Contrast-enhanced MR imaging in acute ischemic stroke: T2* measures of blood-brain barrier permeability and their relationship to T1 estimates and hemorrhagic transformation

Unsupervised Deep Learning for Blood-Brain Barrier Leakage Detection in Diffuse Glioma Using Dynamic Contrast-enhanced MRI

Purpose To develop an unsupervised deep learning framework for generalizable blood-brain barrier leakage detection using dynamic contrast-enhanced MRI, without requiring pharmacokinetic models and arterial input function estimation. Materials and Methods This retrospective study included data from patients who underwent dynamic contrast-enhanced MRI between April 2010 and December 2020. An autoencoder-based anomaly detection approach identified one-dimensional voxel-wise time-series abnormal signals through reconstruction residuals, separating them into residual leakage signals (RLSs) and residual vascular signals. The RLS maps were evaluated and compared with the volume transfer constant (Ktrans) using the structural similarity index and correlation coefficient. Generalizability was tested on subsampled data, and isocitrate dehydrogenase (IDH) status classification performance was assessed using area under the receiver operating characteristic curve (AUC). Results A total of 274 patients (mean age, 54.4 years ± 14.6 [SD]; 164 male) were included in the study. RLS showed high structural similarity (structural similarity index, 0.91 ± 0.02) and correlation (r = 0.56; P < .001) with Ktrans. On subsampled data, RLS maps showed better correlation with RLS values from the original data (0.89 vs 0.72; P < .001), higher peak signal-to-noise ratio (33.09 dB vs 28.94 dB; P < .001), and higher structural similarity index (0.92 vs 0.87; P < .001) compared with Ktrans maps. RLS maps also outperformed Ktrans maps in predicting IDH mutation status (AUC, 0.87 [95% CI: 0.83, 0.91] vs 0.81 [95% CI: 0.76, 0.85]; P = .02). Conclusion The unsupervised framework effectively detected blood-brain barrier leakage without pharmacokinetic models and arterial input function. Keywords: Dynamic Contrast-enhanced MRI, Unsupervised Learning, Feature Detection, Blood-Brain Barrier Leakage Detection Supplemental material is available for this article. © RSNA, 2025 See also commentary by Júdice de Mattos Farina and Kuriki in this issue.

Ischemia-reperfusion injury in a salvaged penumbra: Longitudinal high-tesla perfusion magnetic resonance imaging in a rat model

INTRODUCTION

Although ischemia-reperfusion (I/R) injury varies between cortical and subcortical regions, its effects on specific regions remain unclear. In this study, we used various magnetic resonance imaging (MRI) techniques to examine the spatiotemporal dynamics of I/R injury within the salvaged ischemic penumbra (IP) and reperfused ischemic core (IC) of a rodent model, with the aim of enhancing therapeutic strategies by elucidating these dynamics.

MATERIALS AND METHODS

A total of 17 Sprague-Dawley rats were subjected to 1 h of transient middle cerebral artery occlusion with a suture model. MRI, including diffusion tensor imaging (DTI), T2-weighted imaging, perfusion-weighted imaging, and T1 mapping, was conducted at multiple time points for up to 5 days during the I/R phases. The spatiotemporal dynamics of blood-brain barrier (BBB) modifications were characterized through changes in T1 within the IP and IC regions and compared with mean diffusivity (MD), T2, and cerebral blood flow.

RESULTS

During the I/R phases, the MD of the IC initially decreased, normalized after recanalization, decreased again at 24 h, and peaked on day 5. By contrast, the IP remained relatively stable. Both the IP and IC exhibited hyperperfusion, with the IP reaching its peak at 24 h, followed by resolution, whereas hyperperfusion was maintained in the IC until day 5. Despite hyperperfusion, the IP maintained an intact BBB, whereas the IC experienced persistent BBB leakage. At 24 h, the IC exhibited an increase in the T2 signal, corresponding to regions exhibiting BBB disruption at 5 days.

CONCLUSIONS

Hyperperfusion and BBB impairment have distinct patterns in the IP and IC. Quantitative T1 mapping may serve as a supplementary tool for the early detection of malignant hyperemia accompanied by BBB leakage, aiding in precise interventions after recanalization. These findings underscore the value of MRI markers in monitoring ischemia-specific regions and customizing therapeutic strategies to improve patient outcomes.

Blood-Brain Barrier Disruption and Imaging Assessment in Stroke

Disruption of the blood-brain barrier (BBB) is an important pathological hallmark of ischemic stroke. Blood-brain barrier disruption (BBBD) is a consequence of ischemia and may also exacerbate damage to brain parenchyma. Therefore, maintaining BBB integrity is critical for the central nervous system (CNS) homeostasis. This review offers a concise overview of BBB structure and function, along with the mechanisms underlying its impairment following a stroke. In addition, we review the recent imaging techniques employed to study blood-brain barrier permeability (BBBP) in the context of ischemic brain injury with the goal of providing imaging guidance for stroke diagnosis and treatment from the perspective of the BBBD. This knowledge is vital for developing strategies to safeguard the BBB during cerebral ischemia.

A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patients

BACKGROUND

Haemorrhage transformation (HT) is a serious complication of intravenous thrombolysis (IVT) in acute ischaemic stroke (AIS). Accurate and timely prediction of the risk of HT before IVT may change the treatment decision and improve clinical prognosis. We aimed to develop a deep learning method for predicting HT after IVT for AIS using noncontrast computed tomography (NCCT) images.

METHODS

We retrospectively collected data from 828 AIS patients undergoing recombinant tissue plasminogen activator (rt-PA) treatment within a 4.5-h time window (n = 665) or of undergoing urokinase treatment within a 6-h time window (n = 163) and divided them into the HT group (n = 69) and non-HT group (n = 759). HT was defined based on the criteria of the European Cooperative Acute Stroke Study-II trial. To address the problems of indiscernible features and imbalanced data, a weakly supervised deep learning (WSDL) model for HT prediction was constructed based on multiple instance learning and active learning using admission NCCT images and clinical information in addition to conventional deep learning models. Threefold cross-validation and transfer learning were performed to confirm the robustness of the network. Of note, the predictive value of the commonly used scales in clinics associated with NCCT images (i.e., the HAT and SEDAN score) was also analysed and compared to measure the feasibility of our proposed DL algorithms.

RESULTS

Compared to the conventional DL and ML models, the WSDL model had the highest AUC of 0.799 (95% CI 0.712-0.883). Significant differences were observed between the WSDL model and five ML models (P < 0.05). The prediction performance of the WSDL model outperforms the HAT and SEDAN scores at the optimal operating point (threshold = 1.5). Further subgroup analysis showed that the WSDL model performed better for symptomatic intracranial haemorrhage (AUC = 0.833, F1 score = 0.909).

CONCLUSIONS

Our WSDL model based on NCCT images had relatively good performance for predicting HT in AIS and may be suitable for assisting in clinical treatment decision-making.

Contributions of blood-brain barrier imaging to neurovascular unit pathophysiology of Alzheimer's disease and related dementias

The blood-brain barrier (BBB) plays important roles in the maintenance of brain homeostasis. Its main role includes three kinds of functions: (1) to protect the central nervous system from blood-borne toxins and pathogens; (2) to regulate the exchange of substances between the brain parenchyma and capillaries; and (3) to clear metabolic waste and other neurotoxic compounds from the central nervous system into meningeal lymphatics and systemic circulation. Physiologically, the BBB belongs to the glymphatic system and the intramural periarterial drainage pathway, both of which are involved in clearing interstitial solutes such as β-amyloid proteins. Thus, the BBB is believed to contribute to preventing the onset and progression for Alzheimer's disease. Measurements of BBB function are essential toward a better understanding of Alzheimer's pathophysiology to establish novel imaging biomarkers and open new avenues of interventions for Alzheimer's disease and related dementias. The visualization techniques for capillary, cerebrospinal, and interstitial fluid dynamics around the neurovascular unit in living human brains have been enthusiastically developed. The purpose of this review is to summarize recent BBB imaging developments using advanced magnetic resonance imaging technologies in relation to Alzheimer's disease and related dementias. First, we give an overview of the relationship between Alzheimer's pathophysiology and BBB dysfunction. Second, we provide a brief description about the principles of non-contrast agent-based and contrast agent-based BBB imaging methodologies. Third, we summarize previous studies that have reported the findings of each BBB imaging method in individuals with the Alzheimer's disease continuum. Fourth, we introduce a wide range of Alzheimer's pathophysiology in relation to BBB imaging technologies to advance our understanding of the fluid dynamics around the BBB in both clinical and preclinical settings. Finally, we discuss the challenges of BBB imaging techniques and suggest future directions toward clinically useful imaging biomarkers for Alzheimer's disease and related dementias.

MRI-guided thrombolysis for lenticulostriate artery stroke within 12 h of symptom onset

Stroke thrombolysis treatment is generally administered within 4.5 h, but a greater time window may be permitted depending upon the ischemic penumbra on neuroimaging. This observational cohort study investigated the outcomes of thrombolysis given within 12 h after symptom onset of lenticulostriate artery stroke. The population comprised 160 patients. Thrombolysis was administered via tissue plasminogen activator, alteplase (TPA). Thrombolysis was indicated by a mismatch between diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI), that is, an acute ischemic lesion on DWI without a corresponding lesion on T2WI. Demographics and medical history were compared with the modified Rankin scale (mRS) score, to reflect outcome. Patients with a favorable clinical outcome (mRS 0–1) had significantly lower hypertension, baseline NIH Stroke Scale (NIHSS) score, and admission systolic/diastolic blood pressure compared with patients with mRS 2–6. Lower admission systolic blood pressure and NIHSS score were significantly associated with favorable outcome. In patients either with IV-TPA within 4.5 h, or between 4.5 and 12 h, lower admission systolic blood pressure and/or NIHSS score similarly independently predict favorable outcome. However, in all groups, the onset-to-treatment time did not significantly influence the outcomes. We conclude that in our cohort higher admission systolic blood pressure and higher baseline NIHSS and not time were associated with poor outcome in patients with magnetic resonance-guided thrombolysis within 12 h of isolated lenticulostriate artery stroke, therefore loosening the traditionally perceived dependency of outcome on time.

Neuroimaging Prediction of Hemorrhagic Transformation for Acute Ischemic Stroke

BACKGROUND

Hemorrhagic transformation (HT) is a common complication of acute ischemic stroke, often resulting from reperfusion therapy. Early prediction of HT can enable stroke neurologists to undertake measures to avoid clinical deterioration and make optimal treatment strategies. Moreover, the trend of extending the time window for reperfusion therapy (both for intravenous thrombolysis and endovascular treatment) further requires more precise detection of HT tendency.

SUMMARY

In this review, we summarized and discussed the neuroimaging markers of HT prediction of acute ischemic stroke patients, mainly focusing on neuroimaging markers of ischemic degree and neuroimaging markers of blood-brain barrier permeability. This review is aimed to provide a concise introduction of HT prediction and to elicit possibilities of future research combining advanced technology to improve the accessibility and accuracy of HT prediction under emergent clinical settings. Key Messages: Substantial studies have utilized neuroimaging, blood biomarkers, and clinical variables to predict HT occurrence. Although huge progress has been made, more individualized and precise HT prediction using simple and robust imaging predictors combining stroke onset time should be the future goal of development.

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.

A Comprehensive View on MRI Techniques for Imaging Blood-Brain Barrier Integrity

The blood-brain barrier (BBB) is the interface between the blood and brain tissue, which regulates the maintenance of homeostasis within the brain. Impaired BBB integrity is increasingly associated with various neurological diseases. To gain a better understanding of the underlying processes involved in BBB breakdown, magnetic resonance imaging (MRI) techniques are highly suitable for noninvasive BBB assessment. Commonly used MRI techniques to assess BBB integrity are dynamic contrast-enhanced and dynamic susceptibility contrast MRI, both relying on leakage of gadolinium-based contrast agents. A number of conceptually different methods exist that target other aspects of the BBB. These alternative techniques make use of endogenous markers, such as water and glucose, as contrast media. A comprehensive overview of currently available MRI techniques to assess the BBB condition is provided from a scientific point of view, including potential applications in disease. Improvements that are required to make these techniques clinically more easily applicable will also be discussed.

Blood-Brain Barrier Disruption in Mild Traumatic Brain Injury Patients with Post-Concussion Syndrome: Evaluation with Region-Based Quantification of Dynamic Contrast-Enhanced MR Imaging Parameters Using Automatic Whole-Brain Segmentation

Objective

This study aimed to investigate the blood-brain barrier (BBB) disruption in mild traumatic brain injury (mTBI) patients with post-concussion syndrome (PCS) using dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging and automatic whole brain segmentation.

Materials and Methods

Forty-two consecutive mTBI patients with PCS who had undergone post-traumatic MR imaging, including DCE MR imaging, between October 2016 and April 2018, and 29 controls with DCE MR imaging were included in this retrospective study. After performing three-dimensional T1-based brain segmentation with FreeSurfer software (Laboratory for Computational Neuroimaging), the mean K^trans and v_p from DCE MR imaging (derived using the Patlak model and extended Tofts and Kermode model) were analyzed in the bilateral cerebral/cerebellar cortex, bilateral cerebral/cerebellar white matter (WM), and brainstem. K^trans values of the mTBI patients and controls were calculated using both models to identify the model that better reflected the increased permeability owing to mTBI (tendency toward higher K^trans values in mTBI patients than in controls). The Mann-Whitney U test and Spearman rank correlation test were performed to compare the mean K^trans and v_p between the two groups and correlate K^trans and v_p with neuropsychological tests for mTBI patients.

Results

Increased permeability owing to mTBI was observed in the Patlak model but not in the extended Tofts and Kermode model. In the Patlak model, the mean K^trans in the bilateral cerebral cortex was significantly higher in mTBI patients than in controls (p = 0.042). The mean v_p values in the bilateral cerebellar WM and brainstem were significantly lower in mTBI patients than in controls (p = 0.009 and p = 0.011, respectively). The mean K^trans of the bilateral cerebral cortex was significantly higher in patients with atypical performance in the auditory continuous performance test (commission errors) than in average or good performers (p = 0.041).

Conclusion

BBB disruption, as reflected by the increased K^trans and decreased v_p values from the Patlak model, was observed throughout the bilateral cerebral cortex, bilateral cerebellar WM, and brainstem in mTBI patients with PCS.

Radiological predictors of hemorrhagic transformation after acute ischemic stroke: An evidence-based analysis

Hemorrhagic transformation (HT) is one of the most common adverse events related to acute ischemic stroke (AIS) that affects the treatment plan and clinical outcome. Identification of a sensitive radiological marker may influence the controversial thrombolytic decision in the setting of AIS and may at a minimum indicate more intensive monitoring or further prophylactic interventions. In this article we summarize possible radiological biomarkers and the role of different radiological modalities including computed tomography (CT), magnetic resonance imaging, angiography, and ultrasound in predicting HT. Different radiological indices of early ischemic changes, large ischemic lesion volume, severe blood flow restriction, blood-brain barrier disruption, poor collaterals and high blood flow velocities have been reported to be associated with higher risk of HT. The current levels of evidence of the available studies highlight the role of the different CT perfusion parameters in predicting HT. Further large standardized studies are recommended to compare the sensitivity and specificity of the different radiological markers combined and delineate the most reliable predictor.

Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration

INTRODUCTION

Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease.

METHODS

Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis.

RESULTS

A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository.

CONCLUSIONS

The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Quantifying blood-brain barrier leakage in small vessel disease: Review and consensus recommendations

Cerebral small vessel disease (cSVD) comprises pathological processes of the small vessels in the brain that may manifest clinically as stroke, cognitive impairment, dementia, or gait disturbance. It is generally accepted that endothelial dysfunction, including blood-brain barrier (BBB) failure, is pivotal in the pathophysiology. Recent years have seen increasing use of imaging, primarily dynamic contrast-enhanced magnetic resonance imaging, to assess BBB leakage, but there is considerable variability in the approaches and findings reported in the literature. Although dynamic contrast-enhanced magnetic resonance imaging is well established, challenges emerge in cSVD because of the subtle nature of BBB impairment. The purpose of this work, authored by members of the HARNESS Initiative, is to provide an in-depth review and position statement on magnetic resonance imaging measurement of subtle BBB leakage in clinical research studies, with aspects requiring further research identified. We further aim to provide information and consensus recommendations for new investigators wishing to study BBB failure in cSVD and dementia.

Histogram analysis of T2*-based pharmacokinetic imaging in cerebral glioma grading

BACKGROUND AND OBJECTIVE

To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (K^trans) for glioma grading and to explore the diagnostic performance of the histogram analysis of K^trans and blood plasma volume (v_p).

METHODS

We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of K^trans and v_p, derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades.

RESULTS

Histogram parameters of K^trans and v_p showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean K^trans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of K^trans and v_p.

CONCLUSIONS

Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor K^trans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors.

Real-time MRI for precise and predictable intra-arterial stem cell delivery to the central nervous system

Stem cell therapy for neurological disorders reached a pivotal point when the efficacy of several cell types was demonstrated in small animal models. Translation of stem cell therapy is contingent upon overcoming the challenge of effective cell delivery to the human brain, which has a volume ∼1000 times larger than that of the mouse. Intra-arterial injection can achieve a broad, global, but also on-demand spatially targeted biodistribution; however, its utility has been limited by unpredictable cell destination and homing as dictated by the vascular territory, as well as by safety concerns. We show here that high-speed MRI can be used to visualize the intravascular distribution of a superparamagnetic iron oxide contrast agent and can thus be used to accurately predict the distribution of intra-arterial administered stem cells. Moreover, high-speed MRI enables the real-time visualization of cell homing, providing the opportunity for immediate intervention in the case of undesired biodistribution.

Detection of Hyperperfusion on Arterial Spin Labeling using Deep Learning

Hyperperfusion detected on arterial spin labeling (ASL) images acquired after acute stroke onset has been shown to correlate with development of subsequent intracerebral hemorrhage. We present in this study a quantitative hyperperfusion detection model that can provide an objective decision support for the interpretation of ASL cerebral blood flow (CBF) maps and rapidly delineate hyperperfusion regions. The detection problem is solved using Deep Learning such that the model relates ASL image patches to the corresponding label (normal or hyperperfused). Our method takes into account the regional intensity values of contralateral hemisphere during the labeling of a pixel. Each input vector is associated to a label corresponding to the presence of hyperperfusion that was manually established by a clinical researcher in Neurology. When compared to the manually established hyperperfusion, the predicted maps reached an accuracy of 97.45 ± 2.49% after crossvalidation. Pattern recognition based on deep learning can provide an accurate and objective measure of hyperperfusion on ASL CBF images and could therefore improve the detection of hemorrhagic transformation in acute stroke patients.

Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability

There is evidence that subtle breakdown of the blood–brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n = 201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a “sham” DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed v_p and K^Trans estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low-permeability states, which has the potential to provide valuable information regarding BBB integrity in a range of diseases. However, absolute values of the resulting tracer kinetic parameters should be interpreted with extreme caution, and the size and influence of signal drift should be measured where possible.

•

We performed DCE-MRI in 201 patients with a range of small vessel disease severity.

•

We tested tracer kinetic model performance via simulations and statistical analysis.

•

The Patlak model was optimal for assessing leakage in normal tissues and lesions.

•

Scanner drift leads to substantial errors in measured tracer kinetic parameters.

•

DCE-MRI measurements of subtle leakage should be interpreted with caution.

Permeability Parameters Measured with Dynamic Contrast-Enhanced MRI: Correlation with the Extravasation of Evans Blue in a Rat Model of Transient Cerebral Ischemia

OBJECTIVE

The purpose of this study was to correlate permeability parameters measured with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using a clinical 3-tesla scanner with extravasation of Evans blue in a rat model with transient cerebral ischemia.

MATERIALS AND METHODS

Sprague-Dawley rats (n = 13) with transient middle cerebral artery occlusion were imaged using a 3-tesla MRI with an 8-channel wrist coil. DCE-MRI was performed 12 hours, 18 hours, and 36 hours after reperfusion. Permeability parameters (K(trans), ve, and vp) from DCE-MRI were calculated. Evans blue was injected after DCE-MRI and extravasation of Evans blue was correlated as a reference with the integrity of the blood-brain barrier. Correlation analysis was performed between permeability parameters and the extravasation of Evans blue.

RESULTS

All permeability parameters (K(trans), ve, and vp) showed a linear correlation with extravasation of Evans blue. Among them, K(trans) showed highest values of both the correlation coefficient and the coefficient of determination (0.687 and 0.473 respectively, p < 0.001).

CONCLUSION

Permeability parameters obtained by DCE-MRI at 3-T are well-correlated with Evans blue extravasation, and K(trans) shows the strongest correlation among the tested parameters.

[Neurovisualisation predictors of malignant cerebral infarction and hemorrhagic transformation]

Neuroimaging plays a central role in the assessment of patients with acute ischemic stroke. Within a few minutes, modern multimodal imaging protocols can provide one with comprehensive information about prognosis, management, and outcome of the disease, and may detect changes in the intracranial structures reflecting severity of the ischemic injury depicted by four Ps: parenchyma (of the brain), pipes (i.e., the cerebral blood vessels), penumbra, and permeability (of the blood brain barrier). In this article, we have reviewed neuroradiological predictors of malignant middle cerebral artery infarction and hemorrhagic transformation in light of the aforementioned four Ps.

Relation between stroke severity, patient characteristics and CT-perfusion derived blood-brain barrier permeability measurements in acute ischemic stroke

Purpose

Increased blood-brain barrier permeability (BBBP) can result from ischemia. In this study the relation between stroke severity, patient characteristics and admission BBBP values measured with CT-perfusion (CTP) was investigated in acute ischemic stroke patients.

Methods

From prospective data of the Dutch Acute Stroke Study 149 patients with a middle cerebral artery stroke and extended CTP were selected. BBBP values were measured in the penumbra and infarct core as defined by CTP thresholds, and in the contra-lateral hemisphere. The relation between stroke (severity) variables and patient characteristics, including early CT signs, dense vessel sign (DVS), time to scan and National Institute of Health Stroke Score (NIHSS), and BBBP parameters in penumbra and infarct core was quantified with regression analysis.

Results

Early CT signs were related to higher BBBP values in the infarct core (B = 0.710), higher ipsi- to contra-lateral BBBP ratios (B = 0.326) and higher extraction ratios in the infarct core (B = 16.938). Females were found to have lower BBBP values in penumbra and infarct core (B = − 0.446 and − 0.776 respectively) and lower extraction ratios in the infarct core (B = − 10.463). If a DVS was present the ipsi- to contra-lateral BBBP ratios were lower (B = − 0.304). There was no relation between NIHSS or time to scan and BBBP values.

Conclusion

Early CT signs are related to higher BBBP values in the infarct core, suggesting that only severe ischemic damage alters BBBP within the first hours after symptom onset.

Assessment of blood-brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review

There is increasing recognition of the importance of blood-brain barrier (BBB) disruption in aging, dementia, stroke and multiple sclerosis in addition to more commonly-studied pathologies such as tumors. Dynamic contrast-enhanced MRI (DCE-MRI) is a method for studying BBB disruption in vivo. We review pathologies studied, scanning protocols and data analysis procedures to determine the range of available methods and their suitability to different pathologies. We systematically review the existing literature up to February 2014, seeking studies that assessed BBB integrity using T1-weighted DCE-MRI techniques in animals and humans in normal or abnormal brain tissues. The literature search provided 70 studies that were eligible for inclusion, involving 417 animals and 1564 human subjects in total. The pathologies most studied are intracranial neoplasms and acute ischemic strokes. There are large variations in the type of DCE-MRI sequence, the imaging protocols and the contrast agents used. Moreover, studies use a variety of different methods for data analysis, mainly based on model-free measurements and on the Patlak and Tofts models. Consequently, estimated K (Trans) values varied widely. In conclusion, DCE-MRI is shown to provide valuable information in a large variety of applications, ranging from common applications, such as grading of primary brain tumors, to more recent applications, such as assessment of subtle BBB dysfunction in Alzheimer's disease. Further research is required in order to establish consensus-based recommendations for data acquisition and analysis and, hence, improve inter-study comparability and promote wider use of DCE-MRI.

Pretreatment blood-brain barrier damage and post-treatment intracranial hemorrhage in patients receiving intravenous tissue-type plasminogen activator

BACKGROUND AND PURPOSE

Early blood-brain barrier damage after acute ischemic stroke has previously been qualitatively linked to subsequent intracranial hemorrhage (ICH). In this quantitative study, it was investigated whether the amount of blood-brain barrier damage evident on pre-tissue-type plasminogen activator MRI scans was related to the degree of post-tissue-type plasminogen activator ICH in patients with acute ischemic stroke.

METHODS

Analysis was performed on a database of patients with acute ischemic stroke provided by the Stroke Imaging Repository (STIR) and Virtual International Stroke Trials Archive (VISTA) Imaging Investigators. Patients with perfusion-weighted imaging lesions>10 mL and negative gradient-recalled echo imaging before intravenous tissue-type plasminogen activator were included. Postprocessing of the perfusion-weighted imaging source images was performed to estimate changes in blood-brain barrier permeability within the perfusion deficit relative to the unaffected hemisphere. Follow-up gradient-recalled echo images were reviewed for evidence of ICH and divided into 3 groups according to European Cooperative Acute Stroke Study (ECASS) criteria: no hemorrhage, hemorrhagic infarction, and parenchymal hematoma.

RESULTS

Seventy-five patients from the database met the inclusion criteria, 28 of whom experienced ICH, of which 19 were classified as hemorrhagic infarction and 9 were classified as parenchymal hematoma. The mean permeability (±SDs), expressed as an index of contrast leakage, was 17.0±8.8% in the no hemorrhage group, 19.4±4.0% in the hemorrhagic infarction group, and 24.6±4.5% in the parenchymal hematoma group. Permeability was significantly correlated with ICH grade in univariate (P=0.007) and multivariate (P=0.008) linear regression modeling.

CONCLUSIONS

A perfusion-weighted imaging-derived index of blood-brain barrier damage measured before intravenous tissue-type plasminogen activator is given is associated with the severity of ICH after treatment in patients with acute ischemic stroke.

Effects of microvascular permeability changes on contrast-enhanced T1 and pharmacokinetic MR imagings after ischemia

BACKGROUND AND PURPOSE

Brain enhancement on contrast-enhanced T1-weighted imaging (CET1-WI) after ischemic stroke is generally accepted as an indicator of the blood-brain barrier disruption. However, this phenomenon usually starts to become visible at the subacute phase. The purpose of this study was to evaluate the time-course profiles of K(trans), cerebral blood volume (vp), and CET1-WI with early detection of blood-brain barrier changes on K(trans) maps and their role for prediction of subsequent hemorrhagic transformation in acute middle cerebral arterial infarct.

METHODS

Twenty-six patients with acute middle cerebral arterial stroke and early spontaneous reperfusion, whose MR images were obtained at predetermined stroke stages, were included. T2*-based MR perfusion-weighted images were acquired using the first-pass pharmacokinetic model to derive K(trans) and vp. Parenchymal enhancement observed on maps of K(trans), vp, and CET1-WI at each stage was compared. Association among these measurements and hemorrhagic transformation was analyzed.

RESULTS

K(trans) map showed significantly higher parenchymal enhancement in ischemic parenchyma as compared with that of vp map and CET1-WI at early stroke stages (P<0.05). The increased K(trans) at acute stage was not associated with parenchymal enhancement in CET1-WI at the same stage. Parenchymal enhancement in CET1-WI started to occur at the late subacute stage and tended to be luxury reperfusion-dependent. Patients with hemorrhagic transformation showed higher mean K(trans) values as compared with patients without hemorrhagic transformation (P=0.02).

CONCLUSIONS

Postischemic brain enhancement on routine CET1-WI seems to be closely related to the luxury reperfusion at the late subacute stage and is not dependent on microvascular permeability changes at the acute stage.

Association of CT perfusion parameters with hemorrhagic transformation in acute ischemic stroke

BACKGROUND AND PURPOSE

Prediction of hemorrhagic transformation in acute ischemic stroke could help determine treatment and prognostication. With increasing numbers of patients with acute ischemic stroke undergoing multimodal CT imaging, we examined whether CT perfusion could predict hemorrhagic transformation in acute ischemic stroke.

MATERIALS AND METHODS

Patients with acute ischemic stroke who underwent CTP scanning within 12 hours of symptom onset were examined. Patients with and without hemorrhagic transformation were defined as cases and controls, respectively, and were matched as to IV rtPA administration and presentation NIHSS score (± 2). Relative mean transit time, relative CBF, and relative CBV values were calculated from CTP maps and normalized to the contralateral side. Receiver operating characteristic analysis curves were created, and threshold values for significant CTP parameters were obtained to predict hemorrhagic transformation.

RESULTS

Of 83 patients with acute ischemic stroke, 16 developed hemorrhagic transformation (19.28%). By matching, 38 controls were found for only 14 patients with hemorrhagic transformation. Among the matched patients with hemorrhagic transformation, 13 developed hemorrhagic infarction (6 hemorrhagic infarction 1 and 7 hemorrhagic infarction 2) and 1 developed parenchymal hematoma 2. There was no significant difference between cases and controls with respect to age, sex, time to presentation from symptom onset, and comorbidities. Cases had significantly lower median rCBV (8% lower) compared with controls (11% higher) (P = .009; odds ratio, 1.14 for a 0.1-U decrease in rCBV). There was no difference in median total volume of ischemia, rMTT, and rCBF among cases and controls. The area under the receiver operating characteristic was computed to be 0.83 (standard error, 0.08), with a cutoff point for rCBV of 1.09.

CONCLUSIONS

Of the examined CTP parameters, only lower rCBV was found to be significantly associated with a relatively higher chance of hemorrhagic transformation.

Multi-center prediction of hemorrhagic transformation in acute ischemic stroke using permeability imaging features

Permeability images derived from magnetic resonance (MR) perfusion images are sensitive to blood-brain barrier derangement of the brain tissue and have been shown to correlate with subsequent development of hemorrhagic transformation (HT) in acute ischemic stroke. This paper presents a multi-center retrospective study that evaluates the predictive power in terms of HT of six permeability MRI measures including contrast slope (CS), final contrast (FC), maximum peak bolus concentration (MPB), peak bolus area (PB), relative recirculation (rR), and percentage recovery (%R). Dynamic T2*-weighted perfusion MR images were collected from 263 acute ischemic stroke patients from four medical centers. An essential aspect of this study is to exploit a classifier-based framework to automatically identify predictive patterns in the overall intensity distribution of the permeability maps. The model is based on normalized intensity histograms that are used as input features to the predictive model. Linear and nonlinear predictive models are evaluated using a cross-validation to measure generalization power on new patients and a comparative analysis is provided for the different types of parameters. Results demonstrate that perfusion imaging in acute ischemic stroke can predict HT with an average accuracy of more than 85% using a predictive model based on a nonlinear regression model. Results also indicate that the permeability feature based on the percentage of recovery performs significantly better than the other features. This novel model may be used to refine treatment decisions in acute stroke.

Susceptibility-weighted imaging of the brain: does gadolinium administration matter?

OBJECTIVE

Susceptibility-weighted MR imaging (SWI) is usually obtained without administration of intravenous gadolinium (Gd). However, it is occasionally necessary to perform SWI after Gd is injected. The effects of Gd on SWI have not been systematically examined. The aim of this prospective study was to investigate whether performing SWI after Gd would influence the diagnostic image quality, parenchymal signal and vascular enhancement. An additional aim is to suggest potential future applications for Gd-enhanced SWI.

METHODS

SWI was performed in 31 subjects before and after Gd administration. 17 cases were examined in a 1.5T scanner and the remaining 14 were scanned at 3T. The pre- and post-Gd images were analysed for signal changes in the cerebral grey matter (GM), white matter (WM) as well as for enhancement in the superficial and deep venous system. The visibility of the veins was graded on subtraction maps.

RESULTS

The Gd-enhanced images showed no image quality degradation and no significant signal intensity change in the GM and WM as compared to the pre-Gd images (p>0.05). After Gd-administration significant enhancement of the venous sinuses was noticed (p<0.005), while the deep and cortical veins were poorly enhanced as confirmed by the calculated subtraction maps. The results showed no significant difference at variable MRI field strengths.

CONCLUSION

It is possible to perform SWI after Gd injection without information loss or signal change in the parenchyma. The most significant difference is the enhancement of the cerebral venous sinuses. Potential future applications are discussed.