Efficacy of Cerebrolysin Treatment as an Add-On Therapy to Mechanical Thrombectomy in Patients With Acute Ischemic Stroke Due to Large Vessel Occlusion: Study Protocol for a Prospective, Open Label, Single-Center Study With 12 Months of Follow-Up.

This study is designed to determine the efficacy of Cerebrolysin treatment as an add-on therapy to mechanical thrombectomy (MT) in reducing global disability in subjects with acute ischemic stroke (AIS). We have planned a single center, prospective, open-label, single-arm study with a 12-month follow-up of 50 patients with moderate to severe AIS, with a small established infarct core and with good collateral circulation who achieve significant reperfusion following MT and who receive additional Cerebrolysin within 8 h of stroke onset compared to 50 historical controls treated with MT alone, matched for age, clinical severity, occlusion location, baseline perfusion lesion volume, onset to reperfusion time, and use of iv thrombolytic therapy. The primary outcome measure will be the overall proportion of subjects receiving Cerebrolysin compared to the control group experiencing a favorable functional outcome (by modified Rankin Scale 0-2) at 90 days, following stroke onset. The secondary objectives are to determine the efficacy of Cerebrolysin as compared to the control group in reducing the risk of symptomatic secondary hemorrhagic transformation, improving neurological outcomes (NIHSS 0-2 at day 7, day 30, and 90), reducing mortality rates (over the 90-day and 12 months study period), and improving: activities of daily living (by Barthel Index), health-related quality of life (EQ-5D-5L) assessed at day 30, 90, and at 12 months. The other measures of efficacy in the Cerebrolysin group will include: assessment of final stroke volume and penumbral salvage (measured by CT/CTP at 30 days) and its change compared to baseline volume, changes over time in language function (by the 15-item Boston Naming Test), hemispatial neglect (by line bisection test), global cognitive function (by The Montreal Cognitive Assessment), and depression (by Hamilton Depression Rating Scale) between day 30 and day 90 assessments). The patients will receive 30 ml of Cerebrolysin within 8 h of AIS stroke onset and continue treatment once daily until day 21 (first cycle) and they will receive a second cycle of treatment (30 ml/d for 21 days given in the Outpatient Department or Neurorehabilitation Clinic) from day 69 to 90.

Diagnostic accuracy of automated occlusion detection in CT angiography using e-CTA.

BACKGROUND AND AIM: The aim of this study was to assess the diagnostic accuracy of e-CTA (product name) (Brainomix) in the automatic detection of large vessel occlusions in anterior circulation stroke. METHODS: Of 487 CT angiographies from patients with large vessel occlusions stroke, 327 were used to train the algorithm while the remaining cases together with 140 negative CT angiographies were used to validate its performance against ground truth. Of these 301 cases, 144 were randomly selected and used for an additional comparative analysis against 4 raters. Sensitivity, specificity, positive and negative predictive value (PPV and NPV), accuracy and level of agreement with ground truth (Cohen's Kappa) were determined and compared to the performance of a neuroradiologist, a radiology resident, and two neurology residents. RESULTS: e-CTA had a sensitivity and specificity of 0.84 (0.77-0.89) and 0.96 (0.91-0.98) respectively for the detection of any large vessel occlusions on the correct side in the whole validation cohort. This performance was identical in the comparative analysis subgroup and was within the range of physicians at different levels of expertise: 0.86-0.97 and 0.91-1.00, respectively. For the detection of proximal occlusions, it was 0.92 (0.84-0.96) and 0.98 (0.94-1.00) for the whole cohort and 0.93 (0.80-0.98) and 1.00 (0.95-1.00) for the comparative analysis, respectively for e-CTA. The range was 0.8-0.97 for sensitivity and 0.97-1.00 for specificity for the four physicians. CONCLUSIONS: The performance of e-CTA in detecting any large vessel occlusions is comparable to less experienced physicians but is similar to experienced physicians for detecting proximal large vessel occlusions.

A Novel Automated Calculation of Basal Cistern Effacement Status on Computed Tomographic Imaging in Traumatic Brain Injury.

Introduction To predict patient outcomes in traumatic brain injury (TBI) lesions, various scores have been proposed, which use objective assessments. These scores, however, rely on the observer's ability to determine them. This study presents a comprehensive, reproducible, and more anatomically stratified objective measurement of the degree of basal cistern effacement in brain computed tomographic (CT) scan images. Methods Patients with TBI admitted from August 2015 to February 2016 were included. The control group consisted of non-trauma patients, who had normal brain CT scans. The images were analyzed by an automated volumetric compression ratio (CR) defined as the volume ratio between the parenchymal tissue and the cerebrospinal fluid (CSF) in the basal cisterns. This value was compared with the TBI severity recorded at each patient's admission and a consensus score of the basal cisterns' degree of effacement by manual analysis. Results Seventy-three TBI patients were admitted. The mean admission Glasow Coma Scale (GCS) score was 9. In the non-TBI control group, 29 patients were enrolled. The average kappa value for the inter-observer agreement was 0.583. The CR had an inverse linear relationship with the severity of the TBI and the degree of effacement of the basal cisterns. The correlation between the CR value in the midbrain and the specialists' consensus determination was statistically significant (p < 0.01). The CR also showed a difference between the TBI and the control groups (p 0.0001). Conclusions The automated CR is a useful objective variable to determine the degree of basal cistern effacement. The proposed ratio has a good correlation with the classical basal cistern effacement classification and TBI severity.

Collateral Automation for Triage in Stroke: Evaluating Automated Scoring of Collaterals in Acute Stroke on Computed Tomography Scans.

Computed tomography angiography (CTA) collateral scoring can identify patients most likely to benefit from mechanical thrombectomy and those more likely to have good outcomes and ranges from 0 (no collaterals) to 3 (complete collaterals). In this study, we used a machine learning approach to categorise the degree of collateral flow in 98 patients who were eligible for mechanical thrombectomy and generate an e-CTA collateral score (CTA-CS) for each patient (e-STROKE SUITE, Brainomix Ltd., Oxford, UK). Three experienced neuroradiologists (NRs) independently estimated the CTA-CS, first without and then with knowledge of the e-CTA output, before finally agreeing on a consensus score. Addition of the e-CTA improved the intraclass correlation coefficient (ICC) between NRs from 0.58 (0.46-0.67) to 0.77 (0.66-0.85, p = 0.003). Automated e-CTA, without NR input, agreed with the consensus score in 90% of scans with the remaining 10% within 1 point of the consensus (ICC 0.93, 0.90-0.95). Sensitivity and specificity for identifying favourable collateral flow (collateral score 2-3) were 0.99 (0.93-1.00) and 0.94 (0.70-1.00), respectively. e-CTA correlated with the Alberta Stroke Programme Early CT Score (Spearman correlation 0.46, p < 0.001) highlighting the value of good collateral flow in maintaining tissue viability prior to reperfusion. In conclusion, -e-CTA provides a real-time and fully automated approach to collateral scoring with the potential to improve consistency of image interpretation and to independently quantify collateral scores even without expert rater input.

Multi-object segmentation framework using deformable models for medical imaging analysis.

Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed framework has a wide range of applications especially in the presence of adjacent structures of interest or under intra-structure inhomogeneities giving excellent quantitative results.