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

Association between CT Perfusion Parameters and Hemorrhagic Transformation after Endovascular Treatment in Acute Ischemic Stroke: Results from the ESCAPE-NA1 Trial

BACKGROUND AND PURPOSE

Hemorrhagic transformation can occur as a complication of endovascular treatment for acute ischemic stroke. This study aimed to determine whether ischemia depth as measured by admission CTP metrics can predict the development of hemorrhagic transformation at 24 hours.

MATERIALS AND METHODS

Patients with baseline CTP and 24-hour follow-up imaging from the ESCAPE-NA1 trial were included. RAPID software was used to generate CTP volume maps for relative CBF, CBV, and time-to-maximum at different thresholds. Hemorrhage on 24-hour imaging was classified according to the Heidelberg system, and volumes were calculated. Univariable and multivariable regression analyses assessed the association between CTP lesion volumes and hemorrhage/hemorrhage subtypes.

RESULTS

Among 408 patients with baseline CTP, 142 (35%) had hemorrhagic transformation at 24-hour follow-up, with 89 (63%) classified as hemorrhagic infarction (HI1/HI2), and 53 (37%), as parenchymal hematoma (PH1/PH2). Patients with HI or PH had larger volumes of low relative CBF and CBV at each threshold compared with those without hemorrhage. After we adjustied for baseline and treatment variables, only increased relative CBF <30% lesion volume was associated with any hemorrhage (adjusted OR, 1.14; 95% CI, 1.02-1.27 per 10 mL), as well as parenchymal hematoma (adjusted OR, 1.23; 95% CI, 1.06-1.43 per 10 mL). No significant associations were observed for hemorrhagic infarction.

CONCLUSIONS

Larger "core" volumes of relative CBF <30% were associated with an increased risk of PH following endovascular treatment. This particular metric, in conjunction with other clinical and imaging variables, may, therefore, help estimate the risk of post-endovascular treatment hemorrhagic complications.

Prediction of cerebral hemorrhagic transformation after thrombectomy using a deep learning of dual-energy CT

OBJECTIVES

To develop and validate a deep learning model for predicting hemorrhagic transformation after endovascular thrombectomy using dual-energy computed tomography (CT).

MATERIALS AND METHODS

This was a retrospective study from a prospective registry of acute ischemic stroke. Patients admitted between May 2019 and February 2023 who underwent endovascular thrombectomy for acute anterior circulation occlusions were enrolled. Hemorrhagic transformation was defined using follow-up magnetic resonance imaging or CT. The deep learning model was developed using post-thrombectomy dual-energy CT to predict hemorrhagic transformation within 72 h. Temporal validation was performed with patients who were admitted after July 2022. The deep learning model's performance was compared with a logistic regression model developed from clinical variables using the area under the receiver operating characteristic curve (AUC).

RESULTS

Total of 202 patients (mean age 71.4 years ± 14.5 [standard deviation], 92 men) were included, with 109 (54.0%) patients having hemorrhagic transformation. The deep learning model performed consistently well, showing an average AUC of 0.867 (95% confidence interval [CI], 0.815-0.902) upon five-fold cross validation and AUC of 0.911 (95% CI, 0.774-1.000) with the test dataset. The clinical variable model showed an AUC of 0.775 (95% CI, 0.709-0.842) on the training dataset (p < 0.01) and AUC of 0.634 (95% CI, 0.385-0.883) on the test dataset (p = 0.06).

CONCLUSION

A deep learning model was developed and validated for prediction of hemorrhagic transformation after endovascular thrombectomy in patients with acute stroke using dual-energy computed tomography.

CLINICAL RELEVANCE STATEMENT

This study demonstrates that a convolutional neural network (CNN) can be utilized on dual-energy computed tomography (DECT) for the accurate prediction of hemorrhagic transformation after thrombectomy. The CNN achieves high performance without the need for region of interest drawing.

KEY POINTS

• Iodine leakage on dual-energy CT after thrombectomy may be from blood-brain barrier disruption. • A convolutional neural network on post-thrombectomy dual-energy CT enables individualized prediction of hemorrhagic transformation. • Iodine leakage is an important predictor of hemorrhagic transformation following thrombectomy for ischemic stroke.

Assessment of Computed Tomography Perfusion Research Landscape: A Topic Modeling Study

The number of scholarly articles continues to rise. The continuous increase in scientific output poses a challenge for researchers, who must devote considerable time to collecting and analyzing these results. The topic modeling approach emerges as a novel response to this need. Considering the swift advancements in computed tomography perfusion (CTP), we deem it essential to launch an initiative focused on topic modeling. We conducted a comprehensive search of the Scopus database from 1 January 2000 to 16 August 2023, to identify relevant articles about CTP. Using the BERTopic model, we derived a group of topics along with their respective representative articles. For the 2020s, linear regression models were used to identify and interpret trending topics. From the most to the least prevalent, the topics that were identified include "Tumor Vascularity", "Stroke Assessment", "Myocardial Perfusion", "Intracerebral Hemorrhage", "Imaging Optimization", "Reperfusion Therapy", "Postprocessing", "Carotid Artery Disease", "Seizures", "Hemorrhagic Transformation", "Artificial Intelligence", and "Moyamoya Disease". The model provided insights into the trends of the current decade, highlighting "Postprocessing" and "Artificial Intelligence" as the most trending topics.

Core and penumbra estimation using deep learning-based AIF in association with clinical measures in computed tomography perfusion (CTP)

OBJECTIVES

To investigate whether utilizing a convolutional neural network (CNN)-based arterial input function (AIF) improves the volumetric estimation of core and penumbra in association with clinical measures in stroke patients.

METHODS

The study included 160 acute ischemic stroke patients (male = 87, female = 73, median age = 73 years) with approval from the institutional review board. The patients had undergone CTP imaging, NIHSS and ASPECTS grading. convolutional neural network (CNN) model was trained to fit a raw AIF curve to a gamma variate function. CNN AIF was utilized to estimate the core and penumbra volumes which were further validated with clinical scores.

RESULTS

Penumbra estimated by CNN AIF correlated positively with the NIHSS score (r = 0.69; p < 0.001) and negatively with the ASPECTS (r =  - 0.43; p < 0.001). The CNN AIF estimated penumbra and core volume matching the patient symptoms, typically in patients with higher NIHSS (> 20) and lower ASPECT score (< 5). In group analysis, the median CBF < 20%, CBF < 30%, rCBF < 38%, Tmax > 10 s, Tmax > 10 s volumes were statistically significantly higher (p < .05).

CONCLUSIONS

With inclusion of the CNN AIF in perfusion imaging pipeline, penumbra and core estimations are more reliable as they correlate with scores representing neurological deficits in stroke.

CRITICAL RELEVANCE STATEMENT

With CNN AIF perfusion imaging pipeline, penumbra and core estimations are more reliable as they correlate with scores representing neurological deficits in stroke.

CT perfusion - an up-to-date element of the contemporary multimodal diagnostic approach to acute ischemic stroke

Acute ischemic stroke is of great clinical and societal importance due to its high incidence and mortality rates, as well as the fact that those who are affected suffer from permanent acquired disability. Modern trends explicitly state that the disease's diagnostic plan should use a multidisciplinary approach. The therapeutic steps that ultimately determine the clinical outcome are defined by an accurate diagnosis of acute ischemic stroke. Highly specialized facilities for the diagnosis and treatment of acute ischemic stroke (Stroke Units) are in operation in countries that make significant investments in healthcare. Imaging the brain parenchyma at risk, or the so-called ischemic penumbra, in acute ischemic stroke is one of the main tasks of the multimodal computed tomography approach. The most rapid method for imaging the ischemic penumbra is computed tomography perfusion (CTP). This modality provides information about the anatomy and the physiologic state of the brain parenchyma.

Predictive Value of CT Perfusion in Hemorrhagic Transformation after Acute Ischemic Stroke: A Systematic Review and Meta-Analysis

Background: Existing studies indicate that some computed tomography perfusion (CTP) parameters may predict hemorrhagic transformation (HT) after acute ischemic stroke (AIS), but there is an inconsistency in the conclusions alongside a lack of comprehensive comparison. Objective: To comprehensively evaluate the predictive value of CTP parameters in HT after AIS. Data sources: A systematical literature review of existing studies was conducted up to 1st October 2022 in six mainstream databases that included original data on the CTP parameters of HT and non-HT groups or on the diagnostic performance of relative cerebral blood flow (rCBF), relative permeability-surface area product (rPS), or relative cerebral blood volume (rCBV) in patients with AIS that completed CTP within 24 h of onset. Data Synthesis: Eighteen observational studies were included. HT and non-HT groups had statistically significant differences in CBF, CBV, PS, rCBF, rCBV, and rPS (p < 0.05 for all). The hierarchical summary receiver operating characteristic (HSROC) revealed that rCBF (area under the curve (AUC) = 0.9), rPS (AUC = 0.89), and rCBV (AUC = 0.85) had moderate diagnostic performances in predicting HT. The pooled sensitivity and specificity of rCBF were 0.85 (95% CI, 0.75−0.91) and 0.83 (95% CI, 0.63−0.94), respectively. Conclusions: rCBF, rPS, and rCBV had moderate diagnostic performances in predicting HT, and rCBF had the best pooled sensitivity and specificity.

Clinical application of brain perfusion imaging in detecting stroke mimics: A review

Stroke mimics constitute a significant proportion of patients with suspected acute ischemic stroke. These conditions may resemble acute ischemic stroke and demonstrate abnormalities on perfusion imaging sequences. The most common stroke mimics include seizure/epilepsy, migraine with aura, brain tumors, functional disorders, infectious encephalopathies, Wernicke's encephalopathy, and metabolic abnormalities. Brain perfusion imaging techniques, particularly computed tomography perfusion and magnetic resonance perfusion, are being widely used in routine clinical practice for treatment selection in patients presenting with large vessel occlusion. At the same time, the utilization of these imaging modalities enables the opportunity to better diagnose patients with stroke mimics in a time-sensitive setting, leading to appropriate management, decision-making, and resource allocation. In this review, we describe patterns of perfusion abnormalities that could discriminate patients with stroke mimics from those with acute ischemic stroke and provide specific case examples to illustrate these perfusion abnormalities. In addition, we discuss the challenges associated with interpretation of perfusion images in stroke-related pathologies. In general, perfusion imaging can provide additional information in some cases-when used in combination with conventional magnetic resonance imaging and computed tomography-and might help in detecting stroke mimics among patients who present with acute onset focal neurological symptoms.

Pre-treatment spectral CT combined with CT perfusion can predict hemorrhagic transformation after thrombolysis in patients with acute ischemic stroke

OBJECTIVE

To investigate the value of pre-treatment spectral CT angiography (CTA) in predicting hemorrhagic transformation (HT) after intravenous thrombolysis (IVT) treatment in acute ischemic stroke (AIS) patients.

MATERIALS AND METHODS

AIS patients who underwent IVT with recombinant tissue plasminogen activator and pre-treatment head and neck spectral CTA and head CT perfusion (CTP) from January 2018 to June 2020 were reviewed retrospectively. Finally, 20 patients were included in the HT group and 22 age-matched patients were included in the non-HT group. Spectral and CTP parameters of the region of interest on pre-treatment CTA axial raw images and CTP images, including the infarct core (IC) and ischemic penumbral (IP) regions, were recorded. The differences in clinical variables, CTP, collateral scores and spectral parameters between the two groups were analyzed. Three multivariate logistic regression models were then developed, where model 1 included clinical and spectral parameters, model 2 included clinical and CTP parameters and a combined model included clinical, CTP, and spectral parameters. Receiver operating characteristic analysis was used to evaluate the performance of the multivariate model.

RESULTS

Patients with HT had higher Safe Implementation of Treatments in Stroke (SITS) score (p = 0.023), the volume of perfusion lesions (p = 0.005), the volume of IP (p = 0.003), the mean transit time (MIT) in the IC area (p = 0.012), as well as the TTP in IP area (p = 0.015) compared with patients without HT. The HT group showed significantly lower CBF in the IC area (p = 0.019), iodine concentration (p = 0.017) and the effective atomic number (p = 0.024) in the IP area than non-HT group. And the slope of the spectral curve of the HT group in the IP region was larger than that of the non-HT group (p = 0.023). Gender, age, SITS score, the volume of entire perfusion lesion, CBF and MIT in the IC area, TTP in the IP area, as well as iodine concentration in the IP area were included in the final multivariate model for predicting HT. And CBF in the IC area (OR = 0.779, 95 % CI:0.609-0.996, p = 0.046) as well as the iodine concentration of IP area (OR = 0.343, 95 % CI: 0.131-0.901, p = 0.030) were proved to be independent predictors for HT. The combined model including clinical, spectral, and CTP parameters, showed improved accuracy compared to the other two models, while the Delong test did not suggest a statistically significant difference (both p values > 0.05).

CONCLUSIONS

The iodine concentration of IP area derived from pre-treatment spectral CTA was an independent predictor of HT after IVT treatment for AIS patients. Moreover, multivariate models combined with clinical, spectral, and CTP parameters may be able to predict HT.

Hemorrhagic Transformation Rates following Contrast Media Administration in Patients Hospitalized with Ischemic Stroke

BACKGROUND AND PURPOSE

Hemorrhagic transformation is a critical complication associated with ischemic stroke and has been associated with contrast media administration. The objective of our study was to use real-world in-hospital data to evaluate the correlation between contrast media type and transformation from ischemic to hemorrhagic stroke.

MATERIALS AND METHODS

We obtained data on inpatient admissions with a diagnosis of ischemic stroke and a record of either iso-osmolar or low-osmolar iodinated contrast media for a stroke-related diagnostic test and a treatment procedure (thrombectomy, thrombolysis, or angioplasty). We performed multivariable regression analysis to assess the relationship between contrast media type and the development of hemorrhagic transformation during hospitalization, adjusting for patient characteristics, comorbid conditions, procedure type, a threshold for contrast media volume, and differences across hospitals.

RESULTS

Inpatient visits with exclusive use of either low-osmolar (n = 38,130) or iso-osmolar contrast media (n = 4042) were included. We observed an overall risk reduction in hemorrhagic transformation among patients who received iso-osmolar compared with low-osmolar contrast media, with an absolute risk reduction of 1.4% (P = .032), relative risk reduction of 12.5%, and number needed to prevent harm of 70. This outcome was driven primarily by patients undergoing endovascular thrombectomy (n = 9211), in which iso-osmolar contrast media was associated with an absolute risk reduction of 4.6% (P = .028), a relative risk reduction of 20.8%, and number needed to prevent harm of 22, compared with low-osmolar contrast media.

CONCLUSIONS

Iso-osmolar contrast media was associated with a lower rate of hemorrhagic transformation compared with low-osmolar contrast media in patients with ischemic stroke.

Evaluation and Prediction of Post-stroke Cerebral Edema Based on Neuroimaging

Cerebral edema is a common complication of acute ischemic stroke that leads to poorer functional outcomes and substantially increases the mortality rate. Given that its negative effects can be reduced by more intensive monitoring and evidence-based interventions, the early identification of patients with a high risk of severe edema is crucial. Neuroimaging is essential for the assessment and prediction of edema. Simple markers, such as midline shift and hypodensity volume on computed tomography, have been used to evaluate edema in clinical trials; however, advanced techniques can be applied to examine the underlying mechanisms. In this study, we aimed to review current imaging tools in the assessment and prediction of cerebral edema to provide guidance for using these methods in clinical practice.

Association of cerebral microvascular perfusion and diffusion dynamics detected by intravoxel incoherent motion-diffusion weighted imaging with initial neurological function and clinical outcome in acute ischemic stroke

Background

This work aimed to explore the association of cerebral microvascular perfusion and diffusion dynamics measured by intravoxel incoherent motion (IVIM) imaging with initial neurological function and clinical outcome in acute stroke.

Methods

In total, 39 patients were assessed with admission National Institutes of Health Stroke Scale (NIHSS) and day-90 modified Rankin Scale (mRS). The parametrical maps of IVIM were obtained, including apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*), true diffusion coefficient (D) and perfusion fraction (f). The fD* was the product of f and D*. Moreover, the ratios of lesioned/contralateral parameters (rADC, rD, rD*, rf and rfD*) were also obtained. The differences of these parameters between the poor outcome group and good outcome group were evaluated. Partial correlation analysis was used to evaluate the correlations between the admission NIHSS/day-90 mRS and each parameter ratio, with lesion volumes controlled.

Results

The ADC, D, D*, f and fD* values of lesions were significantly reduced than those of the contralateral regions. The rADC and rD were significantly decreased in the poor outcome group than good outcome group (all p < 0.01). With lesion volume controlled, rADC showed a weak negative correlation (r = −0.340, p = 0.037) and a notable negative correlation (r = −0.688, p < 0.001) with admission NIHSS score and day-90 mRS score, respectively. In addition, rD showed a strong negative correlation (r = −0.731, p < 0.001) with day-90 mRS score.

Conclusion

Significant negative correlations were revealed between IVIM derived diffusion dynamics parameters and initial neurological function as well as clinical outcome for patients with acute ischemic stroke. IVIM can be therefore suggested as an effective non-invasive method for evaluating the acute ischemic stroke.

Predicting hemorrhagic transformation after large vessel occlusion stroke in the era of mechanical thrombectomy

Serum biomarkers are associated with hemorrhagic transformation and brain edema after cerebral infarction. However, whether serum biomarkers predict hemorrhagic transformation in large vessel occlusion stroke even after mechanical thrombectomy, which has become widely used, remains uncertain. In this prospective study, we enrolled patients with large vessel occlusion stroke in the anterior circulation. We analyzed 91 patients with serum samples obtained on admission. The levels of matrix metalloproteinase-9 (MMP-9), amyloid precursor protein (APP) 770, endothelin-1, S100B, and claudin-5 were measured. We examined the association between serum biomarkers and hemorrhagic transformation within one week. Fifty-four patients underwent mechanical thrombectomy, and 17 patients developed relevant hemorrhagic transformation (rHT, defined as hemorrhagic changes ≥ hemorrhagic infarction type 2). Neither MMP-9 (no rHT: 46 ± 48 vs. rHT: 15 ± 4 ng/mL, P = 0.30), APP770 (80 ± 31 vs. 85 ± 8 ng/mL, P = 0.53), endothelin-1 (7.0 ± 25.7 vs. 2.0 ± 2.1 pg/mL, P = 0.42), S100B (13 ± 42 vs. 12 ± 15 pg/mL, P = 0.97), nor claudin-5 (1.7 ± 2.3 vs. 1.9 ± 1.5 ng/mL, P = 0.68) levels on admission were associated with subsequent rHT. When limited to patients who underwent mechanical thrombectomy, the level of claudin-5 was higher in patients with rHT than in those without (1.2 ± 1.0 vs. 2.1 ± 1.7 ng/mL, P = 0.0181). APP770 levels were marginally higher in patients with a midline shift ≥ 5 mm than in those without (79 ± 29 vs. 97 ± 41 ng/mL, P = 0.084). The predictive role of serum biomarkers has to be reexamined in the mechanical thrombectomy era because some previously reported serum biomarkers may not predict hemorrhagic transformation, whereas the level of APP770 may be useful for predicting brain edema.

Study on Model Iterative Reconstruction Algorithm vs. Filter Back Projection Algorithm for Diagnosis of Acute Cerebral Infarction Using CT Images

The aim was to explore the application value of computed tomography (CT) perfusion (CTP) imaging based on the iterative model reconstruction (IMR) in the diagnosis of acute cerebral infarction (ACI). 80 patients with ACI, admitted to hospital, were selected as the research objects and divided randomly into a routine treatment group (group A) and a low-dose group (group B) (each group with 40 patients). Patients in group A were scanned at 80 kV–150 mAs, and the traditional filtered back projection (FBP) algorithm was employed to reconstruct the images; besides, 80 kV–30 mAs was adopted to scan the patients in group B, and the images were reconstructed by IMR1, IMR2, IMR3, iDose4 (a kind of hybrid iterative reconstruction technology), and FBP, respectively. The application values of different algorithms were evaluated by CTP based on the collected CTP images of patients and detecting indicators. The results showed that the gray and white matter CT value, SD value, SNR, CNR, and subjective image scores of patients in group B were basically consistent with those of group A (p > 0.05) after the IMR1 reconstruction, and the CT and SD of gray and white matter in patients from group B reduced steeply (p < 0.05), while SNR and CNR increased dramatically after IMR2 and IMR3 reconstruction in contrast to group A (p < 0.05). Furthermore, the cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT) of contrast agent, and time to peak (TTP) of contrast agent in patients from group B after iDose4 and IMR reconstruction were basically the same as those of group A (p > 0.05). Therefore, IMR combined with low-dose CTP could obtain high-quality CTP images of the brain with stable perfusion indicators and low radiation dose, which could be clinically applied in the diagnosis of ACI.

Value of Perfusion CT in the Prediction of Intracerebral Hemorrhage after Endovascular Treatment

Background

Intracerebral hemorrhage (ICH) is a serious complication of endovascular treatment (EVT) in stroke patients with large vessel occlusion (LVO) and associated with increased morbidity and mortality.

Aims

Identification of radiological predictors is highly relevant. We investigated the predictive power of computed tomography perfusion (CTP) parameters concerning ICH in patients receiving EVT.

Methods

392 patients with anterior circulation LVO with multimodal CT imaging who underwent EVT were analyzed. CTP parameters were visually evaluated for modified ASPECTS regions and compared between patients without ICH, those with hemorrhagic infarction (HI), and those with parenchymal hematoma (PH) according to the ECASS criteria at follow-up imaging and broken down by ASPECTS regions.

Results

168 received intravenous thrombolysis (IV-rtPA), and 115 developed subsequent ICH (29.3%), of which 74 were classified as HI and 41 as PH. Patients with HI and PH had lower ASPECTS than patients without ICH and worse functional outcome after 90 days (p < 0.05). In 102 of the 115 patients with ICH, the deep middle cerebral artery (MCA) territory was affected with differences between patients without ICH, those with HI, and those with PH regarding cerebral blood volume (CBV) and blood-brain barrier permeability measured as flow extraction product (FED) relative to the contralateral hemisphere (p < 0.05). Patients with PH showed larger perfusion CT infarct core than patients without ICH (p < 0.01).

Conclusion

None of the examined CTP parameters was found to be a strong predictor of subsequent ICH. ASPECTS and initial CTP core volume were more reliable and may be useful and even so more practicable to assess the risk of subsequent ICH after EVT.

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.

Post-stroke blood-brain barrier disruption predicts poor outcome in patients enrolled in the ACTION study

BACKGROUND AND PURPOSE

A prior study found a link between post-stroke blood-brain barrier disruption and functional outcomes. The current study aimed to replicate this finding in a cohort of patients recruited in the context of a randomized clinical trial.

METHODS

The ACTION trial was a study of natalizumab in acute stroke patients. Patients with MRI-perfusion weighted imaging (PWI) were included in this post-hoc analysis. Blood-brain permeability images (BBPI) were calculated from the PWI source images. Mean BBPI values from the 24 h time point were compared with modified Rankin scores (mRS) at 5, 30, and 90-day assessments using linear regression. Good functional outcome (mRS< = 1) was compared with mean BBPI using logistic regression.

RESULTS

One hundred and nineteen patients were included in the analysis (median age = 74, 43% female). Higher mean BBPI was associated with worse mRS at 5 days (p = 0.002; r² = 0.078) and 30 days (p = 0.036; r² = 0.039) but did not reach statistical significance at 90 days (p = 0.30; r² = 0.010). When removing high-value outliers, all outcome measures showed a stronger relationship with mean BBPI. Logistic regression found that with every 1% increase in mean BBPI measured 24 h after the stroke, the likelihood of achieving a good functional outcome at 90 days is decreased by half (OR = 0.53; CI = 0.30:0.95; p = 0.032).

CONCLUSIONS

With sufficient image quality, elevated BBPI measured in the days after an ischemic event is predictive of worse functional outcome and may serve as a biomarker for post-stroke inflammation.

Systematic review protocol to assess artificial intelligence diagnostic accuracy performance in detecting acute ischaemic stroke and large-vessel occlusions on CT and MR medical imaging

INTRODUCTION

The use of artificial intelligence (AI) to support the diagnosis of acute ischaemic stroke (AIS) could improve patient outcomes and facilitate accurate tissue and vessel assessment. However, the evidence in published AI studies is inadequate and difficult to interpret which reduces the accountability of the diagnostic results in clinical settings. This study protocol describes a rigorous systematic review of the accuracy of AI in the diagnosis of AIS and detection of large-vessel occlusions (LVOs).

METHODS AND ANALYSIS

We will perform a systematic review and meta-analysis of the performance of AI models for diagnosing AIS and detecting LVOs. We will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols guidelines. Literature searches will be conducted in eight databases. For data screening and extraction, two reviewers will use a modified Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist. We will assess the included studies using the Quality Assessment of Diagnostic Accuracy Studies guidelines. We will conduct a meta-analysis if sufficient data are available. We will use hierarchical summary receiver operating characteristic curves to estimate the summary operating points, including the pooled sensitivity and specificity, with 95% CIs, if pooling is appropriate. Furthermore, if sufficient data are available, we will use Grading of Recommendations, Assessment, Development and Evaluations profiler software to summarise the main findings of the systematic review, as a summary of results.

ETHICS AND DISSEMINATION

There are no ethical considerations associated with this study protocol, as the systematic review focuses on the examination of secondary data. The systematic review results will be used to report on the accuracy, completeness and standard procedures of the included studies. We will disseminate our findings by publishing our analysis in a peer-reviewed journal and, if required, we will communicate with the stakeholders of the studies and bibliographic databases.

PROSPERO REGISTRATION NUMBER

CRD42020179652.

Intracranial Bleeding After Reperfusion Therapy in Acute Ischemic Stroke

Intracranial hemorrhage is one of the most feared complications following brain infarct. Ischemic tissues have a natural tendency to bleed. Moreover, the first recanalization trials using intravenous thrombolysis have shown an increase in mild to severe intracranial hemorrhage. Symptomatic intracerebral hemorrhage is strongly associated with poor outcomes and is an important factor in recanalization decisions. Stroke physicians have to weigh the potential benefit of recanalization therapies, first, with different risks of intracranial hemorrhage described in randomized controlled trials, and second with numerous risk markers that have been found to be associated with intracranial hemorrhage in retrospective series. These decisions have become quite complex with different intravenous thrombolytics and mechanical thrombectomy. This review aims to outline some elements of the pathophysiological mechanisms and classifications, describe most of the risk factors identified for each reperfusion therapy, and finally suggest future research directions that could help physicians dealing with these complications.

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.

Pathophysiology of Blood-Brain Barrier Permeability Throughout the Different Stages of Ischemic Stroke and Its Implication on Hemorrhagic Transformation and Recovery

The blood–brain barrier (BBB) is a dynamic interface responsible for maintaining the central nervous system homeostasis. Its unique characteristics allow protecting the brain from unwanted compounds, but its impairment is involved in a vast number of pathological conditions. Disruption of the BBB and increase in its permeability are key in the development of several neurological diseases and have been extensively studied in stroke. Ischemic stroke is the most prevalent type of stroke and is characterized by a myriad of pathological events triggered by an arterial occlusion that can eventually lead to fatal outcomes such as hemorrhagic transformation (HT). BBB permeability seems to follow a multiphasic pattern throughout the different stroke stages that have been associated with distinct biological substrates. In the hyperacute stage, sudden hypoxia damages the BBB, leading to cytotoxic edema and increased permeability; in the acute stage, the neuroinflammatory response aggravates the BBB injury, leading to higher permeability and a consequent risk of HT that can be motivated by reperfusion therapy; in the subacute stage (1–3 weeks), repair mechanisms take place, especially neoangiogenesis. Immature vessels show leaky BBB, but this permeability has been associated with improved clinical recovery. In the chronic stage (>6 weeks), an increase of BBB restoration factors leads the barrier to start decreasing its permeability. Nonetheless, permeability will persist to some degree several weeks after injury. Understanding the mechanisms behind BBB dysregulation and HT pathophysiology could potentially help guide acute stroke care decisions and the development of new therapeutic targets; however, effective translation into clinical practice is still lacking. In this review, we will address the different pathological and physiological repair mechanisms involved in BBB permeability through the different stages of ischemic stroke and their role in the development of HT and stroke recovery.

Permeability of the blood-brain barrier through the phases of ischaemic stroke and relation with clinical outcome: protocol for a systematic review

INTRODUCTION

Ischaemic stroke is the most prevalent type of stroke and is characterised by a myriad of pathological events triggered by a vascular arterial occlusion. Disruption of the blood-brain barrier (BBB) is a key pathological event that may lead to fatal outcomes. However, it seems to follow a multiphasic pattern that has been associated with distinct biological substrates and possibly contrasting outcomes. Addressing the BBB permeability (BBBP) along the different phases of stroke through imaging techniques could lead to a better understanding of the disease, improved patient selection for specific treatments and development of new therapeutic modalities and delivery methods. This systematic review will aim to comprehensively summarise the existing evidence regarding the evolution of the BBBP values during the different phases of an acute ischaemic stroke and correlate this event with the clinical outcome of the patient.

METHODS AND ANALYSIS

We will conduct a computerised search on Medline, EMBASE, Cochrane Central Register of Controlled Trials, Scopus and Web of Science. In addition, grey literature and ClinicalTrials.gov will be scanned. We will include randomised controlled trials, cohort, cross-sectional and case-controlled studies on humans that quantitatively assess the BBBP in stroke. Retrieved studies will be independently reviewed by two authors and any discrepancies will be resolved by consensus or with a third reviewer. Reviewers will extract the data and assess the risk of bias of the selected studies. If possible, data will be combined in a quantitative meta-analysis following the guidelines provided by Cochrane Handbook for Systematic Reviews of Interventions. We will assess cumulative evidence using the Grading of Recommendations, Assessment, Development and Evaluation approach.

ETHICS AND DISSEMINATION

Ethical approval is not needed. All data used for this work are publicly available. The result obtained from this work will be published in a peer-reviewed journal and disseminated in relevant conferences.

PROSPERO REGISTRATION NUMBER

CRD42019147314.