Prediction of subsequent hemorrhage in acute ischemic stroke using permeability CT imaging and a distributed parameter tracer kinetic model

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.

Assessment Precision of CT Perfusion Imaging in the Detection of Acute Ischemic Stroke: A Systematic Review and Meta-Analysis

Stroke, a prevalent medical emergency, comprises ischemic and hemorrhagic subtypes, with acute ischemic stroke (AIS) being a predominant type. The application of computed tomography perfusion (CTP) imaging has gained prominence due to its rapidity and accessibility in stroke evaluation. This study systematically reviews and conducts a meta-analysis of existing literature to assess the diagnostic accuracy of CTP in detecting AIS and predicting hemorrhagic transformation (HT). Employing Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, an extensive search was conducted across electronic databases and relevant radiology journals. Studies conducted between 2007 and 2023 that fulfilled predetermined inclusion criteria underwent quality assessment using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS 2) tool. Cochrane diagnostic accuracy tools were used for data extraction. Thirteen studies involving a total of 1014 patients were included in the analysis. The diagnostic performance of CTP in predicting HT demonstrated high sensitivity (86.7%) and moderate specificity (77.8%), resulting in an overall accuracy of 79.1%. The negative predictive value (NPV) was notably high (92.9%), signifying its efficacy in excluding patients at risk of HT. The positive predictive value (PPV) was comparatively lower (60.3%), highlighting the need for clinical context when making thrombolysis decisions. The false positive rate was 16.2%, while the false negative rate was minimal (9.8%). Subgroup analysis underscored consistent sensitivity and specificity across diverse imaging metrics. The findings of this study emphasize the promising diagnostic accuracy of CTP imaging in predicting HT subsequent to AIS. This non-invasive technique can aid treatment decisions and patient management strategies. By effectively assessing perfusion status and offering predictive insights, CTP imaging improves stroke intervention choices, especially in identifying patients with a lower risk of HT.

Permeability Measures Predict Hemorrhagic Transformation after Ischemic Stroke

OBJECTIVE

We sought to examine the diagnostic utility of existing predictors of any hemorrhagic transformation (HT) and compare them with new perfusion imaging permeability measures in ischemic stroke patients receiving alteplase only.

METHODS

A pixel-based analysis of pretreatment CT perfusion (CTP) was undertaken to define the optimal CTP permeability thresholds to predict the likelihood of HT. We then compared previously proposed predictors of HT using regression analyses and receiver operating characteristic curve analysis to produce an area under the curve (AUC). We compared AUCs using χ² analysis.

RESULTS

From 5 centers, 1,407 patients were included in this study; of these, 282 had HT. The cohort was split into a derivation cohort (1,025, 70% patients) and a validation cohort (382 patients or 30%). The extraction fraction (E) permeability map at a threshold of 30% relative to contralateral had the highest AUC at predicting any HT (derivation AUC 0.85, 95% confidence interval [CI], 0.79-0.91; validation AUC 0.84, 95% CI 0.77-0.91). The AUC improved when permeability was assessed within the acute perfusion lesion for the E maps at a threshold of 30% (derivation AUC 0.91, 95% CI 0.86-0.95; validation AUC 0.89, 95% CI 0.86-0.95). Previously proposed associations with HT and parenchymal hematoma showed lower AUC values than the permeability measure.

INTERPRETATION

In this large multicenter study, we have validated a highly accurate measure of HT prediction. This measure might be useful in clinical practice to predict hemorrhagic transformation in ischemic stroke patients before receiving alteplase alone. ANN NEUROL 2020;88:466-476.

Diagnostic accuracy of computed tomography perfusion in the prediction of haemorrhagic transformation and patient outcome in acute ischaemic stroke: A systematic review and meta-analysis

Purpose

The aim of this systematic review and meta-analysis is to determine the diagnostic accuracy of computed tomography brain perfusion in the prediction of haemorrhagic transformation and patient outcome in acute ischaemic stroke.

Method

Electronic databases and grey literature published over the last 10 years related to healthcare and radiology were searched using the key terms: 'computed tomography perfusion', 'haemorrhagic transformation', 'acute ischaemic stroke', 'functional outcome' and their synonyms using both UK and American spellings. Inclusion criteria were: sample size at least 30 patients, original research, evaluate ability of computed tomography perfusion to predict haemorrhagic transformation, reports diagnostic accuracy or provide relevant data for a 2 × 2 contingency table, use follow-up non-contrast computed tomography (NCCT) or magnetic resonance imaging as reference standard.

Findings

Twelve studies were included in the review; studies cover a total of 808 patients. Haemorrhagic transformation occurred in 30.2% of patients. Pooled sensitivity and specificity were 85.9% (95% CI; 65-97%), 73.9% (95% CI; 45-92%) and accuracy of 79.1% (95% CI; 57-98%). Pooled NPV was 92.9% with a high false positive rate (19.8%), which could be explained in terms of outcome classification, acquisition artefact and computed tomography perfusion processing algorithms.

Discussion

This review evaluated the importance of using pre-defined threshold measurement for optimal prediction of HT, the relevance of patient pre-treatment clinical parameters to HT occurrence, the CTP parameters and the measurements that are independent predictors of HT, the significance of rtPA rather as an exacerbator of HT and the impact of both minor and major HT/PH on patient 2⁰ functional outcome.

Conclusion

Computed tomography perfusion has a high sensitivity and moderately high specificity for prediction of haemorrhagic transformation in acute ischaemic stroke. Pre-treatment clinical decision making requires consideration of clinical factors in addition to imaging findings. This systematic review and meta-analysis highlights that pre-treatment computed tomography perfusion adds to clinical confidence by predicting potential for haemorrhage, both in thrombolysed and un-thrombolysed patients, and also influences decisions about alternative treatments for acute ischaemic stroke patients.

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%.

Computed Tomography Perfusion Derived Blood-Brain Barrier Permeability Does Not Yet Improve Prediction of Hemorrhagic Transformation

INTRODUCTION

Hemorrhagic transformation (HT) in acute ischemic stroke can occur as a result of reperfusion treatment. While withholding treatment may be warranted in patients with increased risk of HT, prediction of HT remains difficult. Nonlinear regression analysis can be used to estimate blood-brain barrier permeability (BBBP). The aim of this study was to identify a combination of clinical and imaging variables, including BBBP estimations, that can predict HT.

MATERIALS AND METHODS

From the Dutch acute stroke study, 545 patients treated with intravenous recombinant tissue plasminogen activator and/or intra-arterial treatment were selected, with available admission extended computed tomography (CT) perfusion and follow-up imaging. Patient admission treatment characteristics and CT imaging parameters regarding occlusion site, stroke severity, and BBBP were recorded. HT was assessed on day 3 follow-up imaging. The association between potential predictors and HT was analyzed using univariate and multivariate logistic regression. To compare the added value of BBBP, areas under the curve (AUCs) were created from 2 models, with and without BBBP.

RESULTS

HT occurred in 57 patients (10%). In univariate analysis, older age (OR 1.03, 95% CI 1.006-1.05), higher admission National Institutes of Health Stroke Scale (NIHSS; OR 1.13, 95% CI 1.08-1.18), higher clot burden (OR 1.28, 95% CI 1.16-1.41), poor collateral score (OR 3.49, 95% CI 1.85-6.58), larger Alberta Stroke Program Early CT Score cerebral blood volume deficit size (OR 1.26, 95% CI 1.14-1.38), and increased BBBP (OR 2.22, 95% CI 1.46-3.37) were associated with HT. In multivariate analysis with age and admission NIHSS, the addition of BBBP did not improve the AUC compared to both independent predictors alone (AUC 0.77, 95% CI 0.71-0.83).

CONCLUSION

BBBP predicts HT but does not improve prediction with age and admission NIHSS.

High-permeability region size on perfusion CT predicts hemorrhagic transformation after intravenous thrombolysis in stroke

OBJECTIVE

Blood-brain barrier (BBB) permeability has been proposed as a predictor of hemorrhagic transformation (HT) after tissue plasminogen activator (tPA) administration; however, the reliability of perfusion computed tomography (PCT) permeability imaging for predicting HT is uncertain. We aimed to determine the performance of high-permeability region size on PCT (HPrs-PCT) in predicting HT after intravenous tPA administration in patients with acute stroke.

METHODS

We performed a multimodal CT protocol (non-contrast CT, PCT, CT angiography) to prospectively study patients with middle cerebral artery occlusion treated with tPA within 4.5 hours of symptom onset. HT was graded at 24 hours using the European-Australasian Acute Stroke Study II criteria. ROC curves selected optimal volume threshold, and multivariate logistic regression analysis identified predictors of HT.

RESULTS

The study included 156 patients (50% male, median age 75.5 years). Thirty-seven (23,7%) developed HT [12 (7,7%), parenchymal hematoma type 2 (PH-2)]. At admission, patients with HT had lower platelet values, higher NIHSS scores, increased ischemic lesion volumes, larger HPrs-PCT, and poorer collateral status. The negative predictive value of HPrs-PCT at a threshold of 7mL/100g/min was 0.84 for HT and 0.93 for PH-2. The multiple regression analysis selected HPrs-PCT at 7mL/100g/min combined with platelets and baseline NIHSS score as the best model for predicting HT (AUC 0.77). HPrs-PCT at 7mL/100g/min was the only independent predictor of PH-2 (OR 1, AUC 0.68, p = 0.045).

CONCLUSIONS

HPrs-PCT can help predict HT after tPA, and is particularly useful in identifying patients at low risk of developing HT.

TURN Score Predicts 24-Hour Cerebral Edema After IV Thrombolysis

BACKGROUND AND PURPOSE

Cerebral edema is associated with poor outcome after IV thrombolysis. We recently described the TURN score (Thrombolysis risk Using mRS and NIHSS), a predictor of severe outcome after IV thrombolysis. Our purpose was to evaluate its ability to predict 24-h cerebral edema.

METHODS

We retrospectively analyzed data from 303 patients who received IV rt-PA during the NINDS rt-PA trial. Measures of brain swelling included edema, mass effect and midline shift assessed at baseline, at 24 h and new onset at 24 h. Outcome was assessed using intracerebral hemorrhage (ICH), symptomatic intracerebral hemorrhage (sICH), 90-day severe outcome, and 90-day mortality. Statistical associations were assessed by logistic regression reporting odds ratios (OR) and by areas under the receiver operating characteristic curves (AUROC).

RESULTS

Baseline brain swelling did not predict poor outcome; however, 24-h brain swelling predicted ICH (OR 5.69, P < 0.001), sICH (OR 9.50, P = 0.01), 90-day severe outcome (OR 7.10, P < 0.001), and 90-day mortality (OR 5.65, P = 0.01). Similar results were seen for new brain swelling at 24 h. TURN predicted 24-hour brain swelling (OR 2.5, P < 0.001; AUROC 0.69, 95 % CI 0.63-0.75) and new brain swelling at 24 h (OR 2.1, P < 0.001; AUROC 0.67, 95 % CI 0.61-0.73).

CONCLUSIONS

Cerebral edema at 24 h is associated with poor outcome and 90-day mortality. TURN predicts ischemic stroke patients who will develop 24-h cerebral edema after IV thrombolysis.

CT perfusion analysis by nonlinear regression for predicting hemorrhagic transformation in ischemic stroke

PURPOSE

Intravenous thrombolysis can improve clinical outcome in acute ischemic stroke patients but increases the risk of hemorrhagic transformation (HT). Blood-brain barrier damage, which can be quantified by the vascular permeability for contrast agents, is a potential predictor for HT. This study aimed to assess whether this prediction can be improved by measuring vascular permeability using a novel fast nonlinear regression (NLR) method instead of Patlak analysis.

METHODS

From a prospective ischemic stroke multicenter cohort study, 20 patients with HT on follow-up imaging and 40 patients without HT were selected. The permeability transfer constant K(trans) was measured in three ways; using standard Patlak analysis, Patlak analysis with a fixed offset, and the NLR method. In addition, the permeability-surface (PS) area product and the conventional perfusion parameters (blood volume, flow, and mean transit time) were measured using the NLR method. Relative values were calculated in two ways, i.e., by dividing the average in the infarct core by the average in the contralateral hemisphere, and by dividing the average in the ipsilateral hemisphere by the average in the contralateral hemisphere. Mann-Whitney U tests and receiver operating characteristic (ROC) analyses were performed to assess the discriminative power of each of the relative parameters.

RESULTS

Both the infarct-core and whole-hemisphere averaged relative K(trans) (rK(trans)) values, measured with the NLR method, were significantly higher in the patients who developed HT as compared with those who did not. The rK(trans) measured with standard Patlak analysis was not significantly different. The relative PS (rPS), measured with NLR, had the highest discriminative power (P = 0.002). ROC analysis of rPS showed an area under the curve (AUC) of 0.75 (95% confidence interval: 0.62-0.89) and a sensitivity of 0.75 at a specificity of 0.75. The AUCs of the Patlak rK(trans), the Patlak rK(trans) with fixed offset, and the NLR rK(trans) were 0.58, 0.66, and 0.67, respectively.

CONCLUSIONS

CT perfusion analysis may aid in predicting HT, but standard Patlak analysis did not provide estimates for rK(trans) that were significantly higher in the HT group. The rPS, measured in the infarct core with NLR, had superior discriminative power compared with K(trans) measured with either Patlak analysis with a fixed offset or NLR, and conventional perfusion parameters.

What causes intracerebral bleeding after thrombolysis for acute ischaemic stroke? Recent insights into mechanisms and potential biomarkers

The overall population benefit of intravascular recombinant tissue plasminogen activator (rtPA) on functional outcome in ischaemic stroke is clear, but there are some treated patients who are harmed by early symptomatic intracranial haemorrhage (ICH). Although several clinical and radiological factors increase the risk of rtPA-related ICH, none of the currently available risk prediction tools are yet useful for practical clinical decision-making, probably reflecting our limited understanding of the underlying mechanisms. Finding new methods to identify patients at highest risk of rtPA-related ICH, or new measures to limit risk, are urgent challenges in acute stroke therapy research. In this article, we focus on the potential underlying mechanisms of rtPA-related ICH, highlight promising candidate risk biomarkers and suggest future research directions.

Influence of Thin Slice Reconstruction on CT Brain Perfusion Analysis

Objectives

Although CT scanners generally allow dynamic acquisition of thin slices (1 mm), thick slice (≥5 mm) reconstruction is commonly used for stroke imaging to reduce data, processing time, and noise level. Thin slice CT perfusion (CTP) reconstruction may suffer less from partial volume effects, and thus yield more accurate quantitative results with increased resolution. Before thin slice protocols are to be introduced clinically, it needs to be ensured that this does not affect overall CTP constancy. We studied the influence of thin slice reconstruction on average perfusion values by comparing it with standard thick slice reconstruction.

Materials and Methods

From 50 patient studies, absolute and relative hemisphere averaged estimates of cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and permeability-surface area product (PS) were analyzed using 0.8, 2.4, 4.8, and 9.6 mm slice reconstructions. Specifically, the influence of Gaussian and bilateral filtering, the arterial input function (AIF), and motion correction on the perfusion values was investigated.

Results

Bilateral filtering gave noise levels comparable to isotropic Gaussian filtering, with less partial volume effects. Absolute CBF, CBV and PS were 22%, 14% and 46% lower with 0.8 mm than with 4.8 mm slices. If the AIF and motion correction were based on thin slices prior to reconstruction of thicker slices, these differences reduced to 3%, 4% and 3%. The effect of slice thickness on relative values was very small.

Conclusions

This study shows that thin slice reconstruction for CTP with unaltered acquisition protocol gives relative perfusion values without clinically relevant bias. It does however affect absolute perfusion values, of which CBF and CBV are most sensitive. Partial volume effects in large arteries and veins lead to overestimation of these values. The effects of reconstruction slice thickness should be taken into account when absolute perfusion values are used for clinical decision making.

Dynamic contrast-enhanced MRI and CT provide comparable measurement of blood-brain barrier permeability in a rodent stroke model

In the current management of acute ischemic stroke (AIS), clinical criteria are used to estimate the risk of hemorrhagic transformation (HT), which is a devastating early complication. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and computed tomography (DCE-CT) may serve as physiologically-based decision making tools to more reliably assess the risk of HT. Before these tools can be properly validated, the comparability of the blood-brain barrier (BBB) permeability measurements they generate should be assessed. Sixteen rats were subjected to a transient middle cerebral artery occlusion before successively undergoing DCE-CT and DCE-MRI at 24-hours. BBB permeability (K(trans)) values were generated from both modalities. A correlation of R=0.677 was found (p<0.01) and the resulting relationship was [DCE-CT=(0.610*DCE-MRI)+4.140]. A variance components analysis found the intra-rat coefficient of variation to be 0.384 and 0.258 for K(trans) values from DCE-MRI and DCE-CT respectively. Permeability measures from DCE-CT were 22% higher than those from DCE-MRI. The results of this study demonstrate for the first time comparability between DCE-CT and DCE-MRI in the assessment of AIS. These results may provide a foundation for future clinical trials making combined use of these modalities.

Blood-brain barrier permeability imaging using perfusion computed tomography

Background.

The blood-brain barrier represents the selective diffusion barrier at the level of the cerebral microvascular endothelium. Other functions of blood-brain barrier include transport, signaling and osmoregulation. Endothelial cells interact with surrounding astrocytes, pericytes and neurons. These interactions are crucial to the development, structural integrity and function of the cerebral microvascular endothelium. Dysfunctional blood-brain barrier has been associated with pathologies such as acute stroke, tumors, inflammatory and neurodegenerative diseases.

Conclusions.

Blood-brain barrier permeability can be evaluated in vivo by perfusion computed tomography - an efficient diagnostic method that involves the sequential acquisition of tomographic images during the intravenous administration of iodinated contrast material. The major clinical applications of perfusion computed tomography are in acute stroke and in brain tumor imaging.

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.

A fast nonlinear regression method for estimating permeability in CT perfusion imaging

Blood-brain barrier damage, which can be quantified by measuring vascular permeability, is a potential predictor for hemorrhagic transformation in acute ischemic stroke. Permeability is commonly estimated by applying Patlak analysis to computed tomography (CT) perfusion data, but this method lacks precision. Applying more elaborate kinetic models by means of nonlinear regression (NLR) may improve precision, but is more time consuming and therefore less appropriate in an acute stroke setting. We propose a simplified NLR method that may be faster and still precise enough for clinical use. The aim of this study is to evaluate the reliability of in total 12 variations of Patlak analysis and NLR methods, including the simplified NLR method. Confidence intervals for the permeability estimates were evaluated using simulated CT attenuation-time curves with realistic noise, and clinical data from 20 patients. Although fixating the blood volume improved Patlak analysis, the NLR methods yielded significantly more reliable estimates, but took up to 12 × longer to calculate. The simplified NLR method was ∼4 × faster than other NLR methods, while maintaining the same confidence intervals (CIs). In conclusion, the simplified NLR method is a new, reliable way to estimate permeability in stroke, fast enough for clinical application in an acute stroke setting.

Improving low-dose blood-brain barrier permeability quantification using sparse high-dose induced prior for Patlak model

Blood-brain barrier permeability (BBBP) measurements extracted from the perfusion computed tomography (PCT) using the Patlak model can be a valuable indicator to predict hemorrhagic transformation in patients with acute stroke. Unfortunately, the standard Patlak model based PCT requires excessive radiation exposure, which raised attention on radiation safety. Minimizing radiation dose is of high value in clinical practice but can degrade the image quality due to the introduced severe noise. The purpose of this work is to construct high quality BBBP maps from low-dose PCT data by using the brain structural similarity between different individuals and the relations between the high- and low-dose maps. The proposed sparse high-dose induced (shd-Patlak) model performs by building a high-dose induced prior for the Patlak model with a set of location adaptive dictionaries, followed by an optimized estimation of BBBP map with the prior regularized Patlak model. Evaluation with the simulated low-dose clinical brain PCT datasets clearly demonstrate that the shd-Patlak model can achieve more significant gains than the standard Patlak model with improved visual quality, higher fidelity to the gold standard and more accurate details for clinical analysis.

Early time points perfusion imaging: theoretical analysis of correction factors for relative cerebral blood flow estimation given local arterial input function

If local arterial input function (AIF) could be identified, we present a theoretical approach to generate a correction factor based on local AIF for the estimation of relative cerebral blood flow (rCBF) under the framework of early time points perfusion imaging (ET). If C(t), the contrast agent bolus concentration signal time course, is used for rCBF estimation in ET, the correction factor for C(t) is the integral of its local AIF. The recipe to apply the correction factor is to divide C(t) by the integral of its local AIF to obtain the correct rCBF. By similar analysis, the correction factor for the maximum derivative (MD1) of C(t) is the maximum signal of AIF and the correction factor for the maximum second derivative (MD2) of C(t) is the maximum derivative of AIF. In the specific case of using normalized gamma-variate function as a model for AIF, the correction factor for C(t) (but not for MD1) at the time to reach the maximum derivative is relatively insensitive to the shape of the local AIF.

Blood-brain barrier permeability assessed by perfusion CT predicts symptomatic hemorrhagic transformation and malignant edema in acute ischemic stroke

BACKGROUND AND PURPOSE

SHT and ME are feared complications in patients with acute ischemic stroke. They occur >10 times more frequently in tPA-treated versus placebo-treated patients. Our goal was to evaluate the sensitivity and specificity of admission BBBP measurements derived from PCT in predicting the development of SHT and ME in patients with acute ischemic stroke.

MATERIALS AND METHODS

We retrospectively analyzed a dataset consisting of 32 consecutive patients with acute ischemic stroke with appropriate admission and follow-up imaging. We calculated admission BBBP by using delayed-acquisition PCT data and the Patlak model. Collateral flow was assessed on the admission CTA, while recanalization and reperfusion were assessed on the follow-up CTA and PCT, respectively. SHT and ME were defined according to ECASS III criteria. Clinical data were obtained from chart review. In our univariate and forward selection-based multivariate analysis for predictors of SHT and ME, we incorporated both clinical and imaging variables, including age, admission NIHSS score, admission blood glucose level, admission blood pressure, time from symptom onset to scanning, treatment type, admission PCT-defined infarct volume, admission BBBP, collateral flow, recanalization, and reperfusion. Optimal sensitivity and specificity for SHT and ME prediction were calculated by using ROC analysis.

RESULTS

In our sample of 32 patients, 3 developed SHT and 3 developed ME. Of the 3 patients with SHT, 2 received IV tPA, while 1 received IA tPA and treatment with the Merci device; of the 3 patients with ME, 2 received IV tPA, while 1 received IA tPA and treatment with the Merci device. Admission BBBP measurements above the threshold were 100% sensitive and 79% specific in predicting SHT and ME. Furthermore, all patients with SHT and ME--and only those with SHT and ME--had admission BBBP measurements above the threshold, were older than 65 years of age, and received tPA. Admission BBBP, age, and tPA were the independent predictors of SHT and ME in our forward selection-based multivariate analysis. Of these 3 variables, only BBBP measurements and age were known before making the decision of administering tPA and thus are clinically meaningful.

CONCLUSIONS

Admission BBBP, a pretreatment measurement, was 100% sensitive and 79% specific in predicting SHT and ME.

Estimation of the ischemic penumbra based on CT perfusion a pilot study

RATIONALE AND OBJECTIVES

Ischemic penumbra (IP), the target of thrombolytic therapies, could be estimated by the mismatch region between magnetic resonance imaging (MRI) diffusion- and perfusion-defined abnormalities; however, the accuracy of this method has been challenged recently. In this study, we try to establish a method for calculating IP size based on computed tomography perfusion (CTP) and to observe the early evolution of IP in detail.

MATERIALS AND METHODS

The middle cerebral artery occlusion (MCAO) model in monkey was used to compare the accuracy in estimating the IP between CTP and MRI methods. A receiver operating characteristic (ROC) curve was performed to calculate the IP threshold of the different CTP parameters, and then the best parameter was obtained. The dynamic evolutions of estimated size of IP by these two methods were compared.

RESULTS

Among the three CTP parameters, relative cerebral blood flow (rCBF) had the highest sensitivity (83.3%) and specificity (98.5%) in estimating the IP. The optimal cutoff threshold of rCBF was 0.203. During the first 15 hours of the MCAO model, the estimated size of IP by the rCBF was larger than that of the MRI method; however, this relationship was reversed 15 hours later.

CONCLUSION

This study suggests that the rCBF method is more accurate in estimating the IP since previous studies have reported that the MRI method underestimated the exact IP in the early stage of ischemia and overestimated the exact IP in the later stages. Further experimental and clinical studies are needed to validate the conclusion.

Increased blood-brain barrier permeability on perfusion CT might predict malignant middle cerebral artery infarction

BACKGROUND AND PURPOSE

Perfusion CT has been used to assess the extent of blood-brain barrier breakdown. The purpose of this study was to determine the predictive value of blood-brain barrier permeability measured using perfusion CT for development of malignant middle cerebral artery infarction requiring hemicraniectomy (HC).

METHODS

We retrospectively identified patients from our stroke registry who had middle cerebral artery infarction and were evaluated with admission perfusion CT. Blood-brain barrier permeability and cerebral blood volume maps were generated and infarct volumes calculated. Clinical and radiographic characteristics were compared between those who underwent HC versus those who did not undergo HC.

RESULTS

One hundred twenty-two patients (12 HC, 110 no HC) were identified. Twelve patients who underwent HC had developed edema, midline shift, or infarct expansion. Infarct permeability area, infarct cerebral blood volume area, and infarct volumes were significantly different (P < 0.018, P < 0.0211, P < 0.0001, P < 0.0014) between HC and no HC groups. Age (P = 0.03) and admission National Institutes of Health Stroke Scale (P = 0.0029) were found to be independent predictors for HC. Using logistic regression modeling, there was an association between increased infarct permeability area and HC. The OR for HC based on a 5-, 10-, 15-, or 20-cm² increase in infarct permeability area were 1.179, 1.390, 1.638, or 1.932, respectively (95% CI, 1.035 to 1.343, 1.071 to 1.804, 1.108 to 2.423, 1.146 to 3.255, respectively).

CONCLUSIONS

Increased infarct permeability area is associated with an increased likelihood for undergoing HC. Because early HC for malignant middle cerebral artery infarction has been associated with better outcomes, the infarct permeability area on admission perfusion CT might be a useful tool to predict malignant middle cerebral artery infarction and need for HC.

Delay correction for the assessment of blood-brain barrier permeability using first-pass dynamic perfusion CT

SUMMARY

Hemorrhagic transformation is a serious potential complication of ischemic stroke with damage to the BBB as one of the contributing mechanisms. BBB permeability measurements extracted from PCT by using the Patlak model can provide a valuable assessment of the extent of BBB damage. Unfortunately, Patlak assumptions require extended PCT acquisition, increasing the risk of motion artifacts. A necessary correction is presented for obtaining accurate BBB permeability measurements from first-pass PCT.

Recombinant tissue plasminogen activator increases blood-brain barrier disruption in acute ischemic stroke: an MR imaging permeability study

BACKGROUND AND PURPOSE

Although thrombolytic therapy (recombinant tissue plasminogen activator [rtPA]) represents an important step forward in acute ischemic stroke (AIS) management, there is a clear need to identify high-risk patients. The purpose of this study was to investigate the role of quantitative permeability (KPS) MR imaging in patients with AIS treated with and without rtPA. We hypothesized that rtPA would increase KPS and that KPS MR imaging can be used to predict the risk of hemorrhagic transformation (HT).

MATERIALS AND METHODS

Thirty-six patients with AIS were examined within a mean of 3.6 hours of documented symptom onset. KPS MR imaging was performed as part of our AIS protocol. KPS coefficients in the stroke lesion were estimated for all patients, and the relationship between KPS and both HT and rtPA was investigated by using Student t tests. Receiver operating characteristic (ROC) curves were computed for predicting HT from KPS.

RESULTS

The occurrence rate of HT for patients who received rtPA and those who did not was 43% and 37%, respectively. Assessment of KPS in the lesion revealed significant differences between those who hemorrhaged and those who did not (P < .0001) as well as between rtPA-treated and untreated patients (P = .008). ROC analysis indicated a KPS threshold of 0.67 mL/100 g/min, with a sensitivity of 92% and a specificity of 78%.

CONCLUSIONS

The results of this study indicate that KPS is able to identify patients at higher risk of HT and may allow use of physiologic imaging rather than time from onset of symptoms to guide treatment decision.

Optimal duration of acquisition for dynamic perfusion CT assessment of blood-brain barrier permeability using the Patlak model

BACKGROUND AND PURPOSE

A previous study demonstrated the need to use delayed acquisition rather than first-pass data for accurate blood-brain barrier permeability surface product (BBBP) calculation from perfusion CT (PCT) according to the Patlak model, but the optimal duration of the delayed acquisition has not been established. Our goal was to determine the optimal duration of the delayed PCT acquisition to obtain accurate BBBP measurements while minimizing potential motion artifacts and radiation dose.

MATERIALS AND METHODS

We retrospectively identified 23 consecutive patients with acute ischemic anterior circulation stroke who underwent a PCT study with delayed acquisition. The Patlak model was applied for the full delayed acquisition (90-240 seconds) and also for truncated analysis windows (90-210, 90-180, 90-150, 90-120 seconds). Linear regression of Patlak plots was performed separately for the full and truncated analysis windows, and the slope of these regression lines was used to indicate BBBP. The full and truncated analysis windows were compared in terms of the resulting BBBP values and the quality of the Patlak fitting.

RESULTS

BBBP values in the infarct and penumbra were similar for the full 90- to 240-second acquisition (95% confidence intervals for the infarct and penumbra: 1.62-2.47 and 1.75-2.41 mL x100 g(-1) x min(-1), respectively) and the 90- to 210-second analysis window (1.82-2.76 and 2.01-2.74 mL x 100 g(-1) x min(-1), respectively). BBBP values increased significantly with shorter acquisitions. The quality of the Patlak fit was excellent for the full 90- to 240-second and 90- to 210-second acquisitions, but it degraded with shorter acquisitions.

CONCLUSIONS

The duration for the delayed PCT acquisition should be at least 210 seconds, because acquisitions shorter than 210 seconds lead to significantly overestimated BBBP values.

Automated versus manual post-processing of perfusion-CT data in patients with acute cerebral ischemia: influence on interobserver variability

Introduction

The purpose of this study is to compare the variability of PCT results obtained by automatic selection of the arterial input function (AIF), venous output function (VOF) and symmetry axis versus manual selection.

Methods

Imaging data from 30 PCT studies obtained as part of standard clinical stroke care at our institution in patients with suspected acute hemispheric ischemic stroke were retrospectively reviewed. Two observers performed the post-processing of 30 CTP datasets. Each observer processed the data twice, the first time employing manual selection of AIF, VOF and symmetry axis, and a second time using automated selection of these same parameters, with the user being allowed to adjust them whenever deemed appropriate. The volumes of infarct core and of total perfusion defect were recorded. The cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT) and blood–brain barrier permeability (BBBP) values in standardized regions of interest were recorded. Interobserver variability was quantified using the Bland and Altman's approach.

Results

Automated post-processing yielded lower coefficients of variation for the volume of the infarct core and the volume of the total perfusion defect (15.7% and 5.8%, respectively) compared to manual post-processing (31.0% and 12.2%, respectively). Automated post-processing yielded lower coefficients of variation for PCT values (11.3% for CBV, 9.7% for CBF, and 9.5% for MTT) compared to manual post-processing (23.7% for CBV, 32.8% for CBF, and 16.7% for MTT).

Conclusion

Automated post-processing of PCT data improves interobserver agreement in measurements of CBV, CBF and MTT, as well as volume of infarct core and penumbra.

Age- and anatomy-related values of blood-brain barrier permeability measured by perfusion-CT in non-stroke patients

BACKGROUND AND PURPOSE

The goal of this study was to determine blood-brain barrier permeability (BBBP) values extracted from perfusion-CT (PCT) using the Patlak model and possible variations related to age, gender, race, vascular risk factors and their treatment and anatomy in non-stroke patients.

MATERIALS AND METHODS

We retrospectively identified 96 non-stroke patients who underwent a PCT study using a prolonged acquisition time up to 3 minutes. Patients' charts were reviewed for demographic data, vascular risk factors and their treatment. The Patlak model was applied to calculate BBBP values in regions of interest drawn within the basal ganglia and the gray and white matter of the different cerebral lobes. Differences in BBBP values were analyzed using a multivariate analysis considering clinical variables and anatomy.

RESULTS

Mean absolute BBBP values were 1.2 ml 100 g(-1) min(-1) and relative BBBP/CBF values were 3.5%. Statistical differences between gray and white matter were not clinically relevant. BBBP values were influenced by age, history of diabetes and/or hypertension and aspirin intake.

CONCLUSION

This study reports ranges of BBBP values in non-stroke patients calculated from delayed phase PCT data using the Patlak model. These ranges will be useful to detect abnormal BBBP values when assessing patients with cerebral infarction for the risk of hemorrhagic transformation.

Mechanisms and markers for hemorrhagic transformation after stroke

Intracerebral hemorrhagic transformation is a multifactorial phenomenon in which ischemic brain tissue converts into a hemorrhagic lesion with blood vessel leakage. Hemorrhagic transformation can significantly contribute to additional brain injury after stroke. Especially threatening are the thrombolytic-induced hemorrhages after reperfusion therapy with tissue plasminogen activator (tPA), the only treatment available for ischemic stroke. In this context, it is important to understand its underlying mechanisms and identify early markers of hemorrhagic transformation, so that we can both search for new treatments as well as predict clinical outcomes in patients. In this review, we discuss the emerging mechanisms for hemorrhagic transformation after stroke, and briefly survey potential molecular, genetic, and neuroimaging markers that might be used for early detection of this challenging clinical problem.

Accuracy and anatomical coverage of perfusion CT assessment of the blood-brain barrier permeability: one bolus versus two boluses

PURPOSE

To assess whether blood-brain barrier permeability (BBBP) values, extracted with the Patlak model from the second perfusion CT (PCT) contrast bolus, are significantly lower than the values extracted from the first bolus in the same patient.

MATERIALS AND METHODS

125 consecutive patients (29 with acute hemispheric stroke and 96 without stroke) who underwent a PCT study using a prolonged acquisition time up to 3 min were retrospectively identified. The Patlak model was applied to calculate the rate of contrast leakage out of the vascular compartment. Patlak plots were created from the arterial and parenchymal time enhancement curves obtained in multiple regions of interest drawn in ischemic brain tissue and in nonischemic brain tissue. The slope of a regression line fit to the Patlak plot was used as an indicator of BBBP. Square roots of the mean squared errors and correlation coefficients were used to describe the quality of the linear regression model. This was performed separately for the first and the second PCT bolus. Results from the first and the second bolus were compared in terms of BBBP values and the quality of the linear model fitted to the Patlak plot, using generalized estimating equations with robust variance estimation.

RESULTS

BBBP values from the second bolus were not lower than BBBP values from the first bolus in either nonischemic brain tissue [estimated mean with 95% confidence interval: 1.42 (1.10-1.82) ml x 100 g(-1) x min(-1) for the first bolus versus 1.64 (1.31-2.05) ml x 100 g(-1) x min(-1) for the second bolus, p = 1.00] or in ischemic tissue [1.04 (0.97-1.12) ml x 100 g(-1) x min(-1) for the first bolus versus 1.19 (1.11-1.28) ml x 100 g(-1)min(-1) for the second bolus, p = 0.79]. Compared to regression models from the first bolus, the Patlak regression models obtained from the second bolus were of similar or slightly better quality. This was true both in nonischemic and ischemic brain tissue.

CONCLUSION

The contrast material from the first bolus of contrast for PCT does not negatively influence measurements of BBBP values from the second bolus. The second bolus can thus be used to increase anatomical coverage of BBBP assessment using PCT.

Dynamic perfusion CT assessment of the blood-brain barrier permeability: first pass versus delayed acquisition

BACKGROUND AND PURPOSE

The Patlak model has been applied to first-pass perfusion CT (PCT) data to extract information on blood-brain barrier permeability (BBBP) to predict hemorrhagic transformation in patients with acute stroke. However, the Patlak model was originally described for the delayed steady-state phase of contrast circulation. The goal of this study was to assess whether the first pass or the delayed phase of a contrast bolus injection better respects the assumptions of the Patlak model for the assessment of BBBP in patients with acute stroke by using PCT.

MATERIALS AND METHODS

We retrospectively identified 125 consecutive patients (29 with acute hemispheric stroke and 96 without) who underwent a PCT study by using a prolonged acquisition time up to 3 minutes. The Patlak model was applied to calculate BBBP in ischemic and nonischemic brain tissue. Linear regression of the Patlak plot was performed separately for the first pass and for the delayed phase of the contrast bolus injection. Patlak linear regression models for the first pass and the delayed phase were compared in terms of their respective square root mean squared errors (square root MSE) and correlation coefficients (R) by using generalized estimating equations with robust variance estimation.

RESULTS

BBBP values calculated from the first pass were significantly higher than those from the delayed phase, both in nonischemic brain tissue (2.81 mL x 100 g(-1) x min(-1) for the first pass versus 1.05 mL x 100 g(-1) x min(-1) for the delayed phase, P < .001) and in ischemic tissue (7.63 mL x 100 g(-1) x min(-1) for the first pass versus 1.31 mL x 100 g(-1) x min(-1) for the delayed phase, P < .001). Compared with regression models from the first pass, Patlak regression models obtained from the delayed data were of better quality, showing significantly lower square root MSE and higher R.

CONCLUSION

Only the delayed phase of PCT acquisition respects the assumptions of linearity of the Patlak model in patients with and without stroke.

Vascular permeability in cardiovascular disease and cancer

PURPOSE OF REVIEW

Regulation of endothelial barrier function is critical for vascular homeostasis, as dynamic and local control of vascular permeability permits macromolecular transport, immune surveillance, and deposition of a fibrin barrier to contain infection at sites of inflammation. Many of the signaling pathways promoting useful vascular permeability, however, are also triggered during disease, resulting in prolonged or uncontrolled vascular leak. Hyperpermeability triggered by inflammation or ischemia in the heart, brain, or lung promotes edema, exacerbates disease progression, and impairs recovery. During cancer, solid tumors release factors that promote the growth of leaky blood vessels which contribute to metastatic spread and limit targeted delivery of anticancer agents.

RECENT FINDINGS

Although the molecular mechanisms governing vascular leak have been studied intensely over the last few decades, recent advances have identified new therapeutic targets that have begun to show preclinical and clinical promise. These approaches have been recently applied with success to an increasing number of disease models.

SUMMARY

Designing new therapies to limit vascular leak during the progression of disease requires a more complete understanding of the molecular mechanisms governing the endothelial barrier function. This knowledge will benefit the treatment of a growing number of diseases from cardiovascular disease to cancer.

Computed tomography assessment of cerebral perfusion using a distributed parameter tracer kinetics model: validation with H(2)((15))O positron emission tomography measurements and initial clinical experience in patients with acute stroke

We describe a distributed parameter (DP) model for tracer kinetic analysis in brain and validate the derived perfusion values with positron emission tomography (PET) scans. The proposed model is applied on actual clinical cases of hemispheric stroke. Nine patients with experienced transient ischaemic attack or minor stroke and a stenosis of the internal carotid artery were referred for computed tomography (CT) and PET imaging. The applicability of the DP model in clinical practice was tested in seven patients with acute stroke who received a baseline perfusion CT study and a noncontrast follow-up CT study after 2.4+/-1.8 days. The mean blood flow (F) value for all patients with carotid stenosis in the pooled data (54 regions of interest (ROIs)) was 37.9+/-11.2 mL/min per 100 g in perfusion CT and 35.6+/-9.8 mL/min per 100 g in perfusion PET imaging [r=0.77 (P=0.00)]. Regression analysis of the pooled ROIs for every patient revealed significant correlation between F values in seven patients [r=0.50 to 0.79 (r(2)-values ranged from 0.45 to 0.79), (0.01 < or = P < or = 0.05)]. Parametric maps that corresponded to all physiologic parameters were generated for every perfusion CT in the patients with acute stroke using the DP model. The ischaemic area was better delineated in F, intravascular blood volume and lag time (t(lag)) maps. The correlation coefficient comparing the visually outlined regions of abnormality between the t(lag) parametric map and the follow-up CT scans was 0.81 (P=0.003). In conclusion, DP physiological model using more realistic pharmacokinetics is feasible in dynamic contrast-enhanced CT of the brain in patients with acute and chronic cerebrovascular disease.