baron JC, Bousser MG, Comar D, Soussaline F, Castaigne P. Noninvasive tomographic study of cerebral blood flow and oxygen metabolism in vivo. Potentials, limitations, and clinical applications in cerebral ischemic disorders.Eur Neurol. 1981; 20:273–284. doi: 10.1159/000115247CrossrefMedlineGoogle Scholar
  • 6. Heiss WD, Huber M, Fink GR, Herholz K, Pietrzyk U, Wagner R, Wienhard K. Progressive derangement of periinfarct viable tissue in ischemic stroke.J Cereb Blood Flow Metab. 1992; 12:193–203. doi: 10.1038/jcbfm.1992.29CrossrefMedlineGoogle Scholar
  • 7. Albers GW, Thijs VN, Wechsler L, Kemp S, Schlaug G, Skalabrin E, Bammer R, Kakuda W, Lansberg MG, Shuaib A, et al; DEFUSE Investigators. Magnetic resonance imaging profiles predict clinical response to early reperfusion: the diffusion and perfusion imaging evaluation for understanding stroke evolution (DEFUSE) study.Ann Neurol. 2006; 60:508–517. doi: 10.1002/ana.20976CrossrefMedlineGoogle Scholar
  • 8. Lansberg MG, Straka M, Kemp S, Mlynash M, Wechsler LR, Jovin TG, Wilder MJ, Lutsep HL, Czartoski TJ, Bernstein RA, et al; DEFUSE 2 Study Investigators. MRI profile and response to endovascular reperfusion after stroke (DEFUSE 2): a prospective cohort study.Lancet Neurol. 2012; 11:860–867. doi: 10.1016/S1474-4422(12)70203-XCrossrefMedlineGoogle Scholar
  • 9. Saver JL, Goyal M, van der Lugt A, Menon BK, Majoie CB, Dippel DW, Campbell BC, Nogueira RG, Demchuk AM, Tomasello A, et al; HERMES Collaborators. Time to treatment with endovascular thrombectomy and outcomes from ischemic stroke: a meta-analysis.JAMA. 2016; 316:1279–1288. doi: 10.1001/jama.2016.13647CrossrefMedlineGoogle Scholar
  • 10. Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, Bambakidis NC, Becker K, Biller J, Brown M, Demaerschalk BM, Hoh B, et al; American Heart Association Stroke Council. 2018 Guidelines for the early management of patients with acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association.Stroke. 2018; 49:e46–e110. doi: 10.1161/STR.0000000000000158LinkGoogle Scholar
  • 11. Turc G, Bhogal P, Fischer U, Khatri P, Lobotesis K, Mazighi M, Schellinger PD, Toni D, de Vries J, White P, et al. European Stroke Organisation (ESO) - European Society for Minimally Invasive Neurological Therapy (ESMINT) guidelines on mechanical thrombectomy in acute ischemic stroke [published online February 26, 2019].J Neurointerv Surg. 2019;neurintsurg-2018-014569. doi: 10.1136/neurintsurg-2018-014569Google Scholar
  • 12. Albers GW, Marks MP, Kemp S, Christensen S, Tsai JP, Ortega-Gutierrez S, McTaggart RA, Torbey MT, Kim-Tenser M, Leslie-Mazwi T, et al; DEFUSE 3 Investigators. Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging.N Engl J Med. 2018; 378:708–718. doi: 10.1056/NEJMoa1713973CrossrefMedlineGoogle Scholar
  • 13. Heiss WD, Rosner G. Functional recovery of cortical neurons as related to degree and duration of ischemia.Ann Neurol. 1983; 14:294–301. doi: 10.1002/ana.410140307CrossrefMedlineGoogle Scholar
  • 14. Gürer G, Gursoy-Ozdemir Y, Erdemli E, Can A, Dalkara T. Astrocytes are more resistant to focal cerebral ischemia than neurons and die by a delayed necrosis.Brain Pathol. 2009; 19:630–641. doi: 10.1111/j.1750-3639.2008.00226.xCrossrefMedlineGoogle Scholar
  • 15. Garcia Julio H, Lassen Niels A, Weiller C, Sperling B, Nakagawara J. Ischemic stroke and incomplete infarction.Stroke. 1996; 27:761–765. doi: 10.1161/01.str.27.4.761Google Scholar
  • 16. Nagakane Y, Yamada K, Ohara T, Yoshikawa K, Kuriyama N, Takayasu N, Kasai T, Yuki N, Nishimura T, Mizuno T, et al. Preferred involvement of the basal ganglia after lenticulostriate infarction as a possible indicator of different gray and white matter vulnerability.Stroke. 2008; 39:494–496. doi: 10.1161/STROKEAHA.107.484337LinkGoogle Scholar
  • 17. Shen Q, Meng X, Fisher M, Sotak CH, Duong TQ. Pixel-by-pixel spatiotemporal progression of focal ischemia derived using quantitative perfusion and diffusion imaging.J Cereb Blood Flow Metab. 2003; 23:1479–1488. doi: 10.1097/01.WCB.0000100064.36077.03CrossrefMedlineGoogle Scholar
  • 18. Ay H, Koroshetz WJ, Vangel M, Benner T, Melinosky C, Zhu M, Menezes N, Lopez CJ, Sorensen AG. Conversion of ischemic brain tissue into infarction increases with age.Stroke. 2005; 36:2632–2636. doi: 10.1161/01.STR.0000189991.23918.01LinkGoogle Scholar
  • 19. Shukla V, Shakya AK, Perez-Pinzon MA, Dave KR. Cerebral ischemic damage in diabetes: an inflammatory perspective.J Neuroinflammation. 2017; 14:21. doi: 10.1186/s12974-016-0774-5CrossrefMedlineGoogle Scholar
  • 20. Ay H, Arsava EM, Rosand J, Furie KL, Singhal AB, Schaefer PW, Wu O, Gonzalez RG, Koroshetz WJ, Sorensen AG. Severity of leukoaraiosis and susceptibility to infarct growth in acute stroke.Stroke. 2008; 39:1409–1413. doi: 10.1161/STROKEAHA.107.501932LinkGoogle Scholar
  • 21. Labeyrie MA, Turc G, Hess A, Hervo P, Mas JL, Meder JF, Baron JC, Touzé E, Oppenheim C. Diffusion lesion reversal after thrombolysis: a MR correlate of early neurological improvement.Stroke. 2012; 43:2986–2991. doi: 10.1161/STROKEAHA.112.661009LinkGoogle Scholar
  • 22. Lin W, Lee JM, Lee YZ, Vo KD, Pilgram T, Hsu CY. Temporal relationship between apparent diffusion coefficient and absolute measurements of cerebral blood flow in acute stroke patients.Stroke. 2003; 34:64–70. doi: 10.1161/01.str.0000048151.28173.0dAbstractGoogle Scholar
  • 23. Shen Q, Fisher M, Sotak CH, Duong TQ. 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. 2004; 24:280–290. doi: 10.1097/01.WCB.0000110048.43905.E5CrossrefMedlineGoogle Scholar
  • 24. Pantano P, Caramia F, Bozzao L, Dieler C, von Kummer R. Delayed increase in infarct volume after cerebral ischemia: correlations with thrombolytic treatment and clinical outcome.Stroke. 1999; 30:502–507. doi: 10.1161/01.str.30.3.502LinkGoogle Scholar
  • 25. Chalela JA, Kasner SE. The fogging effect.Neurology. 2000; 55:315. doi: 10.1212/wnl.55.2.315Google Scholar
  • 26. Baron JC, Yamauchi H, Fujioka M, Endres M. Selective neuronal loss in ischemic stroke and cerebrovascular disease.J Cereb Blood Flow Metab. 2014; 34:2–18. doi: 10.1038/jcbfm.2013.188CrossrefMedlineGoogle Scholar
  • 27. von Kummer R, Dzialowski I. Imaging of cerebral ischemic edema and neuronal death.Neuroradiology. 2017; 59:545–553. doi: 10.1007/s00234-017-1847-6Google Scholar
  • 28. Bal S, Bhatia R, Menon BK, Shobha N, Puetz V, Dzialowski I, Modi J, Goyal M, Hill MD, Smith EE, et al. Time dependence of reliability of noncontrast computed tomography in comparison to computed tomography angiography source image in acute ischemic stroke.Int J Stroke. 2015; 10:55–60. doi: 10.1111/j.1747-4949.2012.00859.xCrossrefMedlineGoogle Scholar
  • 29. Gao J, Parsons MW, Kawano H, Levi CR, Evans TJ, Lin L, Bivard A. Visibility of CT early ischemic change is significantly associated with time from stroke onset to baseline scan beyond the first 3 hours of stroke onset.J Stroke. 2017; 19:340–346. doi: 10.5853/jos.2016.01424Google Scholar
  • 30. Qiu W, Kuang H, Teleg E, Ospel JM, Sohn SI, Almekhlafi M, Goyal M, Hill MD, Demchuk AM, Menon BK. Machine learning for detecting early infarction in acute stroke with non-contrast-enhanced CT.Radiology. 2020; 294:638–644. doi: 10.1148/radiol.2020191193Google Scholar
  • 31. Srinivasan A, Goyal M, Al Azri F, Lum C. State-of-the-art imaging of acute stroke.Radiographics. 2006; 26(suppl 1):S75–S95. doi: 10.1148/rg.26si065501CrossrefMedlineGoogle Scholar
  • 32. Lui YW, Tang ER, Allmendinger AM, Spektor V. Evaluation of CT perfusion in the setting of cerebral ischemia: patterns and pitfalls.AJNR Am J Neuroradiol. 2010; 31:1552–1563. doi: 10.3174/ajnr.A2026CrossrefMedlineGoogle Scholar
  • 33. Campbell BC, Mitchell PJ, Kleinig TJ, Dewey HM, Churilov L, Yassi N, Yan B, Dowling RJ, Parsons MW, Oxley TJ, et al; EXTEND-IA Investigators. Endovascular therapy for ischemic stroke with perfusion-imaging selection.N Engl J Med. 2015; 372:1009–1018. doi: 10.1056/NEJMoa1414792CrossrefMedlineGoogle Scholar
  • 34. Nogueira RG, Jadhav AP, Haussen DC, Bonafe A, Budzik RF, Bhuva P, Yavagal DR, Ribo M, Cognard C, Hanel RA, et al; DAWN Trial Investigators. Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct.N Engl J Med. 2018; 378:11–21. doi: 10.1056/NEJMoa1706442CrossrefMedlineGoogle Scholar
  • 35. Ma H, Campbell BCV, Parsons MW, Churilov L, Levi CR, Hsu C, Kleinig TJ, Wijeratne T, Curtze S, Dewey HM, et al; EXTEND Investigators. Thrombolysis guided by perfusion imaging up to 9 hours after onset of stroke.N Engl J Med. 2019; 380:1795–1803. doi: 10.1056/NEJMoa1813046CrossrefMedlineGoogle Scholar
  • 36. Saver JL, Goyal M, Diener HC; SWIFT PRIME Investigators. Stent-retriever thrombectomy for stroke.N Engl J Med. 2015; 373:1077. doi: 10.1056/NEJMc1508744MedlineGoogle Scholar
  • 37. Austein F, Riedel C, Kerby T, Meyne J, Binder A, Lindner T, Huhndorf M, Wodarg F, Jansen O. Comparison of perfusion CT software to predict the final infarct volume after thrombectomy.Stroke. 2016; 47:2311–2317. doi: 10.1161/STROKEAHA.116.013147LinkGoogle Scholar
  • 38. Albers GW, Goyal M, Jahan R, Bonafe A, Diener HC, Levy EI, Pereira VM, Cognard C, Cohen DJ, Hacke W, et al. Ischemic core and hypoperfusion volumes predict infarct size in SWIFT PRIME.Ann Neurol. 2016; 79:76–89. doi: 10.1002/ana.24543CrossrefMedlineGoogle Scholar
  • 39. Hoving JW, Marquering HA, Majoie CBLM, Yassi N, Sharma G, Liebeskind DS, van der Lugt A, Roos YB, van Zwam W, van Oostenbrugge RJ, et al. Volumetric and spatial accuracy of computed tomography perfusion estimated ischemic core volume in patients with acute ischemic stroke.Stroke. 2018; 49:2368–2375. doi: 10.1161/STROKEAHA.118.020846LinkGoogle Scholar
  • 40. Martins N, Aires A, Mendez B, Boned S, Rubiera M, Tomasello A, Coscojuela P, Hernandez D, Muchada M, Rodríguez-Luna D, et al. Ghost infarct core and admission computed tomography perfusion: redefining the role of neuroimaging in acute ischemic stroke.Interv Neurol. 2018; 7:513–521. doi: 10.1159/000490117Google Scholar
  • 41. Campbell BCV, Majoie CBLM, Albers GW, Menon BK, Yassi N, Sharma G, van Zwam WH, van Oostenbrugge RJ, Demchuk AM, Guillemin F, et al; HERMES Collaborators. Penumbral imaging and functional outcome in patients with anterior circulation ischaemic stroke treated with endovascular thrombectomy versus medical therapy: a meta-analysis of individual patient-level data.Lancet Neurol. 2019; 18:46–55. doi: 10.1016/S1474-4422(18)30314-4CrossrefMedlineGoogle Scholar
  • 42. Kidwell CS, Saver JL, Mattiello J, Starkman S, Vinuela F, Duckwiler G, Gobin YP, Jahan R, Vespa P, Kalafut M, et al. Thrombolytic reversal of acute human cerebral ischemic injury shown by diffusion/perfusion magnetic resonance imaging.Ann Neurol. 2000; 47:462–469.CrossrefMedlineGoogle Scholar
  • 43. Boers AMM, Jansen IGH, Beenen LFM, Devlin TG, San Roman L, Heo JH, Ribó M, Brown S, Almekhlafi MA, Liebeskind DS, et al. Association of follow-up infarct volume with functional outcome in acute ischemic stroke: a pooled analysis of seven randomized trials.J Neurointerv Surg. 2018; 10:1137–1142. doi: 10.1136/neurintsurg-2017-013724Google Scholar
  • 44. Boers AMM, Jansen IGH, Brown S, Lingsma HF, Beenen LFM, Devlin TG, Román LS, Heo JH, Ribó M, Almekhlafi MA. Mediation of the relationship between endovascular therapy and functional outcome by follow-up infarct volume in patients with acute ischemic stroke.JAMA Neurology. 2019; 76:194–202. doi: 10.1001/jamaneurol.2018.3661Google Scholar
  • 45. Emmrich JV, Ejaz S, Williamson DJ, Hong YT, Sitnikov S, Fryer TD, Aigbirhio FI, Wulff H, Baron JC. Assessing the effects of cytoprotectants on selective neuronal loss, sensorimotor deficit and microglial activation after temporary middle cerebral occlusion.Brain Sci. 2019; 9:287. doi: 10.3390/brainsci9100287Google Scholar
  • 46. Saposnik G, Cote R, Phillips S, Gubitz G, Bayer N, Minuk J, Black S; Stroke Outcome Research Canada (SORCan) Working Group. Stroke outcome in those over 80: a multicenter cohort study across Canada.Stroke. 2008; 39:2310–2317. doi: 10.1161/STROKEAHA.107.511402LinkGoogle Scholar
  • 47. Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, Bambakidis NC, Becker K, Biller J, Brown M, Demaerschalk BM, Hoh B, et al. Guidelines for the early management of patients with acute ischemic stroke: 2019 update to the 2018 guidelines for the early management of acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association.Stroke. 2019; 50:e344–e418. doi: 10.1161/STR.0000000000000211LinkGoogle Scholar
  • 48. Venema E, Mulder MJHL, Roozenbeek B, Broderick JP, Yeatts SD, Khatri P, Berkhemer OA, Emmer BJ, Roos YBWEM, Majoie CBLM, et al. Selection of patients for intra-arterial treatment for acute ischaemic stroke: development and validation of a clinical decision tool in two randomised trials.BMJ. 2017; 357:j1710. doi: 10.1136/bmj.j1710CrossrefMedlineGoogle Scholar
  • 49. Chen C, Bivard A, Lin L, Levi CR, Spratt NJ, Parsons MW. Thresholds for infarction vary between gray matter and white matter in acute ischemic stroke: a CT perfusion study.J Cereb Blood Flow Metab. 2019; 39:536–546. doi: 10.1177/0271678X17744453Google Scholar
  • 50. Flottmann F, Broocks G, Faizy TD, Ernst M, Forkert ND, Grosser M, Thomalla G, Siemonsen S, Fiehler J, Kemmling A. CT-perfusion stroke imaging: a threshold free probabilistic approach to predict infarct volume compared to traditional ischemic thresholds.Sci Rep. 2017; 7:6679. doi: 10.1038/s41598-017-06882-wGoogle Scholar


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