Perfusion-diffusion Mismatch Research Articles

Estimating the volume of penumbra in rodents using DTI and stack-based ensemble machine learning framework

BackgroundThis study investigates the potential of diffusion tensor imaging (DTI) in identifying penumbral volume (PV) compared to the standard gadolinium-required perfusion–diffusion mismatch (PDM), utilizing a stack-based ensemble machine learning (ML) approach with enhanced explainability.MethodsSixteen male rats were subjected to middle cerebral artery occlusion. The penumbra was identified using PDM at 30 and 90 min after occlusion. We used 11 DTI-derived metrics and 14 distance-based features to train five voxel-wise ML models. The model predictions were integrated using stack-based ensemble techniques. ML-estimated and PDM-defined PVs were compared to evaluate model performance through volume similarity assessment, the Pearson correlation analysis, and Bland–Altman analysis. Feature importance was determined for explainability.ResultsIn the test rats, the ML-estimated median PV was 106.4 mL (interquartile range 44.6–157.3 mL), whereas the PDM-defined median PV was 102.0 mL (52.1–144.9 mL). These PVs had a volume similarity of 0.88 (0.79–0.96), a Pearson correlation coefficient of 0.93 (p < 0.001), and a Bland–Altman bias of 2.5 mL (2.4% of the mean PDM-defined PV), with 95% limits of agreement ranging from -44.9 to 49.9 mL. Among the features used for PV prediction, the mean diffusivity was the most important feature.ConclusionsOur study confirmed that PV can be estimated using DTI metrics with a stack-based ensemble ML approach, yielding results comparable to the volume defined by the standard PDM. The model explainability enhanced its clinical relevance. Human studies are warranted to validate our findings.Relevance statementThe proposed DTI-based ML model can estimate PV without the need for contrast agent administration, offering a valuable option for patients with kidney dysfunction. It also can serve as an alternative if perfusion map interpretation fails in the clinical setting.Key points• Penumbral volume can be estimated by DTI combined with stack-based ensemble ML.• Mean diffusivity was the most important feature used for predicting penumbral volume.• The proposed approach can be beneficial for patients with kidney dysfunction.Graphical

Successful Emergency Endovascular Treatment of Cavernous Internal Carotid Artery Stenosis Due to Compression by a Hemorrhagic Pituitary Tumor

Ischemic stroke associated with pituitary apoplexy is an extremely rare but devastating complication. Arterial stenosis or occlusion due to direct compression secondary to acute expansion of the hemorrhagic pituitary adenoma may induce ischemic stroke. In case of presentation of diffusion-perfusion or diffusion-clinical mismatch, urgent tumor resection to decompress the involved arteries should be performed to salvage ischemic penumbra. If emergent surgery is not possible, other therapeutic options are needed to prevent the progression of cerebral ischemia. Herein, we report the case of successful revascularization achieved in a patient with ischemic stroke who underwent balloon angioplasty and stent placement for the non-atherosclerotic steno-occlusion of intracranial internal carotid artery due to pituitary apoplexy.

A Study to Evaluate the Role of Three-Dimensional Pseudo-Continuous Arterial Spin Labelling in Acute Ischemic Stroke.

Introduction Magnetic resonance imaging (MRI) is well known to detect ischemic brain tissue and evaluate the tissue vulnerable to infarction. Diffusion-weighted imaging (DWI) has been a mainstay of stroke evaluation but has a few shortcomings, as it generally indicates only the core of ischemia and does not provide information regarding the tissue at risk or the ischemic penumbra surrounding the infarct. Perfusion imaging identifies brain tissue that has reduced blood flow as a potential target for reperfusion therapy. Arterial spin labelling (ASL) is a new non-invasive, non-contrast MRI perfusion sequence used to detect areas of hypoperfusion qualitatively and quantitatively and also identify the area at risk, i.e., the penumbra, in acute ischemic stroke. The most important component of the imaging is to determine the ischemic penumbra. One of the working definitions of penumbra is brain tissue that is ischemic but not yet infarcted and is at risk of further damage unless the flow is rapidly restored. Hence, perfusion-diffusion mismatch provides a realistic target for potential intervention. The aim of our study is to assess the role of ASLimaging in identifying the penumbra and providing insight into the management of acute ischemic stroke. Materials and methods Patients who presented with symptoms of acute ischemic stroke were included in the study, and an MRI stroke protocol comprising DWI, fluid-attenuated inversion recovery (FLAIR), ASL, and magnetic resonanceangiogram (MRA) sequences was done. Post-thrombolysis, a follow-up MRI was done using DWI, ASL, and MRA to see the restoration of perfusion in the ischemic penumbra. Three-dimensional pseudo-continuous ASL (in our study, ASL refers to pseudo-continuous ASL) is included in the stroke protocol in cases of acute ischemic stroke and assessed qualitatively. Results Our study included 43 patients (n = 43), of whom 39.5% (17 patients) belong to the age group of 51-60 years and 2.3% (one patient) are in the age group of 21-30 years. All 43 cases demonstrated DWI-FLAIR mismatch, suggestive of ischemic stroke within the window period, and all 43 cases showed DWI-ASL mismatch, suggestive of a large yet potentially salvageable peri-infarct ischemic penumbra. The most common territory involved was the middle cerebral artery (MCA), and the posterior cerebral artery (PCA) was the least commonly involved territory. We had one case involving the MCA-PCA watershed zone. Conclusion Arterial spin labelling is a novel, non-invasive, non-contrast MRI sequence with the capability to provide qualitative information regarding the salvageable ischemic penumbra, and timely management prevents the progression of the penumbra. The incorporation of ASL as part of the standard neuroimaging protocol aids in the management of acute stroke, giving insight into the prediction of outcome.

Role of arterial spin labeling magnetic resonance perfusion in acute ischemic stroke

BackgroundArterial spin labeling (ASL) is a recently used magnetic resonance imaging (MRI) perfusion technique in acute cerebrovascular stroke conditions; it can detect the hypo perfused areas on basis of qualitative and quantitative measurements and also identify the area at risk known as penumbra by detecting the diffusion/perfusion mismatch. The purpose of this study was to assess the role of ASL perfusion technique in management of acute ischemic stroke and its ability to predict the clinical outcome of acute stroke patients. The study was prospectively carried out on 33 patients clinically presented with acute stroke from the first of August 2020 till the first of August 2021. All cases were clinically assessed by stroke consultant followed by brain imaging including conventional MRI and ASL perfusion technique, based upon which management was established. These imaging data were correlated with the clinical outcome after 3 months using Modified Rankin Scale.ResultsSixteen cases (48.48%) showed ischemic penumbra with diffusion perfusion mismatch with three cases presenting within the first 4 h managed by intravenous thrombolytic therapy and 13 cases presenting later than 4 h, 10 of whom were managed by endovascular intervention. The group with ischemic penumbra showed significant positive correlation with favorable clinical outcome while the group without ischemic penumbra showed significant positive correlation with poor clinical outcome. Quantitative ASL values were statistically significantly higher (p ≤ 0.05) in patients with favorable clinical outcome than those with poor clinical outcome. The estimated cut off values of ASL absolute cerebral blood flow and relative cerebral blood flow to predict favorable or poor outcome using ROC curve analysis were 19 ml/100gm/min and 74% compared to the contralateral side respectively.ConclusionThe use of MRI as a primary diagnostic tool in arterial ischemic stroke with the application of non-contrast ASL perfusion sequence allows precise detection of perfusion deficit and diffusion perfusion mismatch (penumbra) and provides a reliable insight into outcome prediction.

Discrimination between progressive penumbra and benign oligemia of the diffusion-perfusion mismatch region by amide proton transfer-weighted imaging

PurposeAmide proton transfer-weighted (APTw) imaging was an effective tool to reveal the tissue acidosis of acute ischemic stroke. This study aimed to evaluate the ability of APTw MRI to distinguish progressive penumbra and benign oligemia in the diffusion-perfusion mismatch region. Materials and methods38 acute cerebral infarction patients who underwent a comprehensive MRI examination, including diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), APT imaging, and a follow-up scan in one week were recruited. There were 12 DWI/PWI match cases. The DWI/PWI mismatch patients were divided into 10 progressive cases and 16 stable cases according to the lesion size on the follow-up DWI image compared to the admission scan. Three ROIs: infarction lesion, peripheral, and contralateral normal regions were measured on each subject's MTRasym map. The Friedman test was used to compare the changes of MTRasym among three different regions within each group. The Kruskal-Wallis ANOVA test was used to compare them among the same region of different groups. The correlation between the MTRasym of the peripheral region and the lesion enlargement was analyzed by the Spearman test. ResultsThe MTRasym at the infarction lesion of all three groups showed significant decrease to the contralateral normal tissue. In the progressive mismatch group, the MTRasym at the peripheral region within the DWI/PWI mismatch showed a significant difference with the contralateral normal region and no difference with the infarct core. Whereas both the MTRasym at the peripheral region of the stable mismatch and match groups had no significant difference with the contralateral side, but the differences were significant from those of the central core. When comparing the peripheral region of three groups, the MTRasym of the progressive mismatch group showed a significant decrease to that of the stable mismatch and match groups. The MTRasym of the peripheral region showed a negative correlation with lesion enlargement. ConclusionAPTw imaging is promising to stratify the heterogeneous PWI/DWI mismatch region and benefit the clinical treatment.

Abstract TP75: Waking Up To A New Wake-Up Stroke Protocol Is Feasible And Safe

Introduction: Up to 25% of strokes are recognized upon awakening. Recent studies have demonstrated that a “tissue clock” rather than a time clock can be used to identify patients who may benefit from intravenous thrombolytics (IVT) beyond 4.5 hours from last known well (LKW). Consistent access to hyperacute MRI limits many centers from treating wake-up stroke patients. We created a formal protocol of clinical and imaging criteria to standardize evaluation and management of wake-up strokes. Methods: This retrospective, observational study reviewed consecutive patients admitted to our Comprehensive Stroke Center who qualified for the wake-up protocol between February 2022 and June 2022. The implemented protocol, based on clinical trials’ inclusion criteria, is comprised of the following: 1) arrival within 12 hours from LKW and within 4.5 hours from symptom discovery; 2) high suspicion for acute ischemic stroke; 3) no contraindication to MRI; 4) NIHSS of at least 4; 5) baseline mRS 0-3; 6) no absolute contraindications to IVT. For patients meeting above inclusion criteria, emergent MRI with perfusion was performed. Diffusion-FLAIR mismatch (signal intensity ratio) and diffusion-perfusion mismatch were reviewed to determine thrombolysis eligibility by a trained neuroradiologist or vascular neurologist. Results: Ten patients qualified for the wake-up protocol in the first five months of protocol implementation. Median NIHSS was 7, median LKW to arrival time was 8 hours, and median door to MRI time was 72.5 minutes. A final diagnosis of ischemic stroke was made in 80% of these cases. Overall, 50% were eligible for IVT based on our criteria, and 30% received thrombolysis. Median door to needle time was 92 minutes (range 75-117). There were no symptomatic intracranial hemorrhages. All patients treated with IVT were discharged home with no to minimal residual deficits with mRS 0-1 and median NIHSS at discharge of 2 (range 0-4). Conclusion: A formal protocol for wake-up stroke management allowed a streamlined approach to expand the number of IVT-eligible cases. Continued efforts are needed to improve door to needle times in such cases and to follow clinical courses of treated patients.

Predicting final ischemic stroke lesions from initial diffusion-weighted images using a deep neural network

BackgroundFor prognosis of stroke, measurement of the diffusion-perfusion mismatch is a common practice for estimating tissue at risk of infarction in the absence of timely reperfusion. However, perfusion-weighted imaging (PWI) adds time and expense to the acute stroke imaging workup. We explored whether a deep convolutional neural network (DCNN) model trained with diffusion-weighted imaging obtained at admission could predict final infarct volume and location in acute stroke patients. MethodsIn 445 patients, we trained and validated an attention-gated (AG) DCNN to predict final infarcts as delineated on follow-up studies obtained 3 to 7 days after stroke. The input channels consisted of MR diffusion-weighted imaging (DWI), apparent diffusion coefficients (ADC) maps, and thresholded ADC maps with values less than 620 × 10−6 mm2/s, while the output was a voxel-by-voxel probability map of tissue infarction. We evaluated performance of the model using the area under the receiver-operator characteristic curve (AUC), the Dice similarity coefficient (DSC), absolute lesion volume error, and the concordance correlation coefficient (ρc) of the predicted and true infarct volumes. ResultsThe model obtained a median AUC of 0.91 (IQR: 0.84–0.96). After thresholding at an infarction probability of 0.5, the median sensitivity and specificity were 0.60 (IQR: 0.16–0.84) and 0.97 (IQR: 0.93–0.99), respectively, while the median DSC and absolute volume error were 0.50 (IQR: 0.17–0.66) and 27 ml (IQR: 7–60 ml), respectively. The model’s predicted lesion volumes showed high correlation with ground truth volumes (ρc = 0.73, p < 0.01). ConclusionAn AG-DCNN using diffusion information alone upon admission was able to predict infarct volumes at 3–7 days after stroke onset with comparable accuracy to models that consider both DWI and PWI. This may enable treatment decisions to be made with shorter stroke imaging protocols.

Evaluation of Diffusion-Perfusion Mismatch in Acute Ischemic Stroke with a New Automated Perfusion-Weighted Imaging Software: A Retrospective Study.

The aim of this study was to evaluate the accuracy of automated software (iStroke) on magnetic resonance (MR) apparent diffusion coefficient (ADC) and perfusion-weighted imaging (PWI) against ground truth in assessing infarct core, and compare the hypoperfusion volume and mismatch volume on iStroke with those on Food and Drug Administration-approved software (RAPID) in patients with acute ischemic stroke. We used the single-volume decomposition method to develop the iStroke (iStroke; Beijing Tiantan Hospital, Beijing, China) software. Patients with ischemic stroke were collected from two educational hospitals in China with MR-PWI performed in the emergency department within 24h of symptom onset. Infarct core volume was defined as ADC < 620 × 10-6 mm2/s and hypoperfusion volume was defined as Tmax > 6s. We compared the accuracy of infarct core volume using iStroke and RAPID (iSchema View Inc, Menlo Park, CA) software with ground truth. We included 405 patients with acute ischemic stroke with MR ADC and PWI sequences. The infarct core volume on iStroke (median 2.43ml, interquartile range [IQR] 0.60-10.32ml) was not significantly different from the ground truth (median 2.89ml, IQR 0.77-9.17ml) (P = 0.07); Bland-Altman curves showed that the core volume of iStroke and RAPID software were comparable with each other on individual agreement with ground truth. The hypoperfusion volume and mismatch volume on iStroke were not statistically different from those on the RAPID software, respectively. In patients with large vessel occlusion (n = 74), the agreement between iStroke and RAPID was substantial (kappa = 0.76) according to DEFUSE 3 criteria (infarct core < 70ml, mismatch volume ≥ 15ml, and mismatch ratio ≥ 1.8). The iStroke automatic processing of ADC and PWI is a reliable software for the identification of diffusion-perfusion mismatch in acute ischemic stroke.

Estimating Perfusion Deficits in Acute Stroke Patients Without Perfusion Imaging.

Perfusion weighted imaging (PWI) is critical for determining whether stroke patients presenting in an extended time window are candidates for mechanical thrombectomy. However, PWI is not always available. Fluid-attenuated inversion recovery hyperintense vessels (FHVs) are seen in patients with a PWI lesion. We investigated whether a scale measuring the extent FHV could serve as a surrogate for PWI to determine eligibility for thrombectomy. The National Institutes of Health (NIH) FHV score was developed to quantify the burden of FHV and applied to magnetic resonance imaging scans of stroke patients with fluid-attenuated inversion recovery and perfusion imaging. The NIH-FHV was combined with the diffusion weighted image volume to estimate the diffusion-perfusion mismatch ratio. Linear regression was used to compare PWI volumes and mismatch ratios with estimates from the NIH-FHV score. Receiver operating characteristic analysis was used to test the ability of the NIH-FHV score to identify a significant mismatch. There were 101 patients included in the analysis, of whom 78% had a perfusion deficit detected on PWI with a mean lesion volume of 47 (±59) mL. The NIH-FHV score was strongly associated with the PWI lesion volume (P<0.001; R2=0.32; β-coefficient, 0.57). When combined with diffusion weighted image lesion volume, receiver operating characteristic analysis testing the ability to detect a mismatch ratio ≥1.8 using the NIH-FHV score resulted in an area under the curve of 0.94. The NIH-FHV score provides an estimate of the PWI lesion volume and, when combined with diffusion weighted imaging, may be helpful when trying to determine whether there is a clinically relevant diffusion-perfusion mismatch in situations where perfusion imaging is not available. Further studies are needed to validate this approach.

Role of Magnetic Resonance Perfusion Imaging in Acute Stroke: Arterial Spin Labeling Versus Dynamic Susceptibility Contrast-Enhanced Perfusion.

Introduction: The role of perfusion neuroimaging in managing cases of acute ischemic stroke (AIS) is to identify ischemic penumbra and regions of hypo-perfusion, which can be salvaged. Dynamic susceptibility contrast (DSC) perfusion imaging techniques have been the main magnetic resonance imaging (MRI) perfusion techniques used to identify AIS. Arterial spin labelling (ASL) is an alternative non-invasive perfusion technique, which permits tissue perfusion measurement without any need for administration of exogenous contrast agents. The objective was to compare the diagnostic accuracy of ASL perfusion MRI versus DSC enhanced perfusion MRI in detecting perfusion-diffusion mismatch of varying volumes in acute ischemic stroke.Materials and methods: A hospital-based observational cross-sectional study was done in a tertiary care institute in Tamil Nadu between December 2018 to October 2019. Fifty-five subjects aged more than 18 years referred to the Radio-diagnosis department (less than 24 hours since the onset of weakness) for emergency assessment of suspected acute stroke were subjected to MRI stroke scan protocol. Then AIS cases were evaluated with ASL and DSC perfusion-weighted imaging. The collected data was entered in Excel (Microsoft, Redmond, WA, USA). IBM SPSS version 22 (IBM Corp., Armonk, NY, USA) was used for statistical analysis. Receiver operating characteristic (ROC) analysis was done to assess the predictive validity of ASL in predicting DSC mismatch. The diagnostic accuracy of ASL was the primary outcome variable. P-value < 0.05 was considered statistically significant.Results: Forty-four subjects confirmed as stroke were included in the final analysis. Their mean (±SD) age was 53.84 (±10.80) years. 72.7% were males. The majority (53.8%) presented during the acute stage of cerebral infarction (53.8%). The majority (45.5%) had hemiplegia followed by aphasia (27.3%). The major vascular territory involved was the middle cerebral artery (54.5%). The sensitivity, specificity, positive predictive value, and negative predictive value of ASL (non-contrast) in predicting DSC (contrast) mismatch was found to be 71.43%, 78.57%, 83.33%, and 64.71% respectively.Conclusion: ASL MR has the potential to replace MRI DSC perfusion in the future imaging diagnostic work-up for stroke. However, further studies are required to validate its role as the first-line imaging for stroke therapy.

Should Primary Stroke Centers Perform Advanced Imaging?

Should Primary Stroke Centers Perform Advanced Imaging?

Impact of Diffusion–Perfusion Mismatch on Predicting Final Infarction Lesion Using Deep Learning

We report a study that validates the impact of diffusion-perfusion mismatch in a deep learning (DL) model predicting the final infarction lesion from baseline magnetic resonance imaging (MRI). From 472 consecutive patients with acute ischemic stroke, we gathered baseline and follow-up MRI having intervals of 3–7 days, and initial and final infarction lesions were segmented. Four U-Net-based DL models from baseline MRI with different combinations of diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI) maps, and initial diffusion-restricted lesion prediction map (Pred <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">init</sub> map) were trained to predict the final infarction lesion. Five-fold cross-validation was used for training and testing. As an external test set, 55 patients from another institution were analyzed. Dice similarity coefficient (DSC) was compared between the models and subgroups according to the presence of lesion growth and/or diffusion-perfusion mismatch. The model using the PWI maps and Pred <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">init</sub> map showed the best mean DSC (0.422 and 0.486 for internal and external test set, respectively). This model showed better performance in predicting rapid lesion growth compared with the baseline model (mean DSC difference, 0.040; 95% confidence interval: 0.018–0.062). Using the PWI map with initial diffusion-restricted lesion prediction improved the performance of DL model in predicting the final infarction lesion from baseline MRI.

Clinical-Diffusion Mismatch Is Associated with Early Neurological Improvement after Late-Window Endovascular Treatment

Background: Clinical-diffusion mismatch (CDM) and perfusion-diffusion mismatch (PDM) are used to select patients for endovascular thrombectomy (EVT) in the late-window period. As CDM well reflects true penumbra, we hypothesized that patients with CDM and PDM would respond better to EVT than those with PDM only at the late-window period. Methods: Acute ischemic stroke patients who received EVT 6–24 h after stroke onset were included. PDM (perfusion-/diffusion-weighted image (DWI) lesion volume >1.8) was used to select candidates for EVT in this time-period in our center. CDM was defined according to the DAWN trial criteria. Response to EVT was compared between patients with and without CDM. Early neurological improvement (ENI) was defined as improvement >4 points on National Institutes of Health Stroke Scale (NIHSS) score 1 day after EVT. Multivariable analysis was performed to investigate independent factors associated with ENI. The correlation between DWI lesion volume and NIHSS score was investigated in those with and without CDM. Results: Among 94 patients enrolled, all patients had PDM and 44 (46.3%) had CDM. Forty-eight patients (51.1%) showed ENI. The prevalence of hypertension, initial NIHSS score, improvement in NIHSS score after EVT, and prevalence of ENI were greater in patients with CDM than those without. ENI was independently associated with onset-to-door time (odds ratio [95% confidence interval]: 0.998 [0.997–1.000]; p = 0.042), complete recanalization (23.912 [2.238–255.489]; p = 0.009), initial NIHSS score (1.180 [1.012–1.377]; p = 0.034), and the presence of CDM (5.160 [1.448–18.386]; p = 0.011). The correlation between DWI lesion volume and initial NIHSS score was strong in patients without CDM (r = 0.731) but only moderate in patients with CDM (r = 0.355). Conclusion: Patients with both CDM and PDM had a better response to late-window EVT than those with PDM only.

Automated Perfusion-Diffusion Magnetic Resonance Imaging in Childhood Arterial Ischemic Stroke.

Recent studies using automated perfusion imaging software have identified adults most likely to benefit from reperfusion therapies in extended time windows. The time course of penumbral tissue is poorly characterized in childhood arterial ischemic stroke (AIS). We explore the feasibility of using automated perfusion-diffusion imaging software to characterize penumbra in childhood AIS. An observational cohort study of children with acute unilateral AIS presenting to our institution. Diffusion-weighted imaging and dynamic susceptibility contrast perfusion magnetic resonance imaging performed within 72 hours of symptom onset were necessary for inclusion. Perfusion-diffusion mismatch was estimated using RAPID software. Ischemic core was defined as apparent diffusion coefficient <620×10−6 mm2/s and hypoperfusion as Tmax >6 seconds. Favorable mismatch profile was defined as core volume <70 mL, mismatch volume ≥15 mL, and a mismatch ratio ≥1.8. Twenty-nine children (median 8 years old, interquartile range, 4.4–14.6) were included (26 unilateral middle cerebral artery and 3 unilateral cerebellar infarcts). Median Pediatric National Institutes of Health Stroke Scale was 4 (interquartile range, 3–11). Most cases had cryptogenic (n=11) or focal cerebral arteriopathy (n=9) causes. Median time-to-imaging =13.7 hours (interquartile range, 7.5–25.3). RAPID detected an ischemic core in 19 (66%) patients. In the remaining cases, the mean apparent diffusion coefficient values were mostly higher than the threshold as the majority of these presentations were delayed (median >21 hours) and infarct volumes were small (<3.5 mL). Overall, 3 children, imaged at 3.75, 11, and 23.5 hours had favorable mismatch profiles. This study demonstrates it is feasible to rapidly assess perfusion-diffusion mismatch in childhood AIS using automated software. Favorable mismatch profiles, using adult-based parameters, persisted beyond the standard 4.5 hours window for thrombolysis, suggesting potential therapeutic benefit of RAPID use. Further work is required to determine the utility of perfusion-based imaging to guide clinical decision making, whether adult thresholds require modification in childhood AIS, and to investigate the effect of time-delay and cause on mismatch characteristics.

MR Perfusion in the Evaluation of Mechanical Thrombectomy Candidacy.

Stroke is a leading cause of disability and mortality, and the incidence of ischemic stroke is projected to continue to rise in coming decades. These projections emphasize the need for improved imaging techniques for accurate diagnosis allowing effective treatments for ischemic stroke. Ischemic stroke is commonly evaluated with computed tomography (CT) or magnetic resonance imaging (MRI). Noncontrast CT is typically used within 4.5 hours of symptom onset to identify candidates for thrombolysis. Beyond this time window, thrombolytic therapy may lead to poor outcomes if patients are not optimally selected using appropriate imaging. MRI provides an accurate method for the earliest identification of core infarct, and MR perfusion can identify salvageable hypoperfused penumbra. The prognostic value for a better outcome in these patients lies in the ability to distinguish between core infarct and salvageable brain at risk-the ischemic penumbra-which is a function of the degree of ischemia and time. Many centers underutilize MRI for acute evaluation of ischemic stroke. This review will illustrate how perfusion-diffusion mismatch calculated from diffusion-weighted MRI and MR perfusion is a reliable approach for patient selection for stroke therapy and can be performed in timeframes that are comparable to CT-based algorithms while providing potentially superior diagnostic information.

Emergency STA-MCA bypass surgery for symptomatic progressive ischemic stroke

BackgroundIntravascular acute thrombectomy is recommended for acute cerebral infarction within 8 h of onset, based on several randomized controlled trials. However, standard treatment for cases outside these indications has not been established. ObjectiveEmergent superficial temporal artery (STA)-middle cerebral artery (MCA) bypass was performed within 72 h of onset for non-cardiogenic cerebral artery occlusive disease and the surgical outcomes are discussed. MethodsRetrospective review of 18 consecutive patients with non-cardiac cerebrovascular occlusive stroke who underwent emergent bypass surgery from September 2010 to August 2018. Surgical indications were determined as symptomatic ICA or MCA occlusive disease within 8–72 h after onset, and crescendo and/or progressive frequent transient ischemic attack, or impending stroke despite aggressive medical treatment with National Institutes of Health Stroke Scale (NIHSS) at 4 points or more, small cortical infarction (1/3 or less), and observed perfusion-diffusion mismatch. ResultsSurgical outcome was good recovery in 2 patients, moderate disability in 8, severe disability in 6, and death in 2 patients. Favorable outcome was achieved in 55.6%, and poor outcome in 44.4%. No patient showed enlargement of the area of cerebral infarction. The value of the BRS significantly improved after surgery in favourable outcome group. No patient suffered any complication related to surgical intervention including hemorrhagic complications. ConclusionsEmergent STA-MCA bypass surgery can improve clinical outcome and reduce the risk of morbidity under strict surgical indications, so could be an option for acute stage revascularization after ineffective thrombolytic therapy for non-cardiac acute cerebrovascular stroke.

Prevalence of Imaging Targets in Patients With Minor Stroke Selected for IV tPA Treatment Using MRI: The Treatment of Minor Stroke With MRI Evaluation Study (TIMES).

To determine the IV tissue plasminogen activator (tPA) treatment rate of patients with minor acute ischemic stroke (mAIS) at our centers and compare the frequency of MRI targets by treatment stratification and clinical severity, we evaluated clinical characteristics and baseline MRIs for tPA-treated and untreated patients. Patients with ischemic stroke from 2015 to 2017 with admit NIH Stroke Scale (NIHSS) <6 were considered. The treated cohort received standard IV tPA and was screened with baseline MRI. The untreated cohort received no acute intervention and baseline MRI was <4 hours from onset. Patients were stratified into "clearly" and "not clearly" disabling deficits by NIHSS elements. Baseline MRI was evaluated by independent raters for AIS targets, with frequencies compared between groups. Of 255 patients with mAIS ≤4.5 hours from onset, 140 (55%) received IV tPA, accounting for 46% of all IV tPA patients (n = 305). Eighty-five percent (n = 119) were screened with baseline MRI and had significantly more frequent imaging targets compared to those untreated (n = 90). Of this treated cohort, 75% (n = 89) were not clearly disabling. Except for perfusion-diffusion mismatch (81% clearly disabling vs 56% not clearly disabling [p = 0.036]), there were no significant differences in the frequency of imaging targets across the treated cohort stratified by clinical severity. In MRI-screened mAIS, imaging targets were more frequently seen in patients treated with IV tPA, with similar frequencies even in those without clearly disabling deficits. MRI targets could be used to guide thrombolytic therapy in patients with mAIS; however, a randomized trial is needed to demonstrate efficacy.

Efficacy and Safety of Timely Urgent Superficial Temporal Artery-to-Middle Cerebral Artery Bypass Surgery in Patients with Acute Ischemic Stroke: A Single-Institutional Prospective Study and a Pooled Analysis

Background: Clinical outcome in patients with acute ischemic stroke (AIS) caused by large vessel occlusion (LVO) is not satisfactory if reperfusion treatment fails or is not tried. Aims: We aimed to assess the efficacy and safety of urgent superficial temporal-to-middle cerebral artery (STA-MCA) bypass surgery in selected patients. Methods: Patients who were diagnosed with LVO-induced AIS in the anterior circulation but had a failed intra-arterial thrombectomy (IAT) or were not tried due to IAT contraindications were prospectively enrolled. Timely urgent STA-MCA bypass surgery was performed if they showed perfusion-diffusion mismatch or symptom-diffusion mismatch in the acute phase of disease. Clinical and radiological data of these patients were assessed to demonstrate the safety and efficacy of urgent bypass procedures. A pooled analysis of published data on urgent bypass surgery in acute stroke patients was conducted and analyzed. Results: In 18 patients who underwent timely bypass, the National Institutes of Health Stroke Scale (NIHSS) score improved from 12.11 ± 4.84 to 9.89 ± 6.52, 1 week after surgery. Three-month and long-term (9.72 ± 5.00 months) favorable outcomes (modified Rankin Scale [mRS] scores 0–2) were achieved in 50 and 75% of the patients, respectively. The pooled analysis (117 patients from 10 articles, including ours) identified favorable mRS scores in 71.79% patients at 3 months. A significant NIHSS score improvement from 11.51 ± 4.89 to 7.59 ± 5.50 was observed after surgery with significance. Major complications occurred in 3 patients (2.6%, 3/117) without mortality. Conclusions: Urgent STA-MCA bypass surgery can be regarded as a safe optional treatment to prevent cerebral infarct expansion and to improve clinical and radiological outcomes in highly selected patients.

Impact of the reperfusion status for predicting the final stroke infarct using deep learning

BackgroundPredictive maps of the final infarct may help therapeutic decisions in acute ischemic stroke patients. Our objectives were to assess whether integrating the reperfusion status into deep learning models would improve their performance, and to compare them to current clinical prediction methods. MethodsWe trained and tested convolutional neural networks (CNNs) to predict the final infarct in acute ischemic stroke patients treated by thrombectomy in our center. When training the CNNs, non-reperfused patients from a non-thrombectomized cohort were added to the training set to increase the size of this group. Baseline diffusion and perfusion-weighted magnetic resonance imaging (MRI) were used as inputs, and the lesion segmented on day-6 MRI served as the ground truth for the final infarct. The cohort was dichotomized into two subsets, reperfused and non-reperfused patients, from which reperfusion status specific CNNs were developed and compared to one another, and to the clinically-used perfusion-diffusion mismatch model. Evaluation metrics included the Dice similarity coefficient (DSC), precision, recall, volumetric similarity, Hausdorff distance and area-under-the-curve (AUC). ResultsWe analyzed 109 patients, including 35 without reperfusion. The highest DSC were achieved in both reperfused and non-reperfused patients (DSC = 0.44 ± 0.25 and 0.47 ± 0.17, respectively) when using the corresponding reperfusion status-specific CNN. CNN-based models achieved higher DSC and AUC values compared to those of perfusion-diffusion mismatch models (reperfused patients: AUC = 0.87 ± 0.13 vs 0.79 ± 0.17, P < 0.001; non-reperfused patients: AUC = 0.81 ± 0.13 vs 0.73 ± 0.14, P < 0.01, in CNN vs perfusion-diffusion mismatch models, respectively). ConclusionThe performance of deep learning models improved when the reperfusion status was incorporated in their training. CNN-based models outperformed the clinically-used perfusion-diffusion mismatch model. Comparing the predicted infarct in case of successful vs failed reperfusion may help in estimating the treatment effect and guiding therapeutic decisions in selected patients.

Automated MRI perfusion-diffusion mismatch estimation may be significantly different in individual patients when using different software packages

ObjectiveTo compare two established software applications in terms of apparent diffusion coefficient (ADC) lesion volumes, volume of critically hypoperfused brain tissue, and calculated volumes of perfusion-diffusion mismatch in brain MRI of patients with acute ischemic stroke.MethodsBrain MRI examinations of 81 patients with acute stroke due to large vessel occlusion of the anterior circulation were analyzed. The volume of hypoperfused brain tissue, ADC volume, and the volume of perfusion-diffusion mismatch were calculated automatically with two different software packages. The calculated parameters were compared quantitatively using formal statistics.ResultsSignificant difference was found for the volume of hypoperfused tissue (median 91.0 ml vs. 102.2 ml; p < 0.05) and the ADC volume (median 30.0 ml vs. 23.9 ml; p < 0.05) between different software packages. The volume of the perfusion-diffusion mismatch differed significantly (median 47.0 ml vs. 67.2 ml; p < 0.05). Evaluation of the results on a single-subject basis revealed a mean absolute difference of 20.5 ml for hypoperfused tissue, 10.8 ml for ADC volumes, and 27.6 ml for mismatch volumes, respectively. Application of the DEFUSE 3 threshold of 70 ml infarction core would have resulted in dissenting treatment decisions in 6/81 (7.4%) patients.ConclusionVolume segmentation in different software products may lead to significantly different results in the individual patient and may thus seriously influence the decision for or against mechanical thrombectomy.Key Points• Automated calculation of MRI perfusion-diffusion mismatch helps clinicians to apply inclusion and exclusion criteria derived from randomized trials.• Infarct volume segmentation plays a crucial role and lead to significantly different result for different computer programs.• Perfusion-diffusion mismatch estimation from different computer programs may influence the decision for or against mechanical thrombectomy.