Focal Low and Global High Permeability Predict the Possibility, Risk, and Location of Hemorrhagic Transformation following Intra-Arterial Thrombolysis Therapy in Acute Stroke

Blood-brain barrier permeability by CT perfusion predicts parenchymal hematoma after recanalization with thrombectomy

BACKGROUND AND PURPOSE

Parenchymal hematoma is a dreaded complication of mechanical thrombectomy after acute ischemic stroke. This study evaluated whether blood-brain barrier permeability measurements based on CT perfusion could be used as predictors of parenchymal hematoma after successful recanalization and compared the predictive value of various permeability parameters in patients with acute ischemic stroke.

METHODS

We enrolled 53 patients with acute ischemic stroke who underwent mechanical thrombectomy and achieved successful recanalization. Each patient underwent CT, CT angiography, and CT perfusion imaging before treatment. We used relative volume transfer constant (rKtrans ) values, relative permeability-surface area product (rP·S), and relative extraction fraction (rE) to evaluate preoperative blood-brain barrier permeability in the delayed perfusion area.

RESULTS

Overall, 22 patients (37.7%) developed hemorrhagic transformation after surgery, including 10 patients (16.9%) with hemorrhagic infarction and 11 patients (20.8%) with parenchymal hematoma. The rP·S, rKtrans , and rE of the hypoperfusion area in the parenchymal hematoma group were significantly higher than those in the hemorrhagic infarction and no-hemorrhage transformation groups (p < .01). We found that rE and rP·S were superior to rKtrans in predicting parenchymal hematoma transformation after thrombectomy (P·S area under the curve [AUC] .844 vs. rKtrans AUC .753, z = 2.064, p = .039; rE AUC .907 vs. rKtrans AUC .753, z = 2.399, p = .017).

CONCLUSIONS

Patients with parenchymal hematoma after mechanical thrombectomy had higher blood-brain barrier permeability in hypoperfusion areas. Among blood-brain barrier permeability measurement parameters, rP·S and rE showed better accuracy for parenchymal hematoma prediction.

Microvascular dysfunction associated with unfavorable venous outflow in acute ischemic stroke patients

Unfavorable venous outflow (VO) is associated with cerebral edema, which represents microvascular dysfunction. This study estimated the relationship between VO and microvascular function in acute ischemic stroke patients. We retrospectively included 102 MCA/ICA occluded patients with anterior circulation infarction who underwent reperfusion therapy between July 2017 and April 2022. Unfavorable VO was defined as a cortical vein opacification score of 0-3 and favorable VO as that of 4-6. The clinical characteristics, collateral status, microvascular integrity, and outcomes were compared between patients with favorable and unfavorable VO. Multivariate analysis and receiver operator characteristic (ROC) analysis were used. The patients with unfavorable VO had higher extravascular-extracellular volume fraction (Ve) in the infarct core and a lower percentage of robust arterial collateral circulation. ROC analysis revealed that Ve in the infarct core predicts unfavorable VO (AUC = 0.67, sensitivity = 65.08%, specificity = 69.23%). The higher Ve in the infarct core (odds ratio = 1.011, 95% CI = 1.000-1.021, P = 0.046) and poor arterial collateral flow (odds ratio = 0.102, 95% CI = 0.032-0.327, P < 0.001) were independent predictors of unfavorable VO. This suggests that microvascular dysfunction may be one of the mechanisms underlying impaired VO.

Serum S-100B adds incremental value for the prediction of symptomatic intracranial hemorrhage and brain edema after acute ischemic stroke

Background:

Early identification of patients developing symptomatic intracranial hemorrhage and symptomatic brain edema after acute ischemic stroke is essential for clinical decision-making. Astroglial protein S-100B is a marker of blood-brain barrier disruption, which plays an important role in the formation of intracranial hemorrhage and brain edema. In this study, we assessed the prognostic value of serum S-100B for the development of these complications.

Methods:

Serum S-100B levels were measured within 24 h from symptom onset in 1749 consecutive acute ischemic stroke patients from the prospective, observational, multicenter BIOSIGNAL cohort study (mean age 72.0 years, 58.3% male). To determine symptomatic intracranial hemorrhage or symptomatic brain edema, follow-up neuroimaging was performed in all patients receiving reperfusion therapy or experiencing clinical worsening with an NIHSS increase of ⩾4.

Results:

Forty six patients (2.6%) developed symptomatic intracranial hemorrhage and 90 patients (5.2%) developed symptomatic brain edema. After adjustment for established risk factors, log10S-100B levels remained independently associated with both symptomatic intracranial hemorrhage (OR 3.41, 95% CI 1.7–6.9, p = 0.001) and symptomatic brain edema (OR 4.08, 95% CI 2.3–7.1, p < 0.001) in multivariable logistic regression models. Adding S-100B to the clinical prediction model increased the AUC from 0.72 to 0.75 ( p = 0.001) for symptomatic intracranial hemorrhage and from 0.78 to 0.81 ( p < 0.0001) for symptomatic brain edema.

Conclusions:

Serum S-100B levels measured within 24 h after symptom onset are independently associated with the development of symptomatic intracranial hemorrhage and symptomatic brain edema in acute ischemic stroke patients. Thus, S-100B may be useful for early risk-stratification regarding stroke complications.

Prognostic Value of a New Integrated Parameter-Both Collateral Circulation and Permeability Surface-in Hemorrhagic Transformation of Middle Cerebral Artery Occlusion Acute Ischemic Stroke: Retrospective Cohort Study

Background

Multimodal CT, including CT angiography (CTA) and CT perfusion (CTP), was increasingly used in stroke triage. This study was to determine the relationship between a new integrated parameter—both collateral circulation and relative permeability surface (PS)—and the hemorrhagic transformation (HT) in acute ischemic stroke (AIS) with middle cerebral artery occlusion (MCAO).

Methods

We retrospectively reviewed consecutive AIS patients with MCAO who underwent baseline CTA/CTP within 4 h of symptom onset and follow-up susceptibility-weighted imaging (SWI) within 3 weeks. Collateral circulation was assessed on the baseline CTA. Baseline CTP data were postprocessed to generate PS parameter. The patients with poor collateral circulation and at the same time with high relative PS were classified as the group of both poor collateral circulation and high relative PS. HT was defined according to European Cooperative Acute Stroke Study II criteria on follow-up SWI imaging. Multivariate logistic regression analysis was performed using HT as an outcome variable.

Results

The group of patients with both poor collateral circulation and high relative PS was thirteen and thirty-three (52%) developed HT of the final cohort sixty-three AIS patients with MCAO. Multivariate logistic analysis revealed the new integrated parameter—both collateral circulation and relative PS (odds ratio, 16.59; 95% confidence interval, 13.09–19.10; P < 0.001) was independent predictor of HT. The area under the curve was 0.85 (95% confidence interval, 0.81–0.89). The sensitivity was 57%, specificity 97% and positive predictive value 92%, negative predictive value 58%.

Conclusions

For AIS patients with MCAO, these with poor collateral circulation on CTA and at the same time with high relative PS on CTP were at high risk for HT.

Blood-brain barrier leakage and hemorrhagic transformation: The Reperfusion Injury in Ischemic StroKe (RISK) study

BACKGROUND AND PURPOSE

In patients with acute ischemic stroke treated with reperfusion therapy we aimed to evaluate whether pretreatment blood-brain barrier (BBB) leakage is associated with subsequent hemorrhagic transformation (HT).

METHODS

We prospectively screened patients with acute ischemic stroke treated with intravenous thrombolysis and/or endovascular treatment. Before treatment, each patient received computed tomography (CT), CT angiography, and CT perfusion. We assessed pretreatment BBB leakage within the ischemic area using the volume transfer constant (K^trans ) value. Our primary outcome was relevant HT, defined as hemorrhagic infarction type 2 or parenchymal hemorrhage type 1 or 2. We evaluated independent associations between BBB leakage and HT using logistic regression, adjusting for age, sex, baseline stroke severity, Alberta Stroke Program Early CT Score (ASPECTS) ≥ 6, treatment type, and onset-to-treatment time.

RESULTS

We enrolled 171 patients with available assessment of BBB leakage. The patients' mean (±SD) age was 75.5 (±11.8) years, 86 (50%) were men, and the median (interquartile range) National Institutes of Health Stroke Scale score was 18 (12-23). A total of 32 patients (18%) received intravenous thrombolysis, 102 (60%) underwent direct endovascular treatment, and 37 (22%) underwent both. Patients with relevant HT (N = 31;18%) had greater mean BBB leakage (K^trans 0.77 vs. 0.60; p = 0.027). After adjustment in the logistic regression model, we found that BBB leakage was associated both with a more than twofold risk of relevant HT (odds ratio [OR] 2.50; 95% confidence interval [CI] 1.03-6.03 per K^trans point increase; OR 2.34; 95% CI 1.06-5.17 for K^trans values > 0.63 [mean BBB leakage value]) and with symptomatic intracerebral hemorrhage (OR 4.30; 95% CI 1.13-13.77 per K^trans point increase).

CONCLUSION

Pretreatment BBB leakage before reperfusion therapy was associated with HT, and may help to identify patients at risk of HT.

Advances in imaging acute ischemic stroke: evaluation before thrombectomy

Recent advances in neuroimaging have demonstrated significant assessment benefits and appropriate triage of patients based on specific clinical and radiological features in the acute stroke setting. Endovascular thrombectomy is arguably the most important aspect of acute stroke management with an extended time window. Imaging-based physiological information may potentially shift the treatment paradigm from a rigid time-based model to a more flexible and individualized, tissue-based approach, increasing the proportion of patients amenable to treatment. Various imaging modalities are routinely used in the diagnosis and management of acute ischemic stroke, including multimodal computed tomography (CT) and magnetic resonance imaging (MRI). Therefore, these imaging methods should provide information beyond the presence or absence of intracranial hemorrhage as well as the presence and extent of the ischemic core, collateral circulation and penumbra in patients with neurological symptoms. Target mismatch may optimize selection of patients with late or unknown symptom onset who would potentially be eligible for revascularization therapy. The purpose of this study was to provide a comprehensive review of the current evidence about efficacy and theoretical basis of present imaging modalities, and explores future directions for imaging in the management of acute ischemic stroke.

Blood-Brain Barrier Disruption and Hemorrhagic Transformation in Acute Ischemic Stroke: Systematic Review and Meta-Analysis

Introduction: Hemorrhagic transformation (HT) is a complication of reperfusion therapy for acute ischemic stroke. Blood–brain barrier (BBB) disruption is a crucial step toward HT; however, in clinical studies, there is still uncertainty about this relation. Hence, we conducted a systematic review and meta-analysis to summarize the current evidence.

Methods: We performed systematic review and meta-analysis of observational studies from January 1990 to March 2020 about the relation between BBB disruption and HT in patients with acute ischemic stroke with both computed tomography (CT) and magnetic resonance (MR) assessment of BBB. The outcome of interest was HT at follow-up imaging evaluation (within 48 h from symptom onset). We pooled data from available univariate odds ratios (ORs) in random-effects models with DerSimonian–Laird weights and extracted cumulative ORs.

Results: We included 30 eligible studies (14 with CT and 16 with MR), N = 2,609 patients, with 88% and 70% of patients included in CT and MR studies treated with acute stroke therapy, respectively. The majority of studies were retrospective and had high or unclear risk of bias. BBB disruption was measured with consistent methodology in CT studies, whereas in MR studies, there was more variability. All CT studies provided a BBB disruption cutoff predictive of HT. Four CT and 10 MR studies were included in the quantitative analysis. We found that BBB disruption was associated with HT with both CT (OR = 3.42; 95%CI = 1.62–7.23) and MR (OR = 9.34; 95%CI = 3.16–27.59). There was a likely publication bias particularly for MR studies.

Conclusion: Our results confirm that BBB disruption is associated with HT in both CT and MR studies. Compared with MR, CT has been more uniformly applied in the literature and has resulted in more consistent results. However, more efforts are needed for harmonization of protocols and methodology for implementation of BBB disruption as a neuroradiological marker in clinical practice.

Perfusion CT for prediction of hemorrhagic transformation in acute ischemic stroke: a systematic review and meta-analysis

OBJECTIVE

To investigate the diagnostic performance of perfusion CT for prediction of hemorrhagic transformation in acute ischemic stroke.

METHODS

A computerized literature search of Ovid MEDLINE and EMBASE was conducted up to October 29, 2018. Search terms included acute ischemic stroke, hemorrhagic transformation, and perfusion CT. Studies assessing the diagnostic performance of perfusion CT for prediction of hemorrhagic transformation in acute ischemic stroke were included. Two reviewers independently evaluated the eligibility of the studies. A bivariate random effects model was used to calculate the pooled sensitivity and pooled specificity. Multiple subgroup analyses were performed.

RESULTS

Fifteen original articles with a total of 1134 patients were included. High blood-brain barrier permeability and hypoperfusion status derived from perfusion CT are associated with hemorrhagic transformation. The pooled sensitivity and specificity were 84% (95% CI, 71-91%) and 74% (95% CI, 67-81%), respectively. The area under the hierarchical summary receiver operating characteristic curve was 0.84 (95% CI, 0.81-0.87). The Higgins I² statistic demonstrated that heterogeneity was present in the sensitivity (I² = 80.21%) and specificity (I² = 85.94%).

CONCLUSION

Although various perfusion CT parameters have been used across studies, the current evidence supports the use of perfusion CT to predict hemorrhagic transformation in acute ischemic stroke.

KEY POINTS

• High blood-brain barrier permeability and hypoperfusion status derived from perfusion CT were associated with hemorrhagic transformation. • Perfusion CT has moderate diagnostic performance for the prediction of hemorrhagic transformation in acute ischemic stroke. • The pooled sensitivity was 84%, and the pooled specificity was 74%.

Prediction of Hemorrhagic Transformation Severity in Acute Stroke From Source Perfusion MRI

OBJECTIVE

Hemorrhagic transformation (HT) is the most severe complication of reperfusion therapy in acute ischemic stroke (AIS) patients. Management of AIS patients could benefit from accurate prediction of upcoming HT. While prediction of HT occurrence has recently provided encouraging results, the prediction of the severity and territory of the HT could bring valuable insights that are beyond current methods.

METHODS

This study tackles these issues and aims to predict the spatial occurrence of HT in AIS from perfusion-weighted magnetic resonance imaging (PWI) combined with diffusion weighted imaging. In all, 165 patients were included in this study and analyzed retrospectively from a cohort of AIS patients treated with reperfusion therapy in a single stroke center.

RESULTS

Machine learning models are compared within our framework; support vector machines, linear regression, decision trees, neural networks, and kernel spectral regression were applied to the dataset. Kernel spectral regression performed best with an accuracy of $\text{83.7} \pm \text{2.6}\%$.

CONCLUSION

The key contribution of our framework formalize HT prediction as a machine learning problem. Specifically, the model learns to extract imaging markers of HT directly from source PWI images rather than from pre-established metrics.

SIGNIFICANCE

Predictions visualized in terms of spatial likelihood of HT in various territories of the brain were evaluated against follow-up gradient recalled echo and provide novel insights for neurointerventionalists prior to endovascular therapy.