Transformation In Acute Ischemic Stroke Research Articles

Hemorrhagic transformation in acute ischemic stroke: hemorrhagic subtypes and symptomatic intracranial hemorrhage

BackgroundFew clinical studies perform detailed analyses of subtypes of intracranial hemorrhage (ICH) after mechanical thrombectomy (MT) used to treat acute ischemic stroke. Symptomatic intracranial hemorrhage (sICH) is a formidable complication...

Cerebral circulation time on DSA after thrombectomy associated with hemorrhagic transformation in acute ischemic stroke.

To investigate the association between cerebral circulation time (CCT) on digital subtraction angiography immediately after thrombectomy and hemorrhagic transformation (HT) in acute ischemic stroke (AIS). Retrospectively enrolled consecutive AIS patients presented with large vessel occlusion who received thrombectomy and achieved successful recanalization between January 2019 and June 2021. The time interval from the beginning of the siphon segment of internal carotid artery visualization until the end of the arterial phase during cerebral angiography was calculated as CCT. The independent association of CCT with HT was evaluated using logistic regression analyses. The receiver operating characteristic curve was analyzed to evaluate the association between CCT and HT. Two hundred and twenty-four patients were included, of whom 86 (38.4%) suffered HT. Compared with patients without HT, patients with HT were of advanced age, less commonly male, had more diabetes mellitus, had higher baseline National Institutes of Health Stroke Scale score, lower Alberta Stroke Program Early Computed Tomographic Score, and shorter CCT (P < 0.05). Multivariable logistic regression suggested that CCT was independently associated with HT (adjusted odds ratio, 0.170; 95% confidence interval, 0.004-0.450; P < 0.001). According to the receiver operating characteristic curve, the optimal cut-off value for the strong correlation between CCT and HT was 1.72s, which had 76.6% sensitivity, 81.6% specificity, and the area under the curve was 0.846. Shorter post-thrombectomy CCT was independently associated with HT.

The value of CT-based radiomics in predicting hemorrhagic transformation in acute ischemic stroke patients without recanalization therapy.

The aim of this study is to investigate the clinical value of radiomics based on non-enhanced head CT in the prediction of hemorrhage transformation in acute ischemic stroke (AIS). A total of 140 patients diagnosed with AIS from January 2015 to August 2022 were enrolled. Radiomic features from infarcted areas on non-enhanced CT images were extracted using ITK-SNAP. The max-relevance and min-redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select features. The radiomics signature was then constructed by multiple logistic regressions. The clinicoradiomics nomogram was constructed by combining radiomics signature and clinical characteristics. All predictive models were constructed in the training group, and these were verified in the validation group. All models were evaluated with the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Of the 140 patients, 59 experienced hemorrhagic transformation, while 81 remained stable. The radiomics signature was constructed by 10 radiomics features. The clinicoradiomics nomogram was constructed by combining radiomics signature and atrial fibrillation. The area under the ROC curve (AUCs) of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the training group were 0.64, 0.86, and 0.86, respectively. The AUCs of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the validation group were 0.63, 0.90, and 0.90, respectively. The DCA curves showed that the radiomics signature performed well as well as the clinicoradiomics nomogram. The DCA curve showed that the clinical application value of the radiomics signature is similar to that of the clinicoradiomics nomogram. The radiomics signature, constructed without incorporating clinical characteristics, can independently and effectively predict hemorrhagic transformation in AIS patients.

Clinical and imaging predictors for hemorrhagic transformation of acute ischemic stroke after endovascular thrombectomy.

Hemorrhagic transformation (HT) is a common complication of endovascular thrombectomy (EVT) in patients with acute ischemic stroke (AIS). Our study aims to investigate the clinical and imaging predictors of HT and symptomatic intracranial hemorrhage (sICH) in patients who underwent EVT. A retrospective analysis of 118 patients undergoing EVT for acute anterior circulation stroke was performed. Potential clinical and imaging predictors of all patients were collected and multivariate logistic regression was performed. The risk prediction system was constructed according to the multivariate logistic regression results. The incidence of HT and sICH after EVT were 46.6% and 15.3%, respectively. The multivariate logistic regression results showed that Alberta Stroke Program Early CT Score (ASPECTS) (p = .001, odds ratio [OR] = 0.367, 95% [confidence interval] CI, 0.201-0.670), collateral status (p<.001, OR = 0.117, 95% CI, 0.042-0.325), relative cerebral blood flow (CBF) ratio (p = .025, OR = 0.943, 95% CI, 0.895-0.993), and blood glucose on admission (p = .012, OR = 1.258, 95% CI, 1.053-1.504) were associated with HT. While for sICH, collateral circulation (p = .007, OR = 0.148, 95% CI, 0.037-0.589), ASPECTS (p = .033, OR = 0.510, 95% CI, 0.274-0.946), and blood glucose (p = .005, OR = 1.304, 95% CI, 1.082-1.573) were independent factors. The predictive model for HT after EVT was established, and the sensitivity and specificity of it were 90.9% and 79.4%, respectively, with the area under the curve of 90.0% (84.5%-95.4%). Collateral status, ASPECTS, relative CBF ratio, and blood glucose on admission were predictors for HT in AIS patients, while collateral status, ASPECTS, and blood glucose on admission were also predictors for sICH. In addition, the established predictive model showed good diagnostic value for prediction of HT after EVT.

Prognostic Burden of Hemorrhagic Transformation in Acute Ischemic Stroke: A Brief Report from the Real Life

Introduction: Hemorrhagic Transformation (HT) represents one of the main complications of acute ischemic stroke, affecting its management and prognosis. Few data exists on prognosis of HT in the real world. Aim of this study was to evaluate the prognostic impact of HT in a real world cohort of patients hospitalized for acute ischemic stroke. Methods: We retrospectively analyzed the clinical data of patients with acute ischemic stroke consecutively admitted to our Stroke Unit. Patients with HT were compared with those without HT. Modified Rankin Scale (mRS) at hospital discharge and at 90 days were the study outcomes. Poor prognosis was defined as mRS≥4. A multivariate logistic regression analysis was performed to identify independent predictors of outcomes. Results: The study population consisted of 564 patients with mean age 77.5±11.8 years. Fifty-two patients (9.2%) showed HT on brain CT. Length of hospitalization, in-hospital mortality, median mRS at discharge, percentage of patients with mRS≥4 at discharge, percentage of HT patients discharged without secondary antiplatelet or anticoagulant prophylaxis and median 90- day mRS were significantly higher in patients with HT than in those without. The presence of HT was predictive of mRS≥4 at discharge and at 90 days (AUC 0.720 and 0.776, respectively). The presence of HT was an independent predictor of poor outcome, increasing the risk by about four times both at discharge (OR 3.64, 95% 1.46-9.06) and at 90 days (OR 4.26, 95% 1.07-16.88). Conclusions: HT is associated with a poor outcome in terms of mortality and severe residual disability both in the acute phase and at 90 days.

Magnetic Resonance Perfusion-Weighted Imaging in Predicting Hemorrhagic Transformation of Acute Ischemic Stroke: A Retrospective Study.

Hemorrhagic transformation (HT) is one of the common complications in patients with acute ischemic stroke (AIS). This study aims to investigate the value of different thresholds of Tmax generated from perfusion-weighted MR imaging (PWI) and the apparent diffusion coefficient (ADC) value in the prediction of HT in AIS. A total of 156 AIS patients were enrolled in this study, with 55 patients in the HT group and 101 patients in non-HT group. The clinical baseline data and multi-parametric MRI findings were compared between HT and non-HT groups to identify indicators related to HT. The optimal parameters for predicting HT and the corresponding cutoff values were obtained using the receiver operating characteristic curve analysis of the volumes of ADC < 620 × 10-6 mm2/s and Tmax > 6 s, 8 s, and 10 s. The results showed that the volumes of ADC < 620 × 10-6 mm2/s and Tmax > 6 s, 8 s, and 10 s in the HT group were all significantly larger than that in the non-HT group and were all independent risk factors for HT. Early measurement of the volume of Tmax > 10 s had the highest value, with a cutoff lesion volume of 10.5 mL.

Abstract 256: Proposal of multimodal CT‐based scoring system in prediction of hemorrhagic transformation in acute ischemic stroke

Introduction The routinely used computed tomography (CT)‐based workup in the setting of acute ischemic stroke (AIS) includes non‐contrast brain CT, CT angiography (CTA), and CT perfusion. Several CT, CTA, CTP‐based radiological biomarkers of hemorrhagic transformation (HT) were reported. To assess the predictive value of the combined multimodal CT parameters for HT after AIS and proposal of predictive scoring scale. Methods The source images of the NCCT, CTA and CTP of 282 AIS patients involving the anterior circulation (HT = 91, non‐HT = 191) were retrospectively reviewed and the following biomarkers were recorded and analyzed: Early subtle ischemic signs, hyperdense middle cerebral artery sign (HMCAS) and Alberta Stroke Program Early CT Score (ASPECTS) &lt; 7 in NCCT, large‐vessel occlusion (LVO), clot burden score (CBS) &lt; 6, large‐vessel occlusion, poor collateral score (CS) and Tmax &gt; 6 s ≥ 56.5 ml. A scoring system to predict HT based on these biomarkers was developed. Each biomarker counts for a single point with the total score ranging from 0 to 7. Results All the aforementioned multimodal CT biomarkers and the selected cut offs were significantly associated with higher HT risk. The calculated scores were statistically significant different between the HT and the non‐HT groups with AUC 0.761 (95% CI 0.703–0.819, P &lt; 0.0000001). Rates of HT were approximately five times higher in patients with score ≥ 3. Conclusion Multimodal CT‐based scoring system may provide highly reliable predictive model of hemorrhagic transformation in acute ischemic stroke.

Quantitative assessment of hyperperfusion using arterial spin labeling to predict hemorrhagic transformation in acute ischemic stroke patients with mechanical endovascular therapy.

This study was aimed to quantitatively assess hyperperfusion using arterial spin labeling (ASL) to predict hemorrhagic transformation (HT) in acute ischemic stroke (AIS) patients. This study enrolled 98 AIS patients with anterior circulation large vessel occlusion within 24h of symptom onset. ASL was performed before mechanical endovascular therapy. On pre-treatment ASL maps, a region with relative cerebral blood flow (CBF) ≥ 1.4 was defined as an area of hyperperfusion. The maximum CBF (CBFmax) of hyperperfusion was calculated for each patient. A non-contrast CT scan was performed during the subacute phase for the evaluation of HT. Good clinical outcome was defined as a 90-day modified Rankin scale score of 0-2. The CBFmax of hyperperfusion (odds ratio, 1.023; 95% confidence interval [CI], 1.005-1.042; p = 0.012) was an independent risk factor for the status of HT. The CBFmax of hyperperfusion for HT showed an area under the curve of 0.735 (95% CI, 0.588-0.882) with optimal cutoff value, sensitivity, and specificity being 146.5mL/100g/min, 76.9%, and 69.6%, respectively. There was a statistically significant relationship between HT grades (from no HT to PH2) and CBFmax of hyperperfusion with a Spearman rank correlation of 0.446 (p = 0.001). In addition, low CBFmax of hyperperfusion were associated with good functional outcome (95% CI, 17.130-73.910; p = 0.002). High CBFmax of hyperperfusion was independently associated with subsequent HT and low CBFmax of hyperperfusion linked to good functional outcome. There was a positive correlation between HT grade and CBFmax. CLINICAL RELEVANCE STATEMENT: Arterial spin labeling is a noninvasive and contrast agent-independent technique, which is sensitive in detecting hyperperfusion. This study shows that the cerebral blood flow of hyperperfusion is associated with clinical prognosis, which will benefit more patients. • Quantitative assessment of hyperperfusion using pre-treatment arterial spin labeling to predict hemorrhagic transformation and prognosis in acute ischemic stroke patients. • The maximum cerebral blood flow of hyperperfusion was associated with hemorrhagic transformation and clinical prognosis and higher maximum cerebral blood flow of hyperperfusion was associated with higher grade hemorrhagic transformation. • The maximum cerebral blood flow of hyperperfusion can predict hemorrhagic transformation which enables timely intervention to prevent parenchymal hematoma.

Predictive Factors for Hemorrhagic Transformation in Acute Ischemic Stroke in the REAL-World Clinical Practice.

Few data exists on predictive factors of hemorrhagic transformation (HT) in real-world acute ischemic stroke patients. The aims of this study were: (i) to identify predictive variables of HT (ii) to develop a score for predicting HT. We retrospectively analyzed the clinical, radiographic, and laboratory data of patients with acute ischemic stroke consecutively admitted to our Stroke Unit along two years. Patients with HT were compared with those without HT. A multivariate logistic regression analysis was performed to identify independent predictors of HT on CT scan at 24 hours to develop a practical score. The study population consisted of 564 patients with mean age 77.5±11.8 years. Fifty-two patients (9.2%) showed HT on brain CT at 24 hours (4.9% symptomatic). NIHSS score ≥8 at Stroke Unit admission (3 points), cardioembolic etiology (2 points), acute revascularization by systemic thrombolysis and/or mechanical thrombectomy (1 point), history of previous TIA/stroke (1 point), and major vessel occlusion (1 point) were found independent risk factors of HT and were included in the score (Hemorrhagic Transformation Empoli score (HTE)). The predictive power of HTE score was good with an AUC of 0.785 (95% CI: 0.749-0.818). Compared with 5 HT predictive scores proposed in the literature (THRIVE, SPAN-100, MSS, GRASPS, SITS-SIC), the HTE score significantly better predicted HT. NIHSS score ≥8 at Stroke Unit admission, cardioembolism, urgent revascularization, previous TIA/stroke, and major vessel occlusion were independent predictors of HT. The HTE score has a good predictive power for HT. Prospective studies are warranted.

Proposal of multimodal computed tomography-based scoring system in prediction of hemorrhagic transformation in acute ischemic stroke.

The routinely used computed tomography (CT)-based workup in the setting of acute ischemic stroke (AIS) includes non-contrast brain CT, CT angiography (CTA), and CT perfusion. Several CT, CTA, CTP-based radiological biomarkers of hemorrhagic transformation (HT) were reported. To assess the predictive value of the combined multimodal CT parameters for HT after AIS and proposal of predictive scoring scale. The source images of the NCCT, CTA and CTP of 282 AIS patients involving the anterior circulation (HT = 91, non-HT = 191) were retrospectively reviewed and the following biomarkers were recorded and analyzed: Early subtle ischemic signs, hyperdense middle cerebral artery sign (HMCAS) and Alberta Stroke Program Early CT Score (ASPECTS) < 7 in NCCT, large-vessel occlusion (LVO), clot burden score (CBS) < 6, large-vessel occlusion, poor collateral score (CS) and Tmax > 6s ≥ 56.5ml. A scoring system to predict HT based on these biomarkers was developed. Each biomarker counts for a single point with the total score ranging from 0 to 7. All the aforementioned multimodal CT biomarkers and the selected cut offs were significantly associated with higher HT risk. The calculated scores were statistically significant different between the HT and the non-HT groups with AUC 0.761 (95% CI 0.703-0.819, P < 0.0000001). Rates of HT were approximately five times higher in patients with score ≥ 3. Multimodal CT-based scoring system may provide highly reliable predictive model of hemorrhagic transformation in acute ischemic stroke.

Association between Infarct Location and Hemorrhagic Transformation of Acute Ischemic Stroke following Successful Recanalization after Mechanical Thrombectomy.

The association between infarct location and hemorrhagic transformation of acute ischemic stroke after mechanical thrombectomy is not understood. We aimed to evaluate the association between CTP-based ischemic core variables at admission and hemorrhagic transformation after a successful thrombectomy. We retrospectively analyzed patients who underwent endovascular thrombectomy for acute anterior circulation large-vessel occlusion between October 2019 and June 2021. We enrolled 146 patients with visible ischemic core on pretreatment CTP who had successful reperfusion. The ischemic core infarct territories were classified into the cortical and subcortical areas and then qualitatively and quantitatively analyzed by CTP. Logistic regression and receiver operating characteristic curve analyses were performed to determine the association between ischemic core variables and hemorrhagic transformation. Of the 146 patients analyzed, 72 (49.3%) had hemorrhagic transformation and 23 (15.8%) had symptomatic intracerebral hemorrhage. Multivariate analysis showed that subcortical infarcts were independently associated with hemorrhagic transformation (OR, 8.06; 95% CI, 2.31-28.10; P = .001) and subcortical infarct volume was independently linked to symptomatic intracerebral hemorrhage (OR, 1.05; 95% CI, 1.01-1.09; P = .039). The receiver operating characteristic curve indicated that subcortical infarcts can predict hemorrhagic transformation accurately (area under the curve = 0.755; 95% CI, 0.68-0.82; P < .001) and subcortical infarct volume can predict symptomatic intracerebral hemorrhage (area under the curve = 0.694; 95% CI, 0.61-0.77; P = .002). Subcortical infarcts seen on CTP at admission are associated with hemorrhagic transformation in patients after successful thrombectomy, and subcortical infarct volume may influence the risk of symptomatic intracerebral hemorrhage.

Machine Learning-Based Model for Prediction of Hemorrhage Transformation in Acute Ischemic Stroke After Alteplase.

Hemorrhage transformation (HT) is the most dreaded complication of intravenous thrombolysis (IVT) in acute ischemic stroke (AIS). The prediction of HT after IVT is important in the treatment decision-making for AIS. We designed and compared different machine learning methods, capable of predicting HT in AIS after IVT. A total of 345 AIS patients who received intravenous alteplase between January 2016 and June 2021 were enrolled in this retrospective study. The demographic characteristics, clinical condition, biochemical data, and neuroimaging variables were included for analysis. HT was confirmed by head computed tomography (CT) or magnetic resonance imaging (MRI) within 48 h after IVT. Based on the neuroimaging results, all of the patients were divided into the non-HT group and the HT group. Then, the variables were applied in logistic regression (LR) and random forest (RF) algorithms to establish HT prediction models. To evaluate the accuracy of the machine learning models, the models were compared to several of the common scales used in clinics, including the multicenter stroke survey (MSS) score, safe implementation of treatments in stroke (SITS) score, and SEDAN score. The performance of these prediction models was evaluated using the receiver operating characteristic (ROC) curve (AUC). Forty-five patients had HT (13.0%) within 48 h after IVT. The ROC curve results showed that the AUCs of HT that were predicted by the RF model, LR model, MSS, SITS, and SEDAN scales after IVT were 0.795 (95% CI, 0.647–0.944), 0.703 (95% CI, 0.515–0.892), 0.657 (95% CI, 0.574–0.741), 0.660 (95% CI, 0.580–0.740) and 0.655 (95% CI, 0.571–0.739), respectively. The RF model performed better than the other models and scales. The top four most influential factors in the RF importance matrix plot were triglyceride, Lpa, the baseline NIHSS, and hemoglobin. The SHapley Additive exPlanation values made the RF prediction model clinically interpretable. In this study, an RF machine learning method was successfully established to predict HT in AIS patients after intravenous alteplase, which the sensitivity was 66.7%, and the specificity was 80.7%.

ASPECTS-Based Attenuation Changes on CT Angiography as an Imaging Biomarker to Predict Hemorrhagic Transformation in Acute Ischemic Stroke

Introduction: Imaging-based early warning indicators and feasible stratification of acute ischemic stroke (AIS) patients with hemorrhagic transformation (HT), especially high-risk patients with parenchymal hematoma (PH), are crucial in determining subsequent treatment strategies. This study combined automated ASPECTS software with noncontrast CT (NCCT) and CTA source image (CTASI) attenuation changes using Hounsfield unit (HU) values to predict HT and PH in patients with AIS. Materials and Methods: We retrospectively enrolled 172 consecutive patients with anterior circulation large-vessel occlusion between 2016 and 2020. Univariate and multivariate logistic regression and receiver operating characteristic (ROC) analyses were used to investigate the relationship between NCCT and CTASI-ASPECTS-HU, as well as other clinical and radiological parameters of HT and PH. Univariate and multivariate logistic regression analyses were performed to explore risk factors for HT or PH, and an ROC curve was used to evaluate their diagnostic values. Results: A multivariate analysis showed that CTASI-ASPECTS-HU and NIHSS score were independent predictors of HT (CTASI-ASPECTS-HU: odds ratio (OR), 2.22; 95% CI, 1.01–4.92; NIHSS: OR, 1.07; 95% CI, 1.02–1.13) and PH (CTASI-ASPECTS-HU: OR, 6.51; 95% CI, 2.29–18.50; NIHSS: OR, 1.07; 95% CI, 1.01–1.13). According to ROC analysis, CTASI-ASPECTS-HU >0.09 identified HT (area under the curve, 0.70; sensitivity, 70.15%; specificity, 61.90%), and CTASI-ASPECTS-HU >0.10 identified PH (area under the curve, 0.79; sensitivity, 76.19%; specificity, 73.33%). The area under the curve for predicting HT or PH increased when CTASI-ASPECTS-HU was combined with NIHSS score (HT: area under the curve, 0.74; sensitivity, 73.13%; specificity, 70.48%; PH: area under the curve, 0.81; sensitivity, 85.71%; specificity, 72.38%). Conclusion: CTASI-ASPECTS-HU is a reliable radiological predictor of HT and PH in patients with AIS. Its predictive efficacy is moderately improved when combined with NIHSS score.

Clinical and Imaging Indicators of Hemorrhagic Transformation in Acute Ischemic Stroke After Endovascular Thrombectomy.

Prior studies have investigated the clinical and imaging factors for hemorrhagic transformation (HT), especially symptomatic intracranial hemorrhage (sICH); however, whether alteplase increases the risk of HT after endovascular thrombectomy (EVT) is unknown. This study aimed to assess clinical and imaging features associated with HT, sICH, and parenchymal hematoma (PH) in patients with acute ischemic stroke after EVT, with and without intravenous alteplase in DIRECT-MT (Direct Intraarterial Thrombectomy to Revascularize Acute Ischemic Stroke Patients with Large Vessel Occlusion Efficiently in Chinese Tertiary Hospitals: a Multicenter Randomized Clinical Trial). The DIRECT-MT trial is a randomized trial of EVT alone versus intravenous thrombolysis combined with EVT. HT, sICH, and PH was evaluated on follow-up computed tomography. Multivariable ordinal logistic regression analysis was used to test the association of stepwise selected determinants with HT, sICH, and PH. In total, 633 patients were analyzed; 261 (41.2%) had HT; 34 (5.4%) had sICH; and 85 (13.4%) had PH. The median age was 69, and 56.7% were men. The median National Institutes of Health Stroke Scale score was 18, and 320 patients were in combination-therapy group. Symptomatic intracranial hemorrhage was associated with higher baseline National Institutes of Health Stroke Scale score (adjusted odds ratio [OR], 1.06 [95% CI, 1.10-1.12]) and higher glucose level at hospital arrival (adjusted OR, 1.14 [95% CI, 1.00-1.29]). No association was found between alteplase treatment and HT, sICH, or PH. The independent predictor of sICH was higher baseline National Institutes of Health Stroke Scale score (adjusted OR, 1.09 [95% CI, 1.01-1.18]) in EVT alone group, and history of anticoagulant drugs (adjusted OR, 3.75 [95% CI, 1.07-13.06]), higher glucose level at hospital arrival (adjusted OR, 1.19 [95% CI, 1.03-1.38]), >3 passes of device (adjusted OR, 4.42 [95% CI, 1.36-14.32]) in combination-therapy group. In DIRECT-MT, independent predictors of sICH were baseline National Institutes of Health Stroke Scale score and glucose level at hospital arrival. Alteplase treatment did not increase the risk of HT, sICH, or PH after EVT. The independent predictor of sICH was different in EVT alone group and combination-therapy group. URL: https://www. gov; Unique identifier: NCT03469206.

The importance of matrix metalloproteinases in the prognosis of acute ischemic stroke patients

Ischemic stroke is one of the leading causes of mortality and disability worldwide. Numerous studies were performed to assess the risk of clinical deterioration of acute ischemic stroke patients, including the risk of haemorrhagic transformation. The complexity of cerebral ischemia pathology raised the possibility of a multitude of candidate-molecules to be studied as stroke biomarkers. The blood brain barrier integrity biomarkers have shown promising results both in fundamental and clinical studies. Matrix metalloproteinases have been extensively analysed and gave encouraging results for predicting unfavourable neurological outcome, including the risk for haemorrhagic transformation. Matrix metalloproteinase-9 plays a crucial role in the disruption of the blood-brain barrier following focal cerebral ischemic stroke. Elevated matrix metalloproteinase-2 levels are responsible for the degradation of tight junction proteins, basal lamina and neuronal injury after ischemia, and may contribute to infarction and hemorrhagic volume. The review provides an overview of matrix metalloproteinases’ role in the prognosis of acute ischemic stroke patients, regarding the stroke outcome and the risk of haemorrhagic transformation. Conclusions: Matrix metalloproteinases, especially gelatinases, are extensively studied for their predictive value in ischemic stroke evolution. Matrix metalloproteinase-2 and matrix metalloproteinase-9 correlate with stroke severity and haemorrhagic transformation in acute ischemic stroke, but large validation studies are needed for practical translation. Future studies should focus on developing a biomarker panel for predicting outcomes in stroke patients.

Imaging for Predicting Hemorrhagic Transformation of Acute Ischemic Stroke-A Narrative Review.

Hemorrhagic transformation is caused by extravasation of blood products from vessels after acute ischemic stroke. It is an undesirable and potentially devastating complication, which occurs in 10%-40% of clinical cases. Hemorrhagic transformation is classified into four subtypes based on European cooperative acute stroke study II. Predicting hemorrhagic complications at presentation can be useful life saving/altering decisions for the patient. Also, understanding the mechanisms of hemorrhagic transformation can lead to new treatments and intervention measures. We highlighted various imaging techniques that have been used to predict hemorrhagic transformation. Specifically, we looked at the usefulness of perfusion and permeability imaging for hemorrhagic transformation. Use of imaging to predict hemorrhagic transformation could change patient management that may lead to the prevention of hemorrhagic transformation before it occurs. We concluded that the current evidence is not strong enough to rely on these imaging parameters for predicting hemorrhagic transformation and more studies are required.

Collateral and permeability imaging derived from dynamic contrast material-enhanced MR angiography in prediction of PH 2 hemorrhagic transformation after acute ischemic stroke: a pilot study.

To evaluate the role of collateral and permeability imaging derived from dynamic contrast material-enhanced magnetic resonance angiography to predict PH 2 hemorrhagic transformation in acute ischemic stroke. The secondary analysis of a published data from participants with acute ischemic stroke. The multiphase collateral map and permeability imaging were generated by using dynamic signals from dynamic contrast material-enhanced magnetic resonance angiography obtained at admission. To identify independent predictors of PH 2 hemorrhagic transformation, age, sex, risk factors, baseline National Institutes of Health Stoke Scale (NIHSS) score, baseline DWI lesion volume, collateral-perfusion status, mode of treatment, and successful early reperfusion were evaluated with multiple logistic regression analyses and the significance of permeability imaging in prediction of PH 2 hemorrhagic transformation was evaluated by subgroup analysis. In 115 participants, including 70 males (mean (SD) age, 69 (12) years), PH 2 hemorrhagic transformation occurred in 6 participants with very poor collateral-perfusion status (MAC 0). MAC 0 (OR, 0.06; 95% CI, 0.01, 0.74; P = .03) was independently associated with PH 2 hemorrhagic transformation. In 22 participants with MAC 0, the permeable signal on Kep permeability imaging was the only significant characteristic associated with PH 2 hemorrhagic transformation (P = .009). The specificity of Kep permeability imaging was 93.8% (95% confidence interval: 69.8, 99.8) in predicting PH 2 hemorrhagic transformation. Individual-based prediction of PH 2 hemorrhagic transformation in patients with acute ischemic stroke may be possible with multiphase collateral map and permeability imaging derived from dynamic contrast material-enhanced magnetic resonance angiography.

Matrix Metalloproteinase-9 Relationship With Infarct Growth and Hemorrhagic Transformation in the Era of Thrombectomy.

Objective: To assess the relationship between matrix metalloproteinase 9 (MMP-9), a proteolytic enzyme involved in the breakdown of the blood-brain barrier, and infarct growth and hemorrhagic transformation in acute ischemic stroke (AIS) with large vessel occlusion (LVO) in the era of mechanical thrombectomy (MT) using the kinetics of MMP-9 and sequential magnetic resonance imaging (MRI).Methods: HIBISCUS-STROKE is a cohort study including AIS patients with LVO treated with MT following admission MRI. Patients underwent sequential assessment of MMP-9, follow-up CT at day 1, and MRI at day 6. The CT scan at day 1 classified any hemorrhagic transformation according to the European Co-operative Acute Stroke Study-II (ECASS II) classification. Infarct growth was defined as the difference between final Fluid-Attenuated Inversion Recovery volume and baseline diffusion-weighted imaging volume. Conditional logistic regression analyses were adjusted for main confounding variables including reperfusion status.Results: One hundred and forty-eight patients represent the study population. A high MMP-9 level at 6 h from admission (H6) (p = 0.02), a high glucose level (p = 0.01), a high temperature (p = 0.04), and lack of reperfusion (p = 0.02) were associated with infarct growth. A high MMP-9 level at H6 (p = 0.03), a high glucose level (p = 0.03) and a long delay from symptom onset to groin puncture (p = 0.01) were associated with hemorrhagic transformation.Conclusions: In this MT cohort study, MMP-9 level at H6 predicts infarct growth and hemorrhagic transformation.

Association Between Coagulation Function and Spontaneous Hemorrhagic Transformation in Acute Ischemic Stroke.

Hemorrhagic transformation (HT) has an adverse effect on the prognosis of patients with acute ischemic stroke, and it is currently known associated with coagulation system. But the conclusion is not consistent and remains to be identified. The aim of this study was to investigate the association between coagulation function and spontaneous hemorrhagic transformation. Patients within 7 days from the onset of ischemic stroke who did not receive reperfusion therapy (thrombolysis or endovascular treatment) were included between January 2016 and October 2017. Coagulation function indicators, including prothrombin time (PT), activated partial thromboplastin time (APTT), international normalized ratio (INR), thrombin time (TT) and fibrinogen (FIB), were tested within 24 h after admission. HT was defined as hemorrhage presented on follow-up magnetic resonance imaging (MRI) or computed tomography (CT) but not on baseline CT. We performed binary logistic regression to examine the association between coagulation function and HT. The coagulation indicators were entered into logistic regression analysis as continuous variables (per 1-unit/L increase) and four-categorized variables (with data collapsed into quartiles), respectively. A total of 1141 patients were included (mean age, 64 ± 15 years; 63.7% males). 102 patients experienced HT (8.9%), of whom 14 patients experienced symptomatic HT (sHT, 1.2%). After adjustment for confounders, TT in the highest quartile is inversely associated with risk of HT (as continuous variable, odds ratio [OR] 0.85; 95% confidence level [CI] 0.73-0.99, P = 0.042; as four-categorized variable, OR 0.36, 95% CI 0.18 - 0.7, P = 0.003). Whether as continuous variables or four-categorized variables, PT, INR, APTT and FIB had no association with HT. Not the whole process of coagulation function is associated with spontaneous HT. Prolonged TT, which may indicate an extension of the last step of the coagulation process, is independently and inversely associated with spontaneous HT in patients with acute ischemic stroke.

The Role of Hemorrhagic Transformation in Acute Ischemic Stroke Upon Clinical Complications and Outcomes

Background and purposeHemorrhagic transformation (HT) is a common neurological complication after ischemic stroke. The influence of symptomatic HT upon clinical outcomes post-stroke is well established, however, the role of asymptomatic HT upon prognosis is still unclear. We aimed to analyze the relationship between HT, clinical complications and outcomes in patients not submitted to reperfusion therapies (RT). MethodsWe included 448 randomly selected patients admitted with acute ischemic stroke to a tertiary hospital stroke unit from 2015 to 2017. Patients submitted to RT were excluded. All patients were evaluated with computed tomography (CT) at admission and within 7 days from the initial CT. Patients with HT were divided into two groups: symptomatic and asymptomatic cases based on the ECASS II definition. A good clinical outcome was defined as a modified Rankin Scale (mRS) 0-2 at discharge. ResultsA total of 95 patients (21.2%) had HT (51 asymptomatic and 44 symptomatic). Age, NIHSS at admission and symptomatic HT were associated with a higher risk of developing pneumonia and seizures during hospitalization. Symptomatic HT was also associated with a prolonged length of hospitalization and death and inversely associated with good clinical outcomes at discharge (OR 0.96, 95% CI 0.94-0.98, p<0.001). In an adjusted analysis, even asymptomatic HT was independently associated with worse clinical outcomes at discharge (mRS 4-6) (OR 5.99, 95% CI 1.83-19.58, p = 0.003). ConclusionsSymptomatic HT is associated with a higher risk of clinical complications, prolonged hospitalization, death and worse clinical outcome at discharge. Furthermore, even patients with asymptomatic HT had a higher chance of worse clinical outcomes at discharge.