Intracranial vessel perforation is a peri-procedural complication during endovascular therapy (EVT). Prompt recognition is important as its occurrence is strongly associated with unfavorable treatment outcomes. However, perforations can be hard to detect because they are rare, can be subtle, and the interventionalist is working under time pressure and focused on treatment of vessel occlusions. Automatic detection holds potential to improve rapid identification of intracranial vessel perforation. In this work, we present the first study on automated perforation detection and localization on X-ray digital subtraction angiography (DSA) image series. We adapt several state-of-the-art single-frame detectors and further propose temporal modules to learn the progressive dynamics of contrast extravasation. Application-tailored loss function and post-processing techniques are designed. We train and validate various automated methods using two national multi-center datasets (i.e., MR CLEAN Registry and MR CLEAN-NoIV Trial), and one international multi-trial dataset (i.e., the HERMES collaboration). With ten-fold cross-validation, the proposed methods achieve an area under the curve (AUC) of the receiver operating characteristic of 0.93 in terms of series level perforation classification. Perforation localization precision and recall reach 0.83 and 0.70 respectively. Furthermore, we demonstrate that the proposed automatic solutions perform at similar level as an expert radiologist.

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The presence of collaterals and high thrombus permeability are associated with good functional outcomes after an acute ischaemic stroke. We aim to understand the combined effect of the collaterals and thrombus permeability on cerebral blood flow during an acute ischaemic stroke. A cerebral blood flow model including the leptomeningeal collateral circulation is used to simulate cerebral blood flow during an acute ischaemic stroke. The collateral circulation is varied to capture the collateral scores: absent, poor, moderate and good. Measurements of the transit time, void fraction and thrombus length in acute ischaemic stroke patients are used to estimate thrombus permeability. Estimated thrombus permeability ranges between 10-7 and 10-4 mm2. Measured flow rates through the thrombus are small and the effect of a permeable thrombus on brain perfusion during stroke is small compared with the effect of collaterals. Our simulations suggest that the collaterals are a dominant factor in the resulting infarct volume after a stroke.

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The collateral score is an important biomarker in decision making for endovascular treatment (EVT) of patients with ischemic stroke. The existing collateral grading systems are based on visual inspection and prone to subjective interpretation and interobserver variation. The purpose of our work is the development of an automatic collateral scoring method. In this work, we present a method that is inspired by human collateral scoring. Firstly, we define an anatomical region by atlas-based registration and extract vessel structures using a deep convolutional neural network. From this, high-level features based on the ratios of vessel length and volume of the occluded and the contralateral side are defined. Multi-class classification models are used to map the feature space to a four-grade collateral score and a quantitative score. The dataset used for training, validation and testing is from a registry of images acquired in clinical routine at multiple medical centers. The model performance is tested on 269 subjects, achieving an accuracy of 0.8. The dichotomized collateral score accuracy is 0.9. The error is comparable to the interobserver variation, the results are comparable to the performance of two radiologists with 10 to 30 years of experience.

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Purpose: Thrombus perviousness has been associated with favorable functional outcome in acute ischemic stroke (AIS) patients. Measuring thrombus perviousness on CTA may be suboptimal due to potential delay in contrast agent arrival in occluded arteries at the moment of imaging. Dynamic sequences acquired over time can potentially overcome this issue. We investigate if dynamic CTA has added value in assessing thrombus perviousness. Methods: Prospectively collected image data of AIS patients with proven occlusion of the anterior or posterior circulation with thin-slice multi-phase CTA (MCTA) and non-contrast CT were co-registered (n = 221). Thrombus attenuation increase (TAI; a perviousness measure) was measured for the arterial, venous, and delayed phase of the MCTA and time-invariant CTAs (TiCTA). Associations with favorable clinical outcome (90-day mRS ≤ 2) were assessed using univariate and multivariable regressions and calculating areas under receiver operating curves (AUC). Results: TAI determined from the arterial phase CTA was superior in the association with favorable outcome with OR = 1.21 per 10 HU increase (95%CI 1.04–1.41, AUC 0.62, p = 0.014) compared to any other phase (venous 1.14(95%CI 1.01–1.30, AUC 0.58, p = 0.033), delayed 1.046(95%CI 0.919–1.19, AUC 0.53, p = 0.50)), and TiCTA (1.15(95%CI 1.02–1.30, AUC 0.60, p = 0.022). In the multivariable model, only TAI on arterial phase was significantly associated with favorable outcome (aOR 1.59, 95%CI 1.04–2.43, p = 0.032). Conclusion: Association between TAI with functional outcome was optimal on arterial-phase CTA such that dynamic CTA imaging has no additional benefits in current thrombus perviousness assessment, thereby suggesting that the delay of contrast arrival at the clot is a key variable for patient functional outcome.

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Purpose
This paper presents and studies a framework for reliable modeling of diffusion MRI using a data-acquisition adaptive prior.

Methods
Automated relevance determination estimates the mean of the posterior distribution of a rank-2 dual tensor model exploiting Jeffreys prior (JARD). This data-acquisition prior is based on the Fisher information matrix and enables the assessment whether two tensors are mandatory to describe the data. The method is compared to Maximum Likelihood Estimation (MLE) of the dual tensor model and to FSL’s ball-and-stick approach.

Results
Monte Carlo experiments demonstrated that JARD’s volume fractions correlated well with the ground truth for single and crossing fiber configurations. In single fiber configurations JARD automatically reduced the volume fraction of one compartment to (almost) zero. The variance in fractional anisotropy (FA) of the main tensor component was thereby reduced compared to MLE. JARD and MLE gave a comparable outcome in data simulating crossing fibers. On brain data, JARD yielded a smaller spread in FA along the corpus callosum compared to MLE. Tract-based spatial statistics demonstrated a higher sensitivity in detecting age-related white matter atrophy using JARD compared to both MLE and the ball-and-stick approach.

Conclusions
The proposed framework offers accurate and precise estimation of diffusion properties in single and dual fiber regions.
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Background and Purpose - Preclinical studies showed that thrombus permeability improves recombinant tissue-type plasminogen activator (r-tPA) efficacy. We hypothesize that thrombus permeability estimated from radiological imaging is associated with improved recanalization after treatment with intravenously administered r-tPA (r-tPA) and with better functional outcome. Methods - We assessed thrombus attenuation increase (TAI) in patients from the Dutch Acute Stroke Study with an occlusion of an intracranial artery on computed tomographic angiography. Patients were included within 9 hours after the stroke onset. After dichotomization of TAI as pervious or impervious, logistic regressions analyses were performed to estimate associations of intravenous r-tPA therapy with complete recanalization and with favorable functional outcome (modified Rankin Scale score of ≤2). Results - Three hundred eight patients matched the inclusion criteria. The median TAI was 20.1 (interquartile range, 8.5-37.8) Hounsfield unit (HU). We found a significant increase in the odds of complete recanalization with increasing TAI for patients treated with intravenous r-tPA (P=0.030). One hundred thirty-one (42%) thrombi were classified as pervious with TAI of ≥23 HU. In patients with a pervious thrombus, complete recanalization was more frequent after treatment with intravenous r-tPA than after conservative treatment (odds ratio, 6.26; 95% confidence interval, 2.4-16.8; P

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BACKGROUNDANDPURPOSE: Hemodynamics are thought to play an important role in the rupture of intracranial aneurysms.Wetested whether hemodynamics, determined from computational fluid dynamics models, have additional value in discriminating ruptured and unruptured aneurysms. Such discriminative power could provide better prediction models for rupture. MATERIALS AND METHODS: A cross-sectional study was performed on patients eligible for endovascular treatment, including 55 ruptured and 62 unruptured aneurysms. Association with rupture status was tested for location, aneurysm type, and 4 geometric and 10 hemodynamic parameters. Patient-specific spatiotemporal velocities measured with phase-contrast MR imaging were used as inflow conditions for computational fluid dynamics. To assess the additional value of hemodynamic parameters, we performed 1 univariate and 2 multivariate analyses: 1 traditional model including only location and geometry and 1 advanced model that included patient-specific hemodynamic parameters. RESULTS: In the univariate analysis, high-risk locations (anterior cerebral arteries, posterior communicating artery, and posterior circulation), daughter sacs, unstable inflow jets, impingements at the aneurysm body, and unstable complex flow patterns were significantly present more often in ruptured aneurysms. In both multivariate analyses, only the high-risk location (OR, 3.92; 95% CI, 1.77-8.68) and the presence of daughter sacs (OR, 2.79; 95% CI, 1.25-6.25) remained as significant independent determinants. CONCLUSIONS: In this study population of patients eligible for endovascular treatment, we found no independent additional value of aneurysmal hemodynamics in discriminating rupture status, despite high univariate associations. Only traditional parameters (high-risk location and the presence of daughter sacs) were independently associated with ruptured aneurysms.

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