A deep learning analysis of stroke onset time prediction and comparison to DWI-FLAIR mismatch

INTRODUCTION

When time since stroke onset is unknown, DWI-FLAIR mismatch rating is an established technique for patient stratification. A visible DWI lesion without corresponding parenchymal hyperintensity on FLAIR suggests time since onset of under 4.5 h and thus a potential benefit from intravenous thrombolysis. To improve accuracy and availability of the mismatch concept, deep learning might be able to augment human rating and support decision-making in these cases.

METHODS

We used unprocessed DWI and coregistered FLAIR imaging data to train a deep learning model to predict dichotomized time since ischemic stroke onset. We analyzed the performance of Group Convolutional Neural Networks compared to other deep learning methods. Unlabeled imaging data was used for pre-training. Prediction performance of the best deep learning model was compared to the performance of four independent junior and senior raters. Additionally, in cases deemed indeterminable by human raters, model ratings were used to augment human performance. Post-hoc gradient-based explanations were analyzed to gain insights into model predictions.

RESULTS

Our best predictive model performed comparably to human raters. Using model ratings in cases deemed indeterminable by human raters improved rating accuracy and interrater agreement for junior and senior ratings. Post-hoc explainability analyses showed that the model localized stroke lesions to derive predictions.

DISCUSSION

Our analysis shows that deep learning based clinical decision support has the potential to improve the accessibility of the DWI-FLAIR mismatch concept by supporting patient stratification.

Personalised simulation of hemodynamics in cerebrovascular disease: lessons learned from a study of diagnostic accuracy

Intracranial atherosclerotic disease (ICAD) poses a significant risk of subsequent stroke but current prevention strategies are limited. Mechanistic simulations of brain hemodynamics offer an alternative precision medicine approach by utilising individual patient characteristics. For clinical use, however, current simulation frameworks have insufficient validation. In this study, we performed the first quantitative validation of a simulation-based precision medicine framework to assess cerebral hemodynamics in patients with ICAD against clinical standard perfusion imaging. In a retrospective analysis, we used a 0-dimensional simulation model to detect brain areas that are hemodynamically vulnerable to subsequent stroke. The main outcome measures were sensitivity, specificity, and area under the receiver operating characteristics curve (ROC AUC) of the simulation to identify brain areas vulnerable to subsequent stroke as defined by quantitative measurements of relative mean transit time (relMTT) from dynamic susceptibility contrast MRI (DSC-MRI). In 68 subjects with unilateral stenosis >70% of the internal carotid artery (ICA) or middle cerebral artery (MCA), the sensitivity and specificity of the simulation were 0.65 and 0.67, respectively. The ROC AUC was 0.68. The low-to-moderate accuracy of the simulation may be attributed to assumptions of Newtonian blood flow, rigid vessel walls, and the use of time-of-flight MRI for geometric representation of subject vasculature. Future simulation approaches should focus on integrating additional patient data, increasing accessibility of precision medicine tools to clinicians, addressing disease burden disparities amongst different populations, and quantifying patient benefit. Our results underscore the need for further improvement of mechanistic simulations of brain hemodynamics to foster the translation of the technology to clinical practice.

Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease

Stroke is a major cause of death or disability. As imaging-based patient stratification improves acute stroke therapy, dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is of major interest in image brain perfusion. However, expert-level perfusion maps require a manual or semi-manual post-processing by a medical expert making the procedure time-consuming and less-standardized. Modern machine learning methods such as generative adversarial networks (GANs) have the potential to automate the perfusion map generation on an expert level without manual validation. We propose a modified pix2pix GAN with a temporal component (temp-pix2pix-GAN) that generates perfusion maps in an end-to-end fashion. We train our model on perfusion maps infused with expert knowledge to encode it into the GANs. The performance was trained and evaluated using the structural similarity index measure (SSIM) on two datasets including patients with acute stroke and the steno-occlusive disease. Our temp-pix2pix architecture showed high performance on the acute stroke dataset for all perfusion maps (mean SSIM 0.92-0.99) and good performance on data including patients with the steno-occlusive disease (mean SSIM 0.84-0.99). While clinical validation is still necessary for future studies, our results mark an important step toward automated expert-level perfusion maps and thus fast patient stratification.

Anatomical labeling of intracranial arteries with deep learning in patients with cerebrovascular disease

Brain arteries are routinely imaged in the clinical setting by various modalities, e.g., time-of-flight magnetic resonance angiography (TOF-MRA). These imaging techniques have great potential for the diagnosis of cerebrovascular disease, disease progression, and response to treatment. Currently, however, only qualitative assessment is implemented in clinical applications, relying on visual inspection. While manual or semi-automated approaches for quantification exist, such solutions are impractical in the clinical setting as they are time-consuming, involve too many processing steps, and/or neglect image intensity information. In this study, we present a deep learning-based solution for the anatomical labeling of intracranial arteries that utilizes complete information from 3D TOF-MRA images. We adapted and trained a state-of-the-art multi-scale Unet architecture using imaging data of 242 patients with cerebrovascular disease to distinguish 24 arterial segments. The proposed model utilizes vessel-specific information as well as raw image intensity information, and can thus take tissue characteristics into account. Our method yielded a performance of 0.89 macro F1 and 0.90 balanced class accuracy (bAcc) in labeling aggregated segments and 0.80 macro F1 and 0.83 bAcc in labeling detailed arterial segments on average. In particular, a higher F1 score than 0.75 for most arteries of clinical interest for cerebrovascular disease was achieved, with higher than 0.90 F1 scores in the larger, main arteries. Due to minimal pre-processing, simple usability, and fast predictions, our method could be highly applicable in the clinical setting.

Toward Sharing Brain Images: Differentially Private TOF-MRA Images With Segmentation Labels Using Generative Adversarial Networks

Sharing labeled data is crucial to acquire large datasets for various Deep Learning applications. In medical imaging, this is often not feasible due to privacy regulations. Whereas anonymization would be a solution, standard techniques have been shown to be partially reversible. Here, synthetic data using a Generative Adversarial Network (GAN) with differential privacy guarantees could be a solution to ensure the patient's privacy while maintaining the predictive properties of the data. In this study, we implemented a Wasserstein GAN (WGAN) with and without differential privacy guarantees to generate privacy-preserving labeled Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) image patches for brain vessel segmentation. The synthesized image-label pairs were used to train a U-net which was evaluated in terms of the segmentation performance on real patient images from two different datasets. Additionally, the Fréchet Inception Distance (FID) was calculated between the generated images and the real images to assess their similarity. During the evaluation using the U-Net and the FID, we explored the effect of different levels of privacy which was represented by the parameter ϵ. With stricter privacy guarantees, the segmentation performance and the similarity to the real patient images in terms of FID decreased. Our best segmentation model, trained on synthetic and private data, achieved a Dice Similarity Coefficient (DSC) of 0.75 for ϵ = 7.4 compared to 0.84 for ϵ = ∞ in a brain vessel segmentation paradigm (DSC of 0.69 and 0.88 on the second test set, respectively). We identified a threshold of ϵ <5 for which the performance (DSC <0.61) became unstable and not usable. Our synthesized labeled TOF-MRA images with strict privacy guarantees retained predictive properties necessary for segmenting the brain vessels. Although further research is warranted regarding generalizability to other imaging modalities and performance improvement, our results mark an encouraging first step for privacy-preserving data sharing in medical imaging.

A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease

BACKGROUND

Cerebrovascular disease, in particular stroke, is a major public health challenge. An important biomarker is cerebral hemodynamics. To measure and quantify cerebral hemodynamics, however, only invasive, potentially harmful or time-to-treatment prolonging methods are available.

RESULTS

We present a simulation-based approach which allows calculation of cerebral hemodynamics based on the patient-individual vessel configuration derived from structural vessel imaging. For this, we implemented a framework allowing segmentation and annotation of brain vessels from structural imaging followed by 0-dimensional lumped simulation modeling of cerebral hemodynamics. For annotation, a 3D-graphical user interface was implemented. For 0D-simulation, we used a modified nodal analysis, which was adapted for easy implementation by code. The simulation enables identification of areas vulnerable to stroke and simulation of changes due to different systemic blood pressures. Moreover, sensitivity analysis was implemented allowing the live simulation of changes to simulate procedures and disease progression. Beyond presentation of the framework, we demonstrated in an exploratory analysis in 67 patients that the simulation has a high specificity and low-to-moderate sensitivity to detect perfusion changes in classic perfusion imaging.

CONCLUSIONS

The presented precision medicine approach using novel biomarkers has the potential to make the application of harmful and complex perfusion methods obsolete.

Synthesizing anonymized and labeled TOF-MRA patches for brain vessel segmentation using generative adversarial networks

Anonymization and data sharing are crucial for privacy protection and acquisition of large datasets for medical image analysis. This is a big challenge, especially for neuroimaging. Here, the brain's unique structure allows for re-identification and thus requires non-conventional anonymization. Generative adversarial networks (GANs) have the potential to provide anonymous images while preserving predictive properties. Analyzing brain vessel segmentation, we trained 3 GANs on time-of-flight (TOF) magnetic resonance angiography (MRA) patches for image-label generation: 1) Deep convolutional GAN, 2) Wasserstein-GAN with gradient penalty (WGAN-GP) and 3) WGAN-GP with spectral normalization (WGAN-GP-SN). The generated image-labels from each GAN were used to train a U-net for segmentation and tested on real data. Moreover, we applied our synthetic patches using transfer learning on a second dataset. For an increasing number of up to 15 patients we evaluated the model performance on real data with and without pre-training. The performance for all models was assessed by the Dice Similarity Coefficient (DSC) and the 95th percentile of the Hausdorff Distance (95HD). Comparing the 3 GANs, the U-net trained on synthetic data generated by the WGAN-GP-SN showed the highest performance to predict vessels (DSC/95HD 0.85/30.00) benchmarked by the U-net trained on real data (0.89/26.57). The transfer learning approach showed superior performance for the same GAN compared to no pre-training, especially for one patient only (0.91/24.66 vs. 0.84/27.36). In this work, synthetic image-label pairs retained generalizable information and showed good performance for vessel segmentation. Besides, we showed that synthetic patches can be used in a transfer learning approach with independent data. This paves the way to overcome the challenges of scarce data and anonymization in medical imaging.

BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease

Introduction: Arterial brain vessel assessment is crucial for the diagnostic process in patients with cerebrovascular disease. Non-invasive neuroimaging techniques, such as time-of-flight (TOF) magnetic resonance angiography (MRA) imaging are applied in the clinical routine to depict arteries. They are, however, only visually assessed. Fully automated vessel segmentation integrated into the clinical routine could facilitate the time-critical diagnosis of vessel abnormalities and might facilitate the identification of valuable biomarkers for cerebrovascular events. In the present work, we developed and validated a new deep learning model for vessel segmentation, coined BRAVE-NET, on a large aggregated dataset of patients with cerebrovascular diseases. Methods: BRAVE-NET is a multiscale 3-D convolutional neural network (CNN) model developed on a dataset of 264 patients from three different studies enrolling patients with cerebrovascular diseases. A context path, dually capturing high- and low-resolution volumes, and deep supervision were implemented. The BRAVE-NET model was compared to a baseline Unet model and variants with only context paths and deep supervision, respectively. The models were developed and validated using high-quality manual labels as ground truth. Next to precision and recall, the performance was assessed quantitatively by Dice coefficient (DSC); average Hausdorff distance (AVD); 95-percentile Hausdorff distance (95HD); and via visual qualitative rating. Results: The BRAVE-NET performance surpassed the other models for arterial brain vessel segmentation with a DSC = 0.931, AVD = 0.165, and 95HD = 29.153. The BRAVE-NET model was also the most resistant toward false labelings as revealed by the visual analysis. The performance improvement is primarily attributed to the integration of the multiscaling context path into the 3-D Unet and to a lesser extent to the deep supervision architectural component. Discussion: We present a new state-of-the-art of arterial brain vessel segmentation tailored to cerebrovascular pathology. We provide an extensive experimental validation of the model using a large aggregated dataset encompassing a large variability of cerebrovascular disease and an external set of healthy volunteers. The framework provides the technological foundation for improving the clinical workflow and can serve as a biomarker extraction tool in cerebrovascular diseases.

Outcomes of Hypothermia in Addition to Decompressive Hemicraniectomy in Treatment of Malignant Middle Cerebral Artery Stroke: A Randomized Clinical Trial

Importance

Moderate hypothermia in addition to early decompressive hemicraniectomy has been suggested to further reduce mortality and improve functional outcome in patients with malignant middle cerebral artery (MCA) stroke.

Objective

To investigate whether moderate hypothermia vs standard treatment after early hemicraniectomy reduces mortality at day 14 in patients with malignant MCA stroke.

Design, Setting, and Participants

This randomized clinical trial recruited patients from August 2011 through September 2015 at 6 German university hospitals with dedicated neurointensive care units. Of the patients treated with hemicraniectomy and assessed for eligibility, patients were randomly assigned to either standard care or moderate hypothermia. Data analysis was completed from December 2016 to June 2018.

Interventions

Moderate hypothermia (temperature, 33.0 ± 1.0°C) was maintained for at least 72 hours immediately after hemicraniectomy.

Main Outcomes and Measures

The primary outcome was mortality rate at day 14 compared with the Fisher exact test and expressed as odds ratio (ORs) with 95% CIs. Rates of patients with serious adverse events were estimated for the period of the first 14 days after hemicraniectomy and 12 months of follow-up. Secondary outcome measures included functional outcome at 12 months.

Results

Of the 50 study participants, 24 were assigned to standard care and 26 to moderate hypothermia. Twenty-eight were male (56%); the mean (SD) patient age was 51.3 (6.6) years. Recruitment was suspended for safety concerns: 12 of 26 patients (46%) in the hypothermia group and 7 of 24 patients (29%) receiving standard care had at least 1 serious adverse event within 14 days (OR, 2.05 [95% CI, 0.56-8.00]; P = .26); after 12 months, rates of serious adverse events were 80% (n = 20 of 25) in the hypothermia group and 43% (n = 10 of 23) in the standard care group (hazard ratio, 2.54 [95% CI, 1.29-5.00]; P = .005). The mortality rate at day 14 was 19% (5 of 26 patients) in the hypothermia group and 13% (3 of 24 patients) in the group receiving standard care (OR, 1.65 [95% CI, 0.28-12.01]; P = .70). There was no significant difference regarding functional outcome after 12 months of follow-up.

Interpretation

In patients with malignant MCA stroke, moderate hypothermia early after hemicraniectomy did not improve mortality and functional outcome compared with standard care, but may cause serious harm in this specific setting.

Trial Registration

http://www.drks.de, identifier DRKS00000623.

Management of therapeutic anticoagulation in patients with intracerebral haemorrhage and mechanical heart valves

Aims

Evidence is lacking regarding acute anticoagulation management in patients after intracerebral haemorrhage (ICH) with implanted mechanical heart valves (MHVs). Our objective was to investigate anticoagulation reversal and resumption strategies by evaluating incidences of haemorrhagic and thromboembolic complications, thereby defining an optimal time-window when to restart therapeutic anticoagulation (TA) in patients with MHV and ICH.

Methods and results

We pooled individual patient-data (n = 2504) from a nationwide multicentre cohort-study (RETRACE, conducted at 22 German centres) and eventually identified MHV-patients (n = 137) with anticoagulation-associated ICH for outcome analyses. The primary outcome consisted of major haemorrhagic complications analysed during hospital stay according to treatment exposure (restarted TA vs. no-TA). Secondary outcomes comprised thromboembolic complications, the composite outcome (haemorrhagic and thromboembolic complications), timing of TA, and mortality. Adjusted analyses involved propensity-score matching and multivariable cox-regressions to identify optimal timing of TA. In 66/137 (48%) of patients TA was restarted, being associated with increased haemorrhagic (TA = 17/66 (26%) vs. no-TA = 4/71 (6%); P < 0.01) and a trend to decreased thromboembolic complications (TA = 1/66 (2%) vs. no-TA = 7/71 (10%); P = 0.06). Controlling treatment crossovers provided an incidence rate-ratio [hazard ratio (HR) 10.31, 95% confidence interval (CI) 3.67–35.70; P < 0.01] in disadvantage of TA for haemorrhagic complications. Analyses of TA-timing displayed significant harm until Day 13 after ICH (HR 7.06, 95% CI 2.33–21.37; P < 0.01). The hazard for the composite—balancing both complications, was increased for restarted TA until Day 6 (HR 2.51, 95% CI 1.10–5.70; P = 0.03).

Conclusion

Restarting TA within less than 2 weeks after ICH in patients with MHV was associated with increased haemorrhagic complications. Optimal weighing—between least risks for thromboembolic and haemorrhagic complications—provided an earliest starting point of TA at Day 6, reserved only for patients at high thromboembolic risk.

Association of Surgical Hematoma Evacuation vs Conservative Treatment With Functional Outcome in Patients With Cerebellar Intracerebral Hemorrhage

Importance

The association of surgical hematoma evacuation with clinical outcomes in patients with cerebellar intracerebral hemorrhage (ICH) has not been established.

Objective

To determine the association of surgical hematoma evacuation with clinical outcomes in cerebellar ICH.

Design, Setting, and Participants

Individual participant data (IPD) meta-analysis of 4 observational ICH studies incorporating 6580 patients treated at 64 hospitals across the United States and Germany (2006-2015).

Exposure

Surgical hematoma evacuation vs conservative treatment.

Main Outcomes and Measures

The primary outcome was functional disability evaluated by the modified Rankin Scale ([mRS] score range: 0, no functional deficit to 6, death) at 3 months; favorable (mRS, 0-3) vs unfavorable (mRS, 4-6). Secondary outcomes included survival at 3 months and at 12 months. Analyses included propensity score matching and covariate adjustment, and predicted probabilities were used to identify treatment-related cutoff values for cerebellar ICH.

Results

Among 578 patients with cerebellar ICH, propensity score-matched groups included 152 patients with surgical hematoma evacuation vs 152 patients with conservative treatment (age, 68.9 vs 69.2 years; men, 55.9% vs 51.3%; prior anticoagulation, 60.5% vs 63.8%; and median ICH volume, 20.5 cm3 vs 18.8 cm3). After adjustment, surgical hematoma evacuation vs conservative treatment was not significantly associated with likelihood of better functional disability at 3 months (30.9% vs 35.5%; adjusted odds ratio [AOR], 0.94 [95% CI, 0.81 to 1.09], P = .43; adjusted risk difference [ARD], -3.7% [95% CI, -8.7% to 1.2%]) but was significantly associated with greater probability of survival at 3 months (78.3% vs 61.2%; AOR, 1.25 [95% CI, 1.07 to 1.45], P = .005; ARD, 18.5% [95% CI, 13.8% to 23.2%]) and at 12 months (71.7% vs 57.2%; AOR, 1.21 [95% CI, 1.03 to 1.42], P = .02; ARD, 17.0% [95% CI, 11.5% to 22.6%]). A volume range of 12 to 15 cm3 was identified; below this level, surgical hematoma evacuation was associated with lower likelihood of favorable functional outcome (volume ≤12 cm3, 30.6% vs 62.3% [P = .003]; ARD, -34.7% [-38.8% to -30.6%]; P value for interaction, .01), and above, it was associated with greater likelihood of survival (volume ≥15 cm3, 74.5% vs 45.1% [P < .001]; ARD, 28.2% [95% CI, 24.6% to 31.8%]; P value for interaction, .02).

Conclusions and Relevance

Among patients with cerebellar ICH, surgical hematoma evacuation, compared with conservative treatment, was not associated with improved functional outcome. Given the null primary outcome, investigation is necessary to establish whether there are differing associations based on hematoma volume.

Heparin for prophylaxis of venous thromboembolism in intracerebral haemorrhage

OBJECTIVE

To determine the occurrence of intracranial haemorrhagic complications (IHC) on heparin prophylaxis (low-dose subcutaneous heparin, LDSH) in primary spontaneous intracerebral haemorrhage (ICH) (not oral anticoagulation-associated ICH, non-OAC-ICH), vitamin K antagonist (VKA)-associated ICH and non-vitamin K antagonist oral anticoagulant (NOAC)-associated ICH.

METHODS

Retrospective cohort study (RETRACE) of 22 participating centres and prospective single-centre study with 1702 patients with VKA-associated or NOAC-associated ICH and 1022 patients with non-OAC-ICH with heparin prophylaxis between 2006 and 2015. Outcomes were defined as rates of IHC during hospital stay among patients with non-OAC-ICH, VKA-ICH and NOAC-ICH, mortality and functional outcome at 3 months between patients with ICH with and without IHC.

RESULTS

IHC occurred in 1.7% (42/2416) of patients with ICH. There were no differences in crude incidence rates among patients with VKA-ICH, NOAC-ICH and non-OAC-ICH (log-rank p=0.645; VKA-ICH: 27/1406 (1.9%), NOAC-ICH 1/130 (0.8%), non-OAC-ICH 14/880 (1.6%); p=0.577). Detailed analysis according to treatment exposure (days with and without LDSH) revealed no differences in incidence rates of IHC per 1000 patient-days (LDSH: 1.43 (1.04-1.93) vs non-LDSH: 1.32 (0.33-3.58), conditional maximum likelihood incidence rate ratio: 1.09 (0.38-4.43); p=0.953). Secondary outcomes showed differences in functional outcome (modified Rankin Scale=4-6: IHC: 29/37 (78.4%) vs non-IHC: 1213/2048 (59.2%); p=0.019) and mortality (IHC: 14/37 (37.8%) vs non-IHC: 485/2048 (23.7%); p=0.045) in disfavour of patients with IHC. Small ICH volume (OR: volume <4.4 mL: 0.18 (0.04-0.78); p=0.022) and low National Institutes of Health Stroke Scale (NIHSS) score on admission (OR: NIHSS <4: 0.29 (0.11-0.78); p=0.014) were significantly associated with fewer IHC.

CONCLUSIONS

Heparin administration for venous thromboembolism (VTE) prophylaxis in patients with ICH appears to be safe regarding IHC among non-OAC-ICH, VKA-ICH and NOAC-ICH in this observational cohort analysis. Randomised controlled trials are needed to verify the safety and efficacy of heparin compared with other methods for VTE prevention.

Characteristics in Non-Vitamin K Antagonist Oral Anticoagulant-Related Intracerebral Hemorrhage

Background and Purpose- Given inconclusive studies, it is debated whether clinical and imaging characteristics, as well as functional outcome, differ among patients with intracerebral hemorrhage (ICH) related to vitamin K antagonists (VKA) versus non-vitamin K antagonist (NOAC)-related ICH. Notably, clinical characteristics according to different NOAC agents and dosages are not established. Methods- Multicenter observational cohort study integrating individual patient data of 1328 patients with oral anticoagulation-associated ICH, including 190 NOAC-related ICH patients, recruited from 2011 to 2015 at 19 tertiary centers across Germany. Imaging, clinical characteristics, and 3-months modified Rankin Scale (mRS) outcomes were compared in NOAC- versus VKA-related ICH patients. Propensity score matching was conducted to adjust for clinically relevant differences in baseline parameters. Subgroup analyses were performed regarding NOAC agent, dosing and present clinically relevant anticoagulatory activity (last intake <12h/24h or NOAC level >30 ng/mL). Results- Despite older age in NOAC patients, there were no relevant differences in clinical and hematoma characteristics between NOAC- and VKA-related ICH regarding baseline hematoma volume (median [interquartile range]: NOAC, 14.7 [5.1-42.3] mL versus VKA, 16.4 [5.8-40.6] mL; P=0.33), rate of hematoma expansion (NOAC, 49/146 [33.6%] versus VKA, 235/688 [34.2%]; P=0.89), and the proportion of patients with unfavorable outcome at 3 months (mRS, 4-6: NOAC 126/179 [70.4%] versus VKA 473/682 [69.4%]; P=0.79). Subgroup analyses revealed that NOAC patients with clinically relevant anticoagulatory effect had higher rates of intraventricular hemorrhage (n/N [%]: present 52/109 [47.7%] versus absent 9/35 [25.7%]; P=0.022) and hematoma expansion (present 35/90 [38.9%] versus absent 5/30 [16.7%]; P=0.040), whereas type of NOAC agent or different NOAC-dosing regimens did not result in relevant differences in imaging characteristics or outcome. Conclusions- If effectively anticoagulated, there are no differences in hematoma characteristics and functional outcome among patients with NOAC- or VKA-related ICH. Clinical Trial Registration- URL: https://www.clinicaltrials.gov . Unique identifier: NCT03093233.

Diagnostic and prognostic benefit of arterial spin labeling in subacute stroke

BACKGROUND AND PURPOSE

Brain perfusion measurement in the subacute phase of stroke may support therapeutic decisions. We evaluated whether arterial spin labeling (ASL), a noninvasive perfusion imaging technique based on magnetic resonance imaging (MRI), adds diagnostic and prognostic benefit to diffusion-weighted imaging (DWI) in subacute stroke.

METHODS

In a single-center imaging study, patients with DWI lesion(s) in the middle cerebral artery (MCA) territory were included. Onset to imaging time was ≤7 days and imaging included ASL and DWI sequences. Qualitative (standardized visual analysis) and quantitative perfusion analyses (region of interest analysis) were performed. Dichotomized early outcome (modified Rankin Scale [mRS] 0-2 vs. 3-6) was analyzed in two logistic regression models. Model 1 included DWI lesion volume, age, vascular pathology, admission NIHSS, and acute stroke treatment as covariates. Model 2 added the ASL-based perfusion pattern to Model 1. Receiver-operating-characteristic (ROC) and area-under-the-curve (AUC) were calculated for both models to assess their predictive power. The likelihood-ratio-test compared both models.

RESULTS

Thirty-eight patients were included (median age 70 years, admission NIHSS 4, onset to imaging time 67 hr, discharge mRS 2). Qualitative perfusion analysis yielded additional diagnostic information in 84% of the patients. In the quantitative analysis, AUC for outcome prediction was 0.88 (95% CI 0.77-0.99) for Model 1 and 0.97 (95% CI 0.91-1.00) for Model 2. Inclusion of perfusion data significantly improved performance and outcome prediction (p = 0.002) of stroke imaging.

CONCLUSIONS

In patients with subacute stroke, our study showed that adding perfusion imaging to structural imaging and clinical data significantly improved outcome prediction. This highlights the usefulness of ASL and noninvasive perfusion biomarkers in stroke diagnosis and management.

A U-Net Deep Learning Framework for High Performance Vessel Segmentation in Patients With Cerebrovascular Disease

Brain vessel status is a promising biomarker for better prevention and treatment in cerebrovascular disease. However, classic rule-based vessel segmentation algorithms need to be hand-crafted and are insufficiently validated. A specialized deep learning method-the U-net-is a promising alternative. Using labeled data from 66 patients with cerebrovascular disease, the U-net framework was optimized and evaluated with three metrics: Dice coefficient, 95% Hausdorff distance (95HD) and average Hausdorff distance (AVD). The model performance was compared with the traditional segmentation method of graph-cuts. Training and reconstruction was performed using 2D patches. A full and a reduced architecture with less parameters were trained. We performed both quantitative and qualitative analyses. The U-net models yielded high performance for both the full and the reduced architecture: A Dice value of ~0.88, a 95HD of ~47 voxels and an AVD of ~0.4 voxels. The visual analysis revealed excellent performance in large vessels and sufficient performance in small vessels. Pathologies like cortical laminar necrosis and a rete mirabile led to limited segmentation performance in few patients. The U-net outperfomed the traditional graph-cuts method (Dice ~0.76, 95HD ~59, AVD ~1.97). Our work highly encourages the development of clinically applicable segmentation tools based on deep learning. Future works should focus on improved segmentation of small vessels and methodologies to deal with specific pathologies.

The choice of embedding media affects image quality, tissue R2 * , and susceptibility behaviors in post-mortem brain MR microscopy at 7.0T

PURPOSE

The quality and precision of post-mortem MRI microscopy may vary depending on the embedding medium used. To investigate this, our study evaluated the impact of 5 widely used media on: (1) image quality, (2) contrast of high spatial resolution gradient-echo (T₁ and T₂ ^* -weighted) MR images, (3) effective transverse relaxation rate (R₂ ^* ), and (4) quantitative susceptibility measurements (QSM) of post-mortem brain specimens.

METHODS

Five formaldehyde-fixed brain slices were scanned using 7.0T MRI in: (1) formaldehyde solution (formalin), (2) phosphate-buffered saline (PBS), (3) deuterium oxide (D₂ O), (4) perfluoropolyether (Galden), and (5) agarose gel. SNR and contrast-to-noise ratii (SNR/CNR) were calculated for cortex/white matter (WM) and basal ganglia/WM regions. In addition, median R₂ ^* and QSM values were extracted from caudate nucleus, putamen, globus pallidus, WM, and cortical regions.

RESULTS

PBS, Galden, and agarose returned higher SNR/CNR compared to formalin and D₂ O. Formalin fixation, and its use as embedding medium for scanning, increased tissue R₂ ^* . Imaging with agarose, D₂ O, and Galden returned lower R₂ ^* values than PBS (and formalin). No major QSM offsets were observed, although spatial variance was increased (with respect to R₂ ^* behaviors) for formalin and agarose.

CONCLUSIONS

Embedding media affect gradient-echo image quality, R₂ ^* , and QSM in differing ways. In this study, PBS embedding was identified as the most stable experimental setup, although by a small margin. Agarose and Galden were preferred to formalin or D₂ O embedding. Formalin significantly increased R₂ ^* causing noisier data and increased QSM variance.

Is Perfusion MRI without Deconvolution Reliable for Mismatch Detection in Acute Stroke? Validation with 15O-Positron Emission Tomography

BACKGROUND

In acute stroke, the magnetic resonance (MR) imaging-based mismatch concept is used to select patients with tissue at risk of infarction for reperfusion therapies. There is however a controversy if non-deconvolved or deconvolved perfusion weighted (PW) parameter maps perform better in tissue at risk prediction and which parameters and thresholds should be used to guide treatment decisions.

METHODS

In a group of 22 acute stroke patients with consecutive MR and quantitative positron emission tomography (PET) imaging, non-deconvolved parameters were validated with the gold standard for penumbral-flow (PF) detection 15O-water PET. Performance of PW parameters was assessed by a receiver operating characteristic curve analysis to identify the accuracy of each PWI map to detect the -upper PF threshold as defined by PET cerebral blood flow <20 mL/100 g/min.

RESULTS

Among normalized non-deconvolved parameters, PW-first moment without delay correction (FM without DC) > 3.6 s (area under the curve [AUC] = 0.89, interquartile range [IQR] 0.85-0.94), PW-maximum of the concentration curve (Cmax) < 0.66 (AUC = 0.92, IQR 0.84-0.96) and PW-time to peak (TTP) > 4.0 s (AUC = 0.92, IQR 0.87-0.94) perform significantly better than other non-deconvolved parameters to detect the PF threshold as defined by PET.

CONCLUSIONS

Non-deconvolved parameters FM without DC, Cmax and TTP are an observer-independent alternative to established deconvolved parameters (e.g., Tmax) to guide treatment decisions in acute stroke.

Boosted Tree Model Reforms Multimodal Magnetic Resonance Imaging Infarct Prediction in Acute Stroke

BACKGROUND AND PURPOSE

Stroke imaging is pivotal for diagnosis and stratification of patients with acute ischemic stroke to treatment. The potential of combining multimodal information into reliable estimates of outcome learning calls for robust machine learning techniques with high flexibility and accuracy. We applied the novel extreme gradient boosting algorithm for multimodal magnetic resonance imaging-based infarct prediction.

METHODS

In a retrospective analysis of 195 patients with acute ischemic stroke, fluid-attenuated inversion recovery, diffusion-weighted imaging, and 10 perfusion parameters were derived from acute magnetic resonance imaging scans. They were integrated to predict final infarct as seen on follow-up T2-fluid-attenuated inversion recovery using the extreme gradient boosting and compared with a standard generalized linear model approach using cross-validation. Submodels for recanalization and persistent occlusion were calculated and were used to identify the important imaging markers. Performance in infarct prediction was analyzed with receiver operating characteristics. Resulting areas under the curve and accuracy rates were compared using Wilcoxon signed-rank test.

RESULTS

The extreme gradient boosting model demonstrated significantly higher performance in infarct prediction compared with generalized linear model in both cross-validation approaches: 5-folds (P<10e-16) and leave-one-out (P<0.015). The imaging parameters time-to-peak, mean transit time, time-to-maximum, and diffusion-weighted imaging were indicated as most valuable for infarct prediction by the systematic algorithm rating. Notably, the performance improvement was higher with 5-folds cross-validation approach than leave-one-out.

CONCLUSIONS

We demonstrate extreme gradient boosting as a state-of-the-art method for clinically applicable multimodal magnetic resonance imaging infarct prediction in acute ischemic stroke. Our findings emphasize the role of perfusion parameters as important biomarkers for infarct prediction. The effect of cross-validation techniques on performance indicates that the intrapatient variability is expressed in nonlinear dynamics of the imaging modalities.

MRI-based mismatch detection in acute ischemic stroke: Optimal PWI maps and thresholds validated with PET

Perfusion-weighted (PW) magnetic resonance imaging (MRI) is used to detect penumbral tissue in acute stroke, but the selection of optimal PW-maps and thresholds for tissue at risk detection remains a matter of debate. We validated the performance of PW-maps with 15O-water-positron emission tomography (PET) in a large comparative PET-MR cohort of acute stroke patients. In acute and subacute stroke patients with back-to-back MRI and PET imaging, PW-maps were validated with 15O-water-PET. We pooled two different cerebral blood flow (CBF) PET-maps to define the critical flow (CF) threshold, (i) quantitative (q)CBF-PET with the CF threshold <20 ml/100 g/min and (ii) normalized non-quantitative (nq)CBF-PET with a CF threshold of <70% (corresponding to <20 ml/100 g/min according to a previously published normogram). A receiver operating characteristic (ROC) curve analysis was performed to specify the accuracy and the optimal critical flow threshold of each PW-map as defined by PET. In 53 patients, (stroke to imaging: 9.8 h; PET to MRI: 52 min) PW-time-to-maximum (Tmax) with a threshold >6.1 s (AUC = 0.94) and non-deconvolved PW-time-to-peak (TTP) >4.8 s (AUC = 0.93) showed the best performance to detect the CF threshold as defined by PET. PW-Tmax with a threshold >6.1 s and TTP with a threshold >4.8 s are the most predictive in detecting the CF threshold for MR-based mismatch definition.

A PET-Guided Framework Supports a Multiple Arterial Input Functions Approach in DSC-MRI in Acute Stroke

BACKGROUND AND PURPOSE

In acute stroke, arterial-input-function (AIF) determination is essential for obtaining perfusion estimates with dynamic susceptibility-weighted contrast-enhanced magnetic resonance imaging (DSC-MRI). Standard DSC-MRI postprocessing applies single AIF selection, ie, global AIF. Physiological considerations, however, suggest that a multiple AIFs selection method would improve perfusion estimates to detect penumbral flow. In this study, we developed a framework based on comparable DSC-MRI and positron emission tomography (PET) images to compare the two AIF selection approaches and assess their performance in penumbral flow detection in acute stroke.

METHODS

In a retrospective analysis of 17 sub(acute) stroke patients with consecutive MRI and PET scans, voxel-wise optimized AIFs were calculated based on the kinetic model as derived from both imaging modalities. Perfusion maps were calculated based on the optimized-AIF using two methodologies: (1) Global AIF and (2) multiple AIFs as identified by cluster analysis. Performance of penumbral-flow detection was tested by receiver-operating characteristics (ROC) curve analysis, ie, the area under the curve (AUC).

RESULTS

Large variation of optimized AIFs across brain voxels demonstrated that there is no optimal single AIF. Subsequently, the multiple-AIF method (AUC range over all maps: .82-.90) outperformed the global AIF methodology (AUC .72-.85) significantly.

CONCLUSIONS

We provide PET imaging-based evidence that a multiple AIF methodology is beneficial for penumbral flow detection in comparison with the standard global AIF methodology in acute stroke.

Abstract WP41: A Multi-Parametric Perfusion Model Improves Assessment of Penumbral Flow in Stroke Imaging

Introduction: Perfusion imaging by DSC-MRI (dynamic susceptibility contrast MRI) is the clinical method of choice for identification of penumbral flow (PF) in acute stroke. To date, the tissue at risk is estimated by a single predefined perfusion map. However, integration of various perfusion parameters may amplify the pathophysiological information and yield better estimation of PF. We therefore combined the common perfusion maps in a generalized linear model (GLM) to predict PF as defined by positron emission tomography (PET).

Methods: In 18 patients with (sub)acute stroke, consecutive DSC-MRI and O15-water PET was performed (median age/NIHSS: 58 y , 12). PF was defined as cerebral-blood-flow (CBF) < 20 mL/100g/min on PET. MRI perfusion maps included: CBF, CBV, MTT, Tmax, TTP (cerebral-blood-volume, mean-transit-time, time-to-maximum and time-to-peak respectively). Probability maps for PF prediction were generated by a) single maps and b) multi-parametric maps (GLM) and underwent cross validation. ROC analysis assessed performance for PF prediction as area-under the curve (AUC).

Results: Single maps showed AUC values between 0.57 and 0.72 (Tmax and CFB showing best performance). The GLM approach yielded an AUC of 0.75. Comparison by the Wilcoxon signed rank test showed that while the absolute difference was moderate, it was significant (p<0.04).

Conclusions: Our results suggest that a multi-parameter perfusion model yields the highest accuracy for PF prediction. This finding, while preliminary, suggest a straight-forward model that can be easily integrated in clinical routine for improved stroke stratification based on the mismatch paradigm. Figure 1: Performance in penumbral flow prediction The graph shows performance in PF prediction for perfusion parameters and GLM. The error-bars represent standard-error. (*) marks significance for p value<0.05.

Moyamoya Vessel Pathology Imaged by Ultra-High-Field Magnetic Resonance Imaging at 7.0 T

BACKGROUND

Prompt diagnosis of vessel pathology and appropriate treatment of moyamoya vasculopathy (MMV) are essential to improve long-term prognosis. The aims of our study were to explore the diagnostic value of ultra-high-field (UHF) magnetic resonance imaging at 7.0 T in MMV patients and to compare the applicability of two different 7.0 T vessel imaging modalities to 3.0 T magnetic resonance angiography (MRA) and digital subtraction angiography (DSA).

METHODS

In a World Health Organization-registered and prospective imaging trial, patients were investigated at 7.0 T magnetization-prepared rapid-acquisition gradient echo (MPRAGE)-MRA and time-of-flight (TOF)-MRA, 3.0 T TOF-MRA, and by DSA.

RESULTS

Six patients were included in our study and evaluated for MMV. 3.0 T TOF-MRA and 7.0 T MPRAGE-MRA were able to depict the complete major vascular tree and confirmed MMV-specific steno-occlusions of major intracranial arteries, as previously identified by DSA. 7.0 T TOF-MRA was limited to visualization of the circle of Willis as well as the internal carotid artery only. Donor vessels for bypass surgery (i.e., branches of superficial temporal artery) could be sufficiently visualized with all magnetic resonance modalities.

CONCLUSIONS

Our results indicate that a specific 7.0 T vascular imaging protocol yields diagnostic information about vessel pathology in MMV that approximates conventional DSA. 7.0 T MPRAGE was superior to 7.0 T TOF-MRA due to shorter scanning times and better brain coverage. To date, however, limited availability of 7.0 T technology in medical facilities as well as technical and procedural constraints excludes a fair amount of patients from the clinical 7.0 T imaging process.

Clinical-Radiological Parameters Improve the Prediction of the Thrombolysis Time Window by Both MRI Signal Intensities and DWI-FLAIR Mismatch

Background: With regard to acute stroke, patients with unknown time from stroke onset are not eligible for thrombolysis. Quantitative diffusion weighted imaging (DWI) and fluid attenuated inversion recovery (FLAIR) MRI relative signal intensity (rSI) biomarkers have been introduced to predict eligibility for thrombolysis, but have shown heterogeneous results in the past. In the present work, we investigated whether the inclusion of easily obtainable clinical-radiological parameters would improve the prediction of the thrombolysis time window by rSIs and compared their performance to the visual DWI-FLAIR mismatch. Methods: In a retrospective study, patients from 2 centers with proven stroke with onset <12 h were included. The DWI lesion was segmented and overlaid on ADC and FLAIR images. rSI mean and SD, were calculated as follows: (mean ROI value/mean value of the unaffected hemisphere). Additionally, the visual DWI-FLAIR mismatch was evaluated. Prediction of the thrombolysis time window was evaluated by the area-under-the-curve (AUC) derived from receiver operating characteristic (ROC) curve analysis. Factors such as the association of age, National Institutes of Health Stroke Scale, MRI field strength, lesion size, vessel occlusion and Wahlund-Score with rSI were investigated and the models were adjusted and stratified accordingly. Results: In 82 patients, the unadjusted rSI measures DWI-mean and -SD showed the highest AUCs (AUC 0.86-0.87). Adjustment for clinical-radiological covariates significantly improved the performance of FLAIR-mean (0.91) and DWI-SD (0.91). The best prediction results based on the AUC were found for the final stratified and adjusted models of DWI-SD (0.94) and FLAIR-mean (0.96) and a multivariable DWI-FLAIR model (0.95). The adjusted visual DWI-FLAIR mismatch did not perform in a significantly worse manner (0.89). ADC-rSIs showed fair performance in all models. Conclusions: Quantitative DWI and FLAIR MRI biomarkers as well as the visual DWI-FLAIR mismatch provide excellent prediction of eligibility for thrombolysis in acute stroke, when easily obtainable clinical-radiological parameters are included in the prediction models.

Abstract WP51: Quantification of the Time of Flight (TOF) Angiography Signal to Predict Grade of Stenosis and Hypoperfusion

Introduction and hypothesis: MR-TOF angiography (magnetic resonance time of flight) offers a rapid, non-invasive assessment of the intracranial vessel status in patients with cerebrovascular diseases. As the signal of the MR-TOF is flow-dependent, we hypothesized that a quantification can predict perfusion of the respective flow territory as well as degree of proximal stenosis.

Methods: Within the PEGASUS study (WHO REG-NR DRKS00003198) we performed intracranial TOF angiography and perfusion imaging with a contrast agent (DSC, dynamic susceptibility-weighted contrast-enhanced) in patients with chronic unilateral stenosis (>70%) or occlusion of the internal carotid artery. Images were acquired on a 3 Tesla MRI (TimTrio, Siemens). The TOF signal was quantified on 2D maximal intensity projections (MIPs): Regions of interest (ROIs) were placed into the M1 segment of the middle cerebral artery (MCA). A TOF ratio was calculated: relTOF[%]=ROIipsi/ROIcontra. The relative cerebral blood flow (relCBF) in the MCA territory was calculated in %. RelCBF and relTOF were correlated (Spearman). Receiver operating characteristic (ROC) analysis defined the performance of the TOF ratio to assess cortical hypoperfusion (defined as relCBF <90%) and vessel pathology (occlusion vs stenosis).

Results: In 40 patients (median 57yrs), we found a moderate correlation for relCBF and relTOF (rho: 0.52, p<0.05). Patients with an occlusion (19/40) showed a significantly lower TOF ratio compared to patients with a stenosis (70% vs. 93%, p<.001). Also, perfusion was significantly reduced in patients with occlusions (median relCBF 89% vs. 95%, p<.05).

The ROC analysis identified a TOF ratio <78% as the best predictor for (i) cortical hypoperfusion (sensitivity/specificity 73%/72%, area under the curve 0.75) and (ii) for an occlusion of the ACI (sens./spec. 79%/86%, area under the curve 0.85).

Conclusion: The intracranial TOF ratio is an easily accessible clinical measure to estimate distal brain perfusion and proximal vessel pathology in patients with chronic stenosis of the internal carotid artery.

Abstract WP50: MRI Biomarkers in Acute Stroke: Addition of Clinical Parameters Improves the Identification of Patients Eligible for Thrombolysis

Introduction: Patients with unknown time from stroke onset, e.g. in wake-up stroke, are not eligible for thrombolyic treatment. Relative signal intensities (rSI) of DWI and FLAIR MRI are biomarkers for eligibility for thrombolysis, but have shown heterogeneous results to date. We investigated if the addition of available clinical parameters improves the prediction of the thrombolysis time window in patients with acute stroke.

Hypothesis: Inclusion of clinical parameters improves the prediction of the thrombolysis time window by quantitative MRI biomarkers

Methods: Patients from two centers with proven stroke and stroke-onset <12 hours were included in a retrospective design. The DWI lesion was segmented and overlaid on ADC and FLAIR maps. rSI mean and standard deviation (std) were calculated: mean VOI value/mean value of the unaffected hemisphere. Prediction of the thrombolysis time window was evaluated by the area-under-the-curve (AUC) of receiver-operating-characteristic (ROC) curve analysis. Age, NIHSS, MRI field strength, lesion size, vessel occlusion and Wahlund-Score were included in adjusted and stratified regression models.

Results: 82 patients were included. In the unadjusted analysis, DWI-mean and -std (AUC: 0.86, 0.87) performed best. Adjustment for clinical parameters significantly improved the performance of FLAIR-mean (0.87) and DWI-std (0.91). The best performance was found for the final stratified and adjusted models of DWI-std (0.94) and FLAIR-mean (0.96). ADC-rSIs showed no clinically acceptable performance in all models.

Conclusion: rSIs of DWI and FLAIR MRI predict eligibility for thrombolysis in acute stroke with high precision, when easily available clinical parameters are included in the prediction.

Walsh-ordered hadamard time-encoded pseudocontinuous ASL (WH pCASL)

PURPOSE

Walsh ordering of Hadamard encoding-matrices and an additional averaging strategy are proposed for Hadamard-encoded pseudocontinuous arterial spin labeling (H-pCASL). In contrast to conventional H-pCASL the proposed method generates more perfusion-weighted images which are accessible already during a running experiment and even from incomplete sets of encoded images.

THEORY

Walsh-ordered Hadamard matrices consist of fully decodable Hadamard submatrices. At any time during a measurement these submatrices may yield perfusion-weighted images, even at runtime and with incomplete datasets. The usage of an additional so-called mirrored matrix for averaging leads to more decodable subboli.

METHODS

Perfusion-weighted images (five healthy volunteers) are generated using both a Walsh-ordered and a corresponding mirrored Hadamard matrix. To test their correctness they are compared with equivalent images from conventional multi postlabeling-delay (PLD) pCASL-measurements.

RESULTS

All predicted perfusion-weighted images could be generated and correlated very well with multi-PLD images. Already small subsets of encoded images, acquired early during the measurement, yielded perfusion-weighted images. The mirrored matrix generates more perfusion-weighted images without time penalty.

CONCLUSION

Early access to perfusion-weighted images despite incomplete datasets allows dynamic adaptation of parameters and increases robustness against artifacts. Thus, the approach may be well suited for clinical applications, where pathologies demand rapid parameter adaptation and increase the chance of artifacts. Magn Reson Med 76:1814-1824, 2016. © 2015 International Society for Magnetic Resonance in Medicine.

Prognostic value of somatosensory evoked potentials, neuron-specific enolase, and S100 for short-term outcome in ischemic stroke

To predict short-term outcome in acute ischemic stroke, we analyzed somatosensory evoked potentials (SEP) and biochemical parameters [neuron-specific enolase (NSE) and S100 protein] in a prospective study with serial measurement. In 31 patients with 1st middle cerebral artery infarction, serum NSE and S100 protein were measured daily between days 1 and 6 poststroke. The N20 and N70 components of the SEP (SEP20 and SEP70) were determined on days 1 and 6. SEP and biochemical markers in stroke patients were compared with a control group. Short-term outcome was assessed by the modified Rankin Scale (mRS) at days 7-10 and was dichotomized between good (mRS 0-2) and poor (mRS ≥3) outcome. Specificity and positive predictive value (PPV) were high at day 1 for SEP (SEP20: 100% for both; SEP70: 93 and 88%, respectively) compared with lower values for NSE (67 and 50%) and S100 (23 and 57%). In contrast, S100 showed the highest sensitivity at day 1 with 77% compared with a relatively low sensitivity of NSE (31%) and SEP (SEP20: 35%, SEP70: 47%). The biochemical markers showed an improving sensitivity over time with best values (>90%) between days 3 and 4 at the expense of a lower specificity. Specificity and PPV of SEP on day 6 was still 100% with sensitivity increasing up to 53% (SEP20) and 60% (SEP70). SEP could early differentiate between good and poor outcome and reliably predict poor outcome. Since biochemical markers and SEP complement each other in the prognosis of stroke, a combined application of these markers seems promising.

Comparison of the 2 Most Popular Deconvolution Techniques for the Detection of Penumbral Flow in Acute Stroke

BACKGROUND AND PURPOSE

Dynamic susceptibility-weighted contrast-enhanced (DSC) magnetic resonance imaging (MRI) is used to identify the tissue-at-risk in acute stroke, but the choice of optimal DSC postprocessing in the clinical setting remains a matter of debate. Using 15O-water positron emission tomography (PET), we validated the performance of 2 common deconvolution methods for DSC-MRI.

METHODS

In (sub)acute stroke patients with consecutive MRI and PET imaging, DSC maps were calculated applying 2 deconvolution methods, standard and block-circulant single value decomposition. We used 2 standardized analysis methods, a region of interest-based and a voxel-based analysis, where PET cerebral blood flow masks of <20 mL/100 g per minute (penumbral flow) and gray matter masks were overlaid on DSC parameter maps. For both methods, receiver operating characteristic curve analysis was performed to identify the accuracy of each DSC-MR map for the detection of PET penumbral flow.

RESULTS

In 18 data sets (median time after stroke onset: 18 hours; median time PET to MRI: 101 minutes), block-circulant single value decomposition showed significantly better performance to detect PET penumbral flow only for mean transit time maps. Time-to-maximum (Tmax) had the highest performance independent of the deconvolution method.

CONCLUSIONS

Block-circulant single value decomposition seems only significantly beneficial for mean transit time maps in (sub)acute stroke. Tmax is likely the most stable deconvolved parameter for the detection of tissue-at-risk using DSC-MRI.

3D GRASE pulsed arterial spin labeling at multiple inflow times in patients with long arterial transit times: comparison with dynamic susceptibility-weighted contrast-enhanced MRI at 3 Tesla

Pulsed arterial spin labeling (PASL) at multiple inflow times (multi-TIs) is advantageous for the measurement of brain perfusion in patients with long arterial transit times (ATTs) as in steno-occlusive disease, because bolus-arrival-time can be measured and blood flow measurements can be corrected accordingly. Owing to its increased signal-to-noise ratio, a combination with a three-dimensional gradient and spin echo (GRASE) readout allows acquiring a sufficient number of multi-TIs within a clinically feasible acquisition time of 5 minutes. We compared this technique with the clinical standard dynamic susceptibility-weighted contrast-enhanced imaging-magnetic resonance imaging in patients with unilateral stenosis >70% of the internal carotid or middle cerebral artery (MCA) at 3 Tesla. We performed qualitative (assessment by three expert raters) and quantitative (region of interest (ROI)/volume of interest (VOI) based) comparisons. In 43 patients, multi-TI PASL-GRASE showed perfusion alterations with moderate accuracy in the qualitative analysis. Quantitatively, moderate correlation coefficients were found for the MCA territory (ROI based: r=0.52, VOI based: r=0.48). In the anterior cerebral artery (ACA) territory, a readout related right-sided susceptibility artifact impaired correlation (ROI based: r=0.29, VOI based: r=0.34). Arterial transit delay artifacts were found only in 12% of patients. In conclusion, multi-TI PASL-GRASE can correct for arterial transit delay in patients with long ATTs. These results are promising for the transfer of ASL to the clinical practice.

Anticoagulant reversal, blood pressure levels, and anticoagulant resumption in patients with anticoagulation-related intracerebral hemorrhage

IMPORTANCE

Although use of oral anticoagulants (OACs) is increasing, there is a substantial lack of data on how to treat OAC-associated intracerebral hemorrhage (ICH).

OBJECTIVE

To assess the association of anticoagulation reversal and blood pressure (BP) with hematoma enlargement and the effects of OAC resumption.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective cohort study at 19 German tertiary care centers (2006-2012) including 1176 individuals for analysis of long-term functional outcome, 853 for analysis of hematoma enlargement, and 719 for analysis of OAC resumption.

EXPOSURES

Reversal of anticoagulation during acute phase, systolic BP at 4 hours, and reinitiation of OAC for long-term treatment.

MAIN OUTCOMES AND MEASURES

Frequency of hematoma enlargement in relation to international normalized ratio (INR) and BP. Incidence analysis of ischemic and hemorrhagic events with or without OAC resumption. Factors associated with favorable (modified Rankin Scale score, 0-3) vs unfavorable functional outcome.

RESULTS

Hemorrhage enlargement occurred in 307 of 853 patients (36.0%). Reduced rates of hematoma enlargement were associated with reversal of INR levels <1.3 within 4 hours after admission (43/217 [19.8%]) vs INR of ≥1.3 (264/636 [41.5%]; P < .001) and systolic BP <160 mm Hg at 4 hours (167/504 [33.1%]) vs ≥160 mm Hg (98/187 [52.4%]; P < .001). The combination of INR reversal <1.3 within 4 hours and systolic BP of <160 mm Hg at 4 hours was associated with lower rates of hematoma enlargement (35/193 [18.1%] vs 220/498 [44.2%] not achieving these values; OR, 0.28; 95% CI, 0.19-0.42; P < .001) and lower rates of in-hospital mortality (26/193 [13.5%] vs 103/498 [20.7%]; OR, 0.60; 95% CI, 0.37-0.95; P = .03). OAC was resumed in 172 of 719 survivors (23.9%). OAC resumption showed fewer ischemic complications (OAC: 9/172 [5.2%] vs no OAC: 82/547 [15.0%]; P < .001) and not significantly different hemorrhagic complications (OAC: 14/172 [8.1%] vs no OAC: 36/547 [6.6%]; P = .48). Propensity-matched survival analysis in patients with atrial fibrillation who restarted OAC showed a decreased HR of 0.258 (95% CI, 0.125-0.534; P < .001) for long-term mortality. Functional long-term outcome was unfavorable in 786 of 1083 patients (72.6%).

CONCLUSIONS AND RELEVANCE

Among patients with OAC-associated ICH, reversal of INR <1.3 within 4 hours and systolic BP <160 mm Hg at 4 hours were associated with lower rates of hematoma enlargement, and resumption of OAC therapy was associated with lower risk of ischemic events. These findings require replication and assessment in prospective studies.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT01829581.

[Ultrahigh field MRI in context of neurological diseases]

Ultrahigh field magnetic resonance imaging (UHF-MRI) has recently gained substantial scientific interest. At field strengths of 7 Tesla (T) and higher UHF-MRI provides unprecedented spatial resolution due to an increased signal-to-noise ratio (SNR). The UHF-MRI method has been successfully applied in various neurological disorders. In neuroinflammatory diseases UHF-MRI has already provided a detailed insight into individual pathological disease processes and elucidated differential diagnoses of several disease entities, e.g. multiple sclerosis (MS), neuromyelitis optica (NMO) and Susac's syndrome. The excellent depiction of normal blood vessels, vessel abnormalities and infarct morphology by UHF-MRI can be utilized in vascular diseases. Detailed imaging of the hippocampus in Alzheimer's disease and the substantia nigra in Parkinson's disease as well as sensitivity to iron depositions could be valuable in neurodegenerative diseases. Current UHF-MRI studies still suffer from small sample sizes, selection bias or propensity to image artefacts. In addition, the increasing clinical relevance of 3T-MRI has not been sufficiently appreciated in previous studies. Although UHF-MRI is only available at a small number of medical research centers it could provide a high-end diagnostic tool for healthcare optimization in the foreseeable future. The potential of UHF-MRI still has to be carefully validated by profound prospective research to define its place in future medicine.

7-Tesla Magnetic Resonance Imaging for Brain Iron Quantification in Homozygous and Heterozygous PANK2 Mutation Carriers

Pantothenate-kinase-associated neurodegeneration (PKAN) is an autosomal recessive disorder characterized by iron deposits in basal ganglia. The aim of this study was to quantify iron concentrations of deep gray matter structures in heterozygous PANK2 mutation carriers and in PKAN patients using quantitative susceptibility mapping MRI. By determining iron concentration, we intended to find mutation-specific brain parenchymal stigmata in heterozygous PANK2 mutation carriers in comparison to age-matched healthy volunteers. We studied 11 heterozygous PANK2 gene mutation carriers (mean age: 43.4 years; standard deviation [SD]: 10.5), who were found to be clinically asymptomatic by neurological examination. These carriers were compared to 2 clinically affected PKAN patients 21 and 32 years of age and to 13 age-matched, healthy controls (mean age: 39.7; SD, 13.6). Scanning was performed on a 7.0-Tesla whole-body scanner applying three-dimensional susceptibility-weighted gradient echo acquisitions. Susceptibility maps were calculated by threshold-based k-space division with single-orientation acquisition. Magnetic susceptibility values, relative to the occipital white matter, were determined for the following regions of interest (ROI): globus pallidus (GP), thalamus, putamen, internal capsule (IC), caudate nucleus, substantia nigra (SN), and red nucleus. Heterozygous PANK2 mutation carriers did not show increased brain iron concentrations, compared to healthy controls (P > 0.05), in any of the examined ROIs. In PKAN patients, more than 3 times higher concentrations of iron were found in the GP, SN, and IC. Our results suggest that heterozygous mutations in PANK2 gene do not cause brain iron accumulation nor do they cause movement disorders.

Stroke: 'time is brain' after stroke, regardless of age and severity

Two recent studies highlight the importance of prompt, coordinated intervention after stroke. A meta-analysis confirms that intravenous thrombolysis is effective within 4.5 h of onset, irrespective of age (below or above 80 years) and stroke severity. Another study demonstrates successful reorganization of care through centralization of stroke services in England.

Accuracy of the spot sign on computed tomography angiography as a predictor of haematoma enlargement after acute spontaneous intracerebral haemorrhage: a systematic review

BACKGROUND

A common early complication of intracerebral haemorrhage (ICH) is haematoma enlargement (HE), a strong independent predictor of a poor outcome. Therapeutic options to limit haematoma progression are currently scarce. Haemostatic therapy may be effective in patients with ICH, but it carries the risk of thromboembolic events in unselected patients. Accurate patient selection would, therefore, be of key importance for delivering potentially successful therapeutic strategies. Currently, there is no gold standard to accurately predict HE. The presence of contrast extravasation within the haematoma on computed tomography angiography (CTA), the 'spot sign', has been reported in several studies and seems a particularly promising marker but lacks a standardised evaluation so far.

SUMMARY

We conducted a systematic review of published data to address the research question: In adults with acute spontaneous ICH, how accurately does the spot sign predict HE on follow-up imaging and thus poor functional outcome or mortality? We searched PubMed and Embase databases (from 1980 to May 2012), using a highly sensitive search strategy and including all studies involving adult patients with spontaneous ICH evaluated with CTA and follow-up CT scans, reporting any measure of clinical outcome, and reporting or allowing calculation of accuracy measures of the spot sign in predicting HE and clinical outcome. Baseline characteristics, accuracy measures and effect measures, as well as bias assessment, were reported according to PRISMA recommendations. The quality of the studies was appraised using an adapted version of the REMARK reporting recommendations. From 259 potentially relevant studies, we finally selected 6 studies (1 of them was a multicentre cohort study) covering a total of 709 patients. Studies varied substantially in terms of size, methodological quality, definitions of terms, outcomes selected and results. In particular, definition of the spot sign was not consistent in all studies. Furthermore, the only outcome measure consistently available was HE, while definitions and analyses of clinical outcomes seemed not adequate. Lastly, the choice of candidate variables for univariate and multivariate analyses did not include all determinants of HE and poor functional outcome. High heterogeneity was demonstrated (I(2): 94% for HE) with substantial potential of bias.

KEY MESSAGES

Studies of the spot sign are diverse and therefore complex to interpret. Our research question could not be answered due to heterogeneity and potential of bias in the selected studies. Further appropriately powered studies using standardised definitions and taking all predictors of HE and poor clinical outcome into account are required for a proper clinical implementation.

DWI intensity values predict FLAIR lesions in acute ischemic stroke

Background and Purpose

In acute stroke, the DWI-FLAIR mismatch allows for the allocation of patients to the thrombolysis window (<4.5 hours). FLAIR-lesions, however, may be challenging to assess. In comparison, DWI may be a useful bio-marker owing to high lesion contrast. We investigated the performance of a relative DWI signal intensity (rSI) threshold to predict the presence of FLAIR-lesions in acute stroke and analyzed its association with time-from-stroke-onset.

Methods

In a retrospective, dual-center MR-imaging study we included patients with acute stroke and time-from-stroke-onset ≤12 hours (group A: n = 49, 1.5T; group B: n = 48, 3T). DW- and FLAIR-images were coregistered. The largest lesion extent in DWI defined the slice for further analysis. FLAIR-lesions were identified by 3 raters, delineated as regions-of-interest (ROIs) and copied on the DW-images. Circular ROIs were placed within the DWI-lesion and labeled according to the FLAIR-pattern (FLAIR+ or FLAIR−). ROI-values were normalized to the unaffected hemisphere. Adjusted and nonadjusted receiver-operating-characteristics (ROC) curve analysis on patient level was performed to analyze the ability of a DWI- and ADC-rSI threshold to predict the presence of FLAIR-lesions. Spearman correlation and adjusted linear regression analysis was performed to assess the relationship between DWI-intensity and time-from-stroke-onset.

Results

DWI-rSI performed well in predicting lesions in FLAIR-imaging (mean area under the curve (AUC): group A: 0.84; group B: 0.85). An optimal mean DWI-rSI threshold was identified (A: 162%; B: 161%). ADC-maps performed worse (mean AUC: A: 0.58; B: 0.77). Adjusted regression models confirmed the superior performance of DWI-rSI. Correlation coefficents and linear regression showed a good association with time-from-stroke-onset for DWI-rSI, but not for ADC-rSI.

Conclusion

An easily assessable DWI-rSI threshold identifies the presence of lesions in FLAIR-imaging with good accuracy and is associated with time-from-stroke-onset in acute stroke. This finding underlines the potential of a DWI-rSI threshold as a marker of lesion age.

Rapid parametric mapping of the longitudinal relaxation time T1 using two-dimensional variable flip angle magnetic resonance imaging at 1.5 Tesla, 3 Tesla, and 7 Tesla

INTRODUCTION

Visual but subjective reading of longitudinal relaxation time (T1) weighted magnetic resonance images is commonly used for the detection of brain pathologies. For this non-quantitative measure, diagnostic quality depends on hardware configuration, imaging parameters, radio frequency transmission field (B1+) uniformity, as well as observer experience. Parametric quantification of the tissue T1 relaxation parameter offsets the propensity for these effects, but is typically time consuming. For this reason, this study examines the feasibility of rapid 2D T1 quantification using a variable flip angles (VFA) approach at magnetic field strengths of 1.5 Tesla, 3 Tesla, and 7 Tesla. These efforts include validation in phantom experiments and application for brain T1 mapping.

METHODS

T1 quantification included simulations of the Bloch equations to correct for slice profile imperfections, and a correction for B1+. Fast gradient echo acquisitions were conducted using three adjusted flip angles for the proposed T1 quantification approach that was benchmarked against slice profile uncorrected 2D VFA and an inversion-recovery spin-echo based reference method. Brain T1 mapping was performed in six healthy subjects, one multiple sclerosis patient, and one stroke patient.

RESULTS

Phantom experiments showed a mean T1 estimation error of (-63±1.5)% for slice profile uncorrected 2D VFA and (0.2±1.4)% for the proposed approach compared to the reference method. Scan time for single slice T1 mapping including B1+ mapping could be reduced to 5 seconds using an in-plane resolution of (2×2) mm2, which equals a scan time reduction of more than 99% compared to the reference method.

CONCLUSION

Our results demonstrate that rapid 2D T1 quantification using a variable flip angle approach is feasible at 1.5T/3T/7T. It represents a valuable alternative for rapid T1 mapping due to the gain in speed versus conventional approaches. This progress may serve to enhance the capabilities of parametric MR based lesion detection and brain tissue characterization.

Influence of acute complications on outcome 3 months after ischemic stroke

BACKGROUND

Early medical complications are potentially modifiable factors influencing in-hospital outcome. We investigated the influence of acute complications on mortality and poor outcome 3 months after ischemic stroke.

METHODS

Data were obtained from patients admitted to one of 13 stroke units of the Berlin Stroke Registry (BSR) who participated in a 3-months-follow up between June 2010 and September 2012. We examined the influence of the cumulative number of early in-hospital complications on mortality and poor outcome (death, disability or institutionalization) 3 months after stroke using multivariable logistic regression analyses and calculated attributable fractions to determine the impact of early complications on mortality and poor outcome.

RESULTS

A total of 2349 ischemic stroke patients alive at discharge from acute care were included in the analysis. Older age, stroke severity, pre-stroke dependency and early complications were independent predictors of mortality 3 months after stroke. Poor outcome was independently associated with older age, stroke severity, pre-stroke dependency, previous stroke and early complications. More than 60% of deaths and poor outcomes were attributed to age, pre-stroke dependency and stroke severity and in-hospital complications contributed to 12.3% of deaths and 9.1% of poor outcomes 3 months after stroke.

CONCLUSION

The majority of deaths and poor outcomes after stroke were attributed to non-modifiable factors. However, early in-hospital complications significantly affect outcome in patients who survived the acute phase after stroke, underlining the need to improve prevention and treatment of complications in hospital.

Combining magnetic resonance imaging within six-hours of symptom onset with clinical follow-up at 24 h improves prediction of 'malignant' middle cerebral artery infarction

BACKGROUND

A large diffusion-weighted imaging lesion ≤six-hours of symptom onset was found to predict the development of 'malignant' middle cerebral artery infarction with high specificity, positive predictive value, and negative predictive value, but sensitivity was low.

HYPOTHESIS

We tested the hypothesis that sensitivity can be improved by adding information from clinical follow-up examination after 24 h.

METHODS

We analyzed data from a prospective, multicenter, observational cohort study of patients with acute ischemic stroke and middle cerebral artery occlusion studied by stroke magnetic resonance imaging ≤six-hours of symptom onset. We used the National Institutes of Health Stroke Scale to assess severity of symptoms after 24 h. We used the Classification and Regression Trees analysis to define the optimal thresholds of diffusion-weighted imaging lesion volume and the National Institutes of Health Stroke Scale after 24 h in patients developing 'malignant' middle cerebral artery infarction. We calculated sensitivity, specificity, positive predictive value, and negative predictive value for two simple predictive models based on acute diffusion-weighted imaging lesion volume alone and acute diffusion-weighted imaging lesion volume together with the National Institutes of Health Stroke Scale after 24 h.

RESULTS

Of 135 patients, 27 (20%) developed a 'malignant' middle cerebral artery infarction. The Classification and Regression Trees analysis identified acute diffusion-weighted imaging lesion ≥78 ml and the National Institutes of Health Stroke Scale score after 24 h ≥22 as optimal cut-offs. Inclusion of the National Institutes of Health Stroke Scale score after 24 h in a simple two-step decision tree increased sensitivity from 0·59 to 0·79, while specificity, positive predictive value, and negative predictive value remained largely unchanged.

CONCLUSION

Clinical follow-up examination after 24 h helps identify patients at risk of 'malignant' middle cerebral artery infarction that are missed by predictive algorithms based on early diffusion-weighted imaging lesion volume alone.

A hidden giant: Wallenberg syndrome and aortal wall thickening as an atypical presentation of a giant cell arteritis

We report a case of a 73-year-old woman with a brainstem stroke presenting as Wallenberg syndrome. By transoesophageal echocardiography and combined 18F-fluordeoxyglucose positron emission and CT (18F-FDG PET/CT), the diagnosis of large artery vasculitis owing to giant cell arteritis was confirmed. In the absence of classical clinical signs, the examination of the large extracranial vessels by ultrasound and 18F-FDG PET/CT played the key role in detecting a widespread vasculitis.

Intensified secondary prevention intending a reduction of recurrent events in TIA and minor stroke patients (INSPiRE-TMS): a protocol for a randomised controlled trial

Background

Patients with recent stroke or TIA are at high risk for new vascular events. Several evidence based strategies in secondary prevention of stroke are available but frequently underused. Support programs with multifactorial risk factor modifications after stroke or TIA have not been investigated in large-scale prospective controlled trials so far. INSPiRE-TMS is a prospective, multi-center, randomized open intervention trial for intensified secondary prevention after minor stroke and TIA.

Methods/design

Patients with acute TIA or minor stroke admitted to the participating stroke centers are screened and recruited during in-hospital stay. Patients are randomised in a 1:1 ratio to intervention (support program) and control (usual care) arms. Inclusion of 2.082 patients is planned. The support program includes cardiovascular risk factor measurement and feedback, monitoring of medication adherence, coaching in lifestyle modifications, and active involvement of relatives. Standardized motivational interviewing is used to assess and enhance patients’ motivation. Primary objective is a reduction of new major vascular events defined as nonfatal stroke and myocardial infarction or vascular death. Recruitment time is planned for 3.5 years, follow up time is at least 2 years for every patient resulting in a total study time of 5 years (first patient in to last patient out).

Discussion

Given the high risk for vascular re-events in acute stroke and the available effective strategies in secondary prevention, the INSPIRE-TMS support program has the potential to lead to a relevant reduction of recurrent events and a prolongation of the event-free survival time. The trial will provide the basis for the decision whether an intensified secondary prevention program after stroke should be implemented into regular care. A cost-effectiveness evaluation will be performed.

Trial registration

clinicaltrials.gov: 01586702

Pregnancy outcome following use of levodopa, pramipexole, ropinirole, and rotigotine for restless legs syndrome during pregnancy: a case series

BACKGROUND

Restless legs syndrome (RLS) is related to parity, and its symptoms may worsen during pregnancy. Treatment with levodopa or dopamine agonists is the first-line therapy for RLS; however, there are limited data on treatment in pregnancy. We therefore assessed the safety of levodopa, pramipexole, rotigotine, and ropinirole in pregnancy.

METHODS

Prospective documentation of pregnancies exposed to levodopa, pramipexole, rotigotine, and ropinirole between 1998 and 2011 was evaluated as to their outcome (teratogenicity or fetotoxicity) by the Berlin Institute for Clinical Teratology and Drug Risk Assessment in Pregnancy.

RESULTS

We were able to complete 59 pregnancy outcomes exposed to RLS pharmacotherapy. For specific treatments, the numbers of exposed pregnancies/live born children/spontaneous abortions/induced abortions/malformations were as follows: levodopa only: 38/29 (one pair of twins)/3/7/3; pramipexole only: 12/9/3/0/0; rotigotine only: 2/2/0/0/0; ropinirole only: 3/2/0/1/0; levodopa combined with pramipexole: 3/3/0/0/0; levodopa combined with ropinirole: 1/1/0/0/0. No major birth defects were found with any RLS treatment, and three infants exposed to levodopa had minor anomalies.

CONCLUSIONS

In our small prospective case series, there was no increased risk above baseline for major malformations or other adverse outcomes for levodopa and pramipexole. If necessary, levodopa treatment may be considered as an alternative to cabergoline, for which safety has been well documented in pregnancy.

Refining the mismatch concept in acute stroke: lessons learned from PET and MRI

In ischemic stroke, positron-emission tomography (PET) established the imaging-based concept of penumbra. It defines hypoperfused, but functionally impaired, tissue with preserved viability that can be rescued by timely reperfusion. Diffusion-weighted and perfusion-weighted (PW) magnetic resonance imaging (MRI) translated the concept of penumbra to the concept of mismatch. However, the use of mismatch-based patient stratification for reperfusion therapy remains a matter of debate. The equivalence of mismatch and penumbra, as well as the validity of the classical mismatch concept is questioned for several reasons. First, methodological differences between PET and MRI lead to different definitions of the tissue at risk. Second, the mismatch concept is still poorly standardized among imaging facilities causing relevant variability in stroke research. Third, relevant conceptual issues (e.g., the choice of the adequate perfusion measure, the best quantitative approach to perfusion maps, and the required size of the mismatch) need further refinement. Fourth, the use of single thresholds does not account for the physiological heterogeneity of the penumbra and probabilistic approaches may be more promising. The implementation of this current knowledge into an optimized state-of-the-art mismatch model and its validation in clinical stroke studies remains a major challenge for future stroke research.

Ultrahigh-field MRI in human ischemic stroke--a 7 tesla study

Introduction

Magnetic resonance imaging (MRI) using field strengths up to 3 Tesla (T) has proven to be a powerful tool for stroke diagnosis. Recently, ultrahigh-field (UHF) MRI at 7 T has shown relevant diagnostic benefits in imaging of neurological diseases, but its value for stroke imaging has not been investigated yet. We present the first evaluation of a clinically feasible stroke imaging protocol at 7 T. For comparison an established stroke imaging protocol was applied at 3 T.

Methods

In a prospective imaging study seven patients with subacute and chronic stroke were included. Imaging at 3 T was immediately followed by 7 T imaging. Both protocols included T1-weighted 3D Magnetization-Prepared Rapid-Acquired Gradient-Echo (3D-MPRAGE), T2-weighted 2D Fluid Attenuated Inversion Recovery (2D-FLAIR), T2-weighted 2D Fluid Attenuated Inversion Recovery (2D-T2-TSE), T2* weighted 2D Fast Low Angle Shot Gradient Echo (2D-HemoFLASH) and 3D Time-of-Flight angiography (3D-TOF).

Results

The diagnostic information relevant for clinical stroke imaging obtained at 3 T was equally available at 7 T. Higher spatial resolution at 7 T revealed more anatomical details precisely depicting ischemic lesions and periinfarct alterations. A clear benefit in anatomical resolution was also demonstrated for vessel imaging at 7 T. RF power deposition constraints induced scan time prolongation and reduced brain coverage for 2D-FLAIR, 2D-T2-TSE and 3D-TOF at 7 T versus 3 T.

Conclusions

The potential of 7 T MRI for human stroke imaging is shown. Our pilot study encourages a further evaluation of the diagnostic benefit of stroke imaging at 7 T in a larger study.