Recommendations for imaging of acute ischemic stroke: a scientific statement from the American Heart Association

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Technical Report

Advanced diagnostic imaging modalities, including ultrasonography, computed tomography, and magnetic resonance imaging, are key components in the evaluation and management of pediatric patients presenting to the emergency department. Advances in imaging technology have led to the availability of faster and more accurate tools to improve patient care. Notwithstanding these advances, it is important for physicians, physician assistants, and nurse practitioners to understand the risks and limitations associated with advanced imaging in children and to limit imaging studies that are considered low value, when possible. This technical report provides a summary of imaging strategies for specific conditions where advanced imaging is commonly considered in the emergency department. As an accompaniment to the policy statement, this document provides resources and strategies to optimize advanced imaging, including clinical decision support mechanisms, teleradiology, shared decision-making, and rationale for deferred imaging for patients who will be transferred for definitive care.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Technical Report

Advanced diagnostic imaging modalities, including ultrasonography, computed tomography, and magnetic resonance imaging (MRI), are key components in the evaluation and management of pediatric patients presenting to the emergency department. Advances in imaging technology have led to the availability of faster and more accurate tools to improve patient care. Notwithstanding these advances, it is important for physicians, physician assistants, and nurse practitioners to understand the risks and limitations associated with advanced imaging in children and to limit imaging studies that are considered low value, when possible. This technical report provides a summary of imaging strategies for specific conditions where advanced imaging is commonly considered in the emergency department. As an accompaniment to the policy statement, this document provides resources and strategies to optimize advanced imaging, including clinical decision support mechanisms, teleradiology, shared decision-making, and rationale for deferred imaging for patients who will be transferred for definitive care.

GPT-4 Performance for Neurologic Localization

Background and Objectives

In health care, large language models such as Generative Pretrained Transformers (GPTs), trained on extensive text datasets, have potential applications in reducing health care disparities across regions and populations. Previous software developed for lesion localization has been limited in scope. This study aims to evaluate the capability of GPT-4 for lesion localization based on clinical presentation.

Methods

GPT-4 was prompted using history and neurologic physical examination (H&P) from published cases of acute stroke followed by questions for clinical reasoning with answering for "single or multiple lesions," "side," and "brain region" using Zero-Shot Chain-of-Thought and Text Classification prompting. GPT-4 output on 3 separate trials for each of 46 cases was compared with imaging-based localization.

Results

GPT-4 successfully processed raw text from H&P to generate accurate neuroanatomical localization and detailed clinical reasoning. Performance metrics across trial-based analysis for specificity, sensitivity, precision, and F1-score were 0.87, 0.74, 0.75, and 0.74, respectively, for side; 0.94, 0.85, 0.84, and 0.85, respectively, for brain region. Class labels within the brain region were similarly high for all regions except the cerebellum and were also similar when considering all 3 trials to examine metrics by case. Errors were due to extrinsic causes-inadequate information in the published cases, and intrinsic causes-failures of logic or inadequate knowledge base.

Discussion

This study reveals capabilities of GPT-4 in the localization of acute stroke lesions, showing a potential future role as a clinical tool in neurology.

CT Perfusion Derived rCBV < 42% Lesion Volume Is Independently Associated with Followup FLAIR Infarct Volume in Anterior Circulation Large Vessel Occlusion

Pretreatment CT Perfusion (CTP) parameter rCBV < 42% lesion volume has recently been shown to predict 90-day mRS. In this study, we aim to assess the relationship between rCBV < 42% and a radiographic follow-up infarct volume delineated on FLAIR images. In this retrospective evaluation of our prospectively collected database, we included acute stroke patients triaged by multimodal CT imaging, including CT angiography and perfusion imaging, with confirmed anterior circulation large vessel occlusion between 9 January 2017 and 10 January 2023. Follow-up FLAIR imaging was used to determine the final infarct volume. Student t, Mann-Whitney-U, and Chi-Square tests were used to assess differences. Spearman's rank correlation and linear regression analysis were used to assess associations between rCBV < 42% and follow-up infarct volume on FLAIR. In total, 158 patients (median age: 68 years, 52.5% female) met our inclusion criteria. rCBV < 42% (ρ = 0.56, p < 0.001) significantly correlated with follow-up-FLAIR infarct volume. On multivariable linear regression analysis, rCBV < 42% lesion volume (beta = 0.60, p < 0.001), ASPECTS (beta = -0.214, p < 0.01), mTICI (beta = -0.277, p < 0.001), and diabetes (beta = 0.16, p < 0.05) were independently associated with follow-up infarct volume. The rCBV < 42% lesion volume is independently associated with FLAIR follow-up infarct volume.

CT perfusion in stroke: Comparing conventional and RAPID automated software

CT perfusion (CTP) imaging is increasingly used for routine evaluation of acute ischemic stroke. Knowledge about the different types of CTP software, imaging acquisition and post-processing, and interpretation is crucial for appropriate patient selection for reperfusion therapy. Conventional vendor-provided CTP software differentiates between ischemic penumbra and core infarct using the tiebreaker of critically reduced cerebral blood volume (CBV) values within brain regions showing abnormally elevated time parameters like mean transit time (MTT) or time to peak (TTP). On the other hand, RAPID automated software differentiates between ischemic penumbra and core infarct using the tiebreaker of critically reduced cerebral blood flow (CBF) values within brain regions showing abnormally elevated time to maximum (Tmax). Additionally, RAPID calculates certain indices that confer prognostic value, such as the hypoperfusion and CBV index. In this review, we aim to familiarize the reader with the technical principles of CTP imaging, compare CTP maps generated by conventional and RAPID software, and discuss important thresholds for reperfusion and prognostic indices. Lastly, we discuss common pitfalls to help with the accurate interpretation of CTP imaging.

Simultaneous perfusion, diffusion, T2 *, and T1 mapping with MR fingerprinting

PURPOSE

Quantitative mapping of brain perfusion, diffusion, T2 *, and T1 has important applications in cerebrovascular diseases. At present, these sequences are performed separately. This study aims to develop a novel MRI technique to simultaneously estimate these parameters.

METHODS

This sequence to measure perfusion, diffusion, T2 *, and T1 mapping with magnetic resonance fingerprinting (MRF) was based on a previously reported MRF-arterial spin labeling (ASL) sequence, but the acquisition module was modified to include different TEs and presence/absence of bipolar diffusion-weighting gradients. We compared parameters derived from the proposed method to those derived from reference methods (i.e., separate sequences of MRF-ASL, conventional spin-echo DWI, and T2 * mapping). Test-retest repeatability and initial clinical application in two patients with stroke were evaluated.

RESULTS

The scan time of our proposed method was 24% shorter than the sum of the reference methods. Parametric maps obtained from the proposed method revealed excellent image quality. Their quantitative values were strongly correlated with those from reference methods and were generally in agreement with values reported in the literature. Repeatability assessment revealed that ADC, T2 *, T1 , and B1 + estimation was highly reliable, with voxelwise coefficient of variation (CoV) <5%. The CoV for arterial transit time and cerebral blood flow was 16% ± 3% and 25% ± 9%, respectively. The results from the two patients with stroke demonstrated that parametric maps derived from the proposed method can detect both ischemic and hemorrhagic stroke.

CONCLUSION

The proposed method is a promising technique for multi-parametric mapping and has potential use in patients with stroke.

Structural Brain Injury on Brain Magnetic Resonance Imaging in Acute Respiratory Distress Syndrome

BACKGROUND

Acute respiratory distress syndrome (ARDS) is an acute inflammatory respiratory failure condition that may be associated with brain injury. We aimed to describe the types of structural brain injuries detected by brain magnetic resonance imaging (MRI) among patients with ARDS.

METHODS

We retrospectively reviewed and collected data on brain injuries as detected by brain MRI during index hospitalization of all patients with ARDS at a single tertiary center in the United States from January 2010 to October 2018 (pre-COVID era). Structural brain injuries were classified as cerebral ischemia (ischemic infarct and hypoxic-ischemic brain injury) or cerebral hemorrhage (intraparenchymal hemorrhage, cerebral microbleeds, subarachnoid hemorrhage, and subdural hematoma). Descriptive statistics were conducted.

RESULTS

Of the 678 patients with ARDS, 66 (9.7%) underwent brain MRI during their ARDS illness. The most common indication for brain MRI was encephalopathy (45.4%), and the median time from hospital admission to MRI was 10 days (interquartile range 4-17). Of 66 patients, 29 (44%) had MRI evidence of brain injury, including cerebral ischemia in 33% (22 of 66) and cerebral hemorrhage in 21% (14 of 66). Among those with cerebral ischemia, common findings were bilateral globus pallidus infarcts (n = 7, 32%), multifocal infarcts (n = 5, 23%), and diffuse hypoxic-ischemic brain injury (n = 3, 14%). Of those with cerebral hemorrhage, common findings were cerebral microbleeds (n = 12, 86%) and intraparenchymal hemorrhage (n = 2, 14%). Patients with ARDS with cerebral hemorrhage had significantly greater use of rescue therapies, including prone positioning (28.6% vs. 5.8%, p = 0.03), inhaled vasodilator (35.7% vs. 11.5%, p = 0.046), and recruitment maneuver (14.3% vs. 0%, p = 0.04).

CONCLUSIONS

Structural brain injury was not uncommon among selected patients with ARDS who underwent brain MRI. The majority of brain injuries seen were bilateral globus pallidus infarcts and cerebral microbleeds.

Predicting Short- and Long-Term Functional Outcomes Based on Serum S100B Protein Levels in Patients with Ischemic Stroke

BACKGROUND

Ischemic stroke is one of the leading causes of mortality and disability. The neuroimaging methods are the gold standard for diagnostics. Biomarkers of cerebral ischemia are considered to be potentially helpful in the determination of the etiology and prognosis of patients with ischemic stroke.

AIM

This study aimed to investigate the usefulness of serum S100B protein levels as a short- and long-term prognostic factor in patients with ischemic stroke.

STUDY DESIGN AND METHODS

The study group comprised 65 patients with ischemic stroke. S100B protein levels were measured by immunoenzymatic assay. Short-term functional outcome was determined by the NIHSS score on day 1 and the difference in the NIHSS scores between day 1 and day 9 (delta NIHSS). Long-term outcome was assessed by the modified Rankin Scale (MRS) at 3 months after the stroke. At the end of the study, patients were divided into groups based on the NIHSS score on day 9 (0-8 "good" and >8 "poor"), the delta NIHSS ("no improvement" ≤0 and >0 "improvement"), and the MRS ("good" 0-2 and >2 "poor"). Differences in S100B levels between groups were analyzed with the ROC curve to establish the optimal cut-off point for S100B. The odds ratio was calculated to determine the strength of association. Correlations between S100B levels at three time points and these variables were evaluated.

RESULTS

We revealed a statistically significant correlation between S100B levels at each measurement point (<24 h, 24-48 H, 48-72 h) and the NIHSS score on day 9 (R Spearman 0.534, 0.631, and 0.517, respectively) and the MRS score after 3 months (R Spearman 0.620, 0.657, and 0.617, respectively). No statistically significant correlation was found between S100B levels and the delta NIHSS. Analysis of the ROC curve confirmed a high sensitivity and specificity for S100B. The calculated AUC for the NIHSS on day 9 were 90.2%, 95.0%, and 82.2%, respectively, and for the MRS, 83.5%, 83.4%, and 84.0%, respectively. After determining the S100B cut-off, the odds ratio for beneficial effect (NIHSS ≤ 8 at day 9 or MRS 0-2 after 3 months) was determined for each sampling point.

CONCLUSION

S100B is a useful marker for predicting short- and long-term functional outcomes in patients with ischemic stroke.

Neuroprotection during Thrombectomy for Acute Ischemic Stroke: A Review of Future Therapies

Stroke is a major cause of death and disability worldwide. Endovascular thrombectomy has been impactful in decreasing mortality. However, many clinical results continue to show suboptimal functional outcomes despite high recanalization rates. This gap in recanalization and symptomatic improvement suggests a need for adjunctive therapies in post-thrombectomy care. With greater insight into ischemia-reperfusion injury, recent preclinical testing of neuroprotective agents has shifted towards preventing oxidative stress through upregulation of antioxidants and downstream effectors, with positive results. Advances in multiple neuroprotective therapies, including uric acid, activated protein C, nerinetide, otaplimastat, imatinib, verapamil, butylphthalide, edaravone, nelonemdaz, ApTOLL, regional hypothermia, remote ischemic conditioning, normobaric oxygen, and especially nuclear factor erythroid 2-related factor 2, have promising evidence for improving stroke care. Sedation and blood pressure management in endovascular thrombectomy also play crucial roles in improved stroke outcomes. A hand-in-hand approach with both endovascular therapy and neuroprotection may be the key to targeting disability due to stroke.

Stroke classification and treatment support system artificial intelligence for usefulness of stroke diagnosis

Background and aims

It is important to diagnose cerebral infarction at an early stage and select an appropriate treatment method. The number of stroke-trained physicians is unevenly distributed; thus, a shortage of specialists is a major problem in some regions. In this retrospective design study, we tested whether an artificial intelligence (AI) we built using computer-aided detection/diagnosis may help medical physicians to classify stroke for the appropriate treatment.

Methods

To build the Stroke Classification and Treatment Support System AI, the clinical data of 231 hospitalized patients with ischemic stroke from January 2016 to December 2017 were used for training the AI. To verify the diagnostic accuracy, 151 patients who were admitted for stroke between January 2018 and December 2018 were also enrolled.

Results

By utilizing multimodal data, such as DWI and ADC map images, as well as patient examination data, we were able to construct an AI that can explain the analysis results with a small amount of training data. Furthermore, the AI was able to classify with high accuracy (Cohort 1, evaluation data 88.7%; Cohort 2, validation data 86.1%).

Conclusion

In recent years, the treatment options for cerebral infarction have increased in number and complexity, making it even more important to provide appropriate treatment according to the initial diagnosis. This system could be used for initial treatment to automatically diagnose and classify strokes in hospitals where stroke-trained physicians are not available and improve the prognosis of cerebral infarction.

Overview of the Association Between the Pathophysiology, Types, and Management of Sickle Cell Disease and Stroke

Sickle cell disease (SCD) is a genetic blood disorder that affects hemoglobin and increases stroke risk, particularly in childhood. This review examines the pathophysiological association between SCD and stroke, the classification of stroke types, risk factors, diagnosis, management, prevention, and prognosis. A comprehensive literature search was conducted via PubMed, Scopus, and Cochrane databases. Relevant studies on SCD and stroke pathophysiology, classification, epidemiology, diagnosis, treatment, and prevention were identified. Sickle cell disease causes red blood cells to become rigid and sickle-shaped, obstructing blood vessels. Recurrent sickling alters cerebral blood flow and damages vessel walls, often leading to ischemic or hemorrhagic strokes (HS). These occur most frequently in childhood, with ischemic strokes (IS) being more common. Key risk factors include a prior transient ischemic attack (TIA), low hemoglobin, and a high leukocyte count. Neuroimaging is essential for diagnosis and determining stroke type. Primary prevention centers on blood transfusions and hydroxyurea for those at high risk. Acute treatment involves promptly restoring blood flow and managing complications. However, significant knowledge gaps remain regarding stroke mechanisms, optimizing screening protocols, and improving long-term outcomes. This review synthesizes current evidence on SCD and stroke to highlight opportunities for further research and standardizing care protocols across institutions. Ultimately, a holistic perspective is critical for mitigating the high risk of debilitating strokes in this vulnerable patient population.

Imaging modality-dependent carotid stenosis severity variations against intravascular ultrasound as a reference: Carotid Artery intravasculaR Ultrasound Study (CARUS)

PURPOSE

Different non-invasive and invasive imaging modalities are used to determine carotid artery stenosis severity that remains a principal parameter in clinical decision-making. We compared stenosis degree obtained with different modalities against vascular imaging gold standard, intravascular ultrasound, IVUS.

METHODS

300 consecutive patients (age 47-83 years, 192 men, 64% asymptomatic) with carotid artery stenosis of " ≥ 50%" referred for potential revascularization received as per study protocol (i) duplex ultrasound (DUS), (ii) computed tomography angiography (CTA), (iii) intraarterial quantitative angiography (iQA) and (iv) and (iv) IVUS. Correlation of measurements with IVUS (r), proportion of those concordant (within 10%) and proportion of under/overestimated were calculated along with recipient-operating-characteristics (ROC).

RESULTS

For IVUS area stenosis (AS) and IVUS minimal lumen area (MLA), there was only a moderate correlation with DUS velocities (peak-systolic, PSV; end-diastolic, EDV; r values of 0.42-0.51, p < 0.001 for all). CTA systematically underestimated both reference area and MLA (80.4% and 92.3% cases) but CTA error was lesser for AS (proportion concordant-57.4%; CTA under/overestimation-12.5%/30.1%). iQA diameter stenosis (DS) was found concordant with IVUS in 41.1% measurements (iQA under/overestimation 7.9%/51.0%). By univariate model, PSV (ROC area-under-the-curve, AUC, 0.77, cutoff 2.6 m/s), EDV (AUC 0.72, cutoff 0.71 m/s) and CTA-DS (AUC 0.83, cutoff 59.6%) were predictors of ≥ 50% DS by IVUS (p < 0.001 for all). Best predictor, however, of ≥ 50% DS by IVUS was stenosis severity evaluation by automated contrast column density measurement on iQA (AUC 0.87, cutoff 68%, p < 0.001). Regarding non-invasive techniques, CTA was the only independent diagnostic modality against IVUS on multivariate model (p = 0.008).

CONCLUSION

IVUS validation shows significant imaging modality-dependent variations in carotid stenosis severity determination.

Brain-Derived Neurotrophic Factor (BDNF) and Translocator Protein (TSPO) as Diagnostic Biomarkers for Acute Ischemic Stroke

Brain-derived neurotrophic factor (BDNF) interacts with tropomyosin-related kinase B (TrkB) to promote neuronal growth, survival, differentiation, neurotransmitter release, and synaptic plasticity. The translocator protein (TSPO) is known to be found in arterial plaques, which are a symptom of atherosclerosis and a contributory cause of ischemic stroke. This study aims to determine the diagnostic accuracy of plasma BDNF and TSPO levels in discriminating new-onset acute ischemic stroke (AIS) patients from individuals without acute ischemic stroke. A total of 90 AIS patients (61% male, with a mean age of 67.7 ± 12.88) were recruited consecutively in a stroke unit, and each patient was paired with two age- and gender-matched controls. The sensitivity, specificity, and area of the curve between high plasma BDNF and TSPO and having AIS was determined using receiver operating characteristic curves. Furthermore, compared to the controls, AIS patients exhibited significantly higher levels of BDNF and TSPO, blood pressure, HbA1c, and white blood cells, as well as higher creatinine levels. The plasma levels of BDNF and TSPO can significantly discriminate AIS patients from healthy individuals (AUC 0.76 and 0.89, respectively). However, combining the two biomarkers provided little improvement in AUC (0.90). It may be possible to use elevated levels of TSPO as a diagnostic biomarker in patients with acute ischemic stroke upon admission.

Magnetic resonance imaging protocols in pediatric stroke

Neuroimaging protocols play an important role in the timely evaluation and treatment of pediatric stroke and its mimics. MRI protocols for stroke in the pediatric population should be guided by the clinical scenario and neurologic examination, with consideration of age, suspected infarct type and underlying risk factors. Acute stroke diagnosis and causes in pediatric age groups can differ significantly from those in adult populations, and delay in stroke diagnosis among children is a common problem. An awareness of pediatric stroke presentations and risk factors among pediatric emergency physicians, neurologists, pediatricians, subspecialists and radiologists is critical to ensuring timely diagnosis. Given special considerations related to unique pediatric stroke risk factors and the need for sedation in some children, expert consensus guidelines for the imaging of suspected pediatric infarct have been proposed. In this article the authors review standard and rapid MRI protocols for the diagnosis of pediatric stroke, as well as the key differences between pediatric and adult stroke imaging.

Post-reperfusion acute MR diffusion in stroke is a potential predictor for clinical outcome in rats

Middle cerebral artery occlusion (MCAO) models show substantial variability in outcome, introducing uncertainties in the evaluation of treatment effects. Early outcome predictors would be essential for prognostic purposes and variability control. We aimed to compare apparent diffusion coefficient (ADC) MRI data obtained during MCAO and shortly after reperfusion for their potentials in acute-phase outcome prediction. Fifty-nine male rats underwent a 45-min MCAO. Outcome was defined in three ways: 21-day survival; 24 h midline-shift and neurological scores. Animals were divided into two groups: rats surviving 21 days after MCAO (survival group, n = 46) and rats dying prematurely (non-survival/NS group, n = 13). At reperfusion, NS group showed considerably larger lesion volume and lower mean ADC of the initial lesion site (p < 0.0001), while during occlusion there were no significant group differences. At reperfusion, each survival animal showed decreased lesion volume and increased mean ADC of the initial lesion site compared to those during occlusion (p < 10^-6), while NS group showed a mixed pattern. At reperfusion, lesion volume and mean ADC of the initial lesion site were significantly associated with 24 h midline-shift and neurological scores. Diffusion MRI performed soon after reperfusion has a great impact in early-phase outcome prediction, and it works better than the measurement during occlusion.

Diagnostic Value of Computed Tomography Angiography in Suspected Acute Ischemic Stroke Patients With Respect to National Institutes of Health Stroke Scale Score

OBJECTIVE

Noncontrast computed tomography (NCCT) plus computed tomography angiography (CTA) is the standard imaging modality for acute stroke. We investigated whether there is an additional diagnostic value of supra-aortic CTA in relation to National Institutes of Health Stroke Scale (NIHSS) and resultant effective radiation dose.

METHODS

In this observational study, 788 patients with suspected acute stroke were included and divided into 3 NIHSS groups: group 1, NIHSS 0-2; group 2, NIHSS 3-5; and group 3, NIHSS ≥ 6.Computed tomography scans were assessed for findings of acute ischemic stroke and vascular pathologies in 3 regions. Final diagnosis was obtained from medical records. Effective radiation dose was calculated based on the dose-length product.

RESULTS

Seven hundred forty-one patients were included. Group 1 had 484 patients, group 2 had 127 patients, and group 3 had 130 patients. Computed tomography diagnosis of acute ischemic stroke was made in 76 patients. In 37 patients, a diagnosis of acute stroke was made based on pathologic CTA findings in case of an unremarkable NCCT. Stroke occurrence was the lowest in groups 1 and 2, with 3.6% and 6.3%, respectively, compared with 12.7% in group 3. If both NCCT and CTA were positive, the patient was discharged with a stroke diagnosis. Male sex had the highest effect on the final stroke diagnosis. The mean effective radiation dose was 2.6 mSv.

CONCLUSIONS

In female patients with NIHSS 0-2, additional CTA rarely contains relevant additional findings decisive for treatment decisions or overall patient outcomes; therefore, CTA in this patient group might yield less impactful findings, and the applied radiation dose could be lowered by approximately 35%.

Update on imaging in Code Stroke

"Code Stroke" is a multidisciplinary procedure designed to detect acute ischemic strokes and transfer patients for early reperfusion. Selecting these patients requires multimodal imaging with either CT or MRI. 1) Conventional studies without contrast material are obligatory to detect bleeding. Applying the ASPECTS scale, these studies can also identify and quantify areas of early infarction. 2) In candidates for mechanical thrombectomy, angiographic studies are necessary to identify stenoses and obstructions and to evaluate the collateral circulation. 3) Patients with known onset between 6 and 24h or with unknown onset require perfusion studies to distinguish between infracted tissue and recoverable ischemic tissue. Semi-automatic software facilitates diagnosis, but radiologists must interpret its output.

An Overview of Telehealth in the Management of Cardiovascular Disease: A Scientific Statement From the American Heart Association

Telehealth enables the remote delivery of health care through telecommunication technologies and has substantially affected the evolving medical landscape. The COVID-19 pandemic accelerated the utilization of telehealth as health care professionals were forced to limit face-to-face in-person visits. It has been shown that information delivery, diagnosis, disease monitoring, and follow-up care can be conducted remotely, resulting in considerable changes specific to cardiovascular disease management. Despite increasing telehealth utilization, several factors such as technological infrastructure, reimbursement, and limited patient digital literacy can hinder the adoption of remote care. This scientific statement reviews definitions pertinent to telehealth discussions, summarizes the effect of telehealth utilization on cardiovascular and peripheral vascular disease care, and identifies obstacles to the adoption of telehealth that need to be addressed to improve health care accessibility and equity.

Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study

OBJECTIVE

This study aimed to develop a deep learning (DL) model to improve the diagnostic performance of EIC and ASPECTS in acute ischemic stroke (AIS).

METHODS

Acute ischemic stroke patients were retrospectively enrolled from 5 hospitals. We proposed a deep learning model to simultaneously segment the infarct and estimate ASPECTS automatically using baseline CT. The model performance of segmentation and ASPECTS scoring was evaluated using dice similarity coefficient (DSC) and ROC, respectively. Four raters participated in the multi-reader and multicenter (MRMC) experiment to fulfill the region-based ASPECTS reading under the assistance of the model or not. At last, sensitivity, specificity, interpretation time and interrater agreement were used to evaluate the raters' reading performance.

RESULTS

In total, 1391 patients were enrolled for model development and 85 patients for external validation with onset to CT scanning time of 176.4 ± 93.6 min and NIHSS of 5 (IQR 2-10). The model achieved a DSC of 0.600 and 0.762 and an AUC of 0.876 (CI 0.846-0.907) and 0.729 (CI 0.679-0.779), in the internal and external validation set, respectively. The assistance of the DL model improved the raters' average sensitivities and specificities from 0.254 (CI 0.22-0.26) and 0.896 (CI 0.884-0.907), to 0.333 (CI 0.301-0.345) and 0.915 (CI 0.904-0.926), respectively. The average interpretation time of the raters was reduced from 219.0 to 175.7 s (p = 0.035). Meanwhile, the interrater agreement increased from 0.741 to 0.980.

CONCLUSIONS

With the assistance of our proposed DL model, radiologists got better performance in the detection of AIS lesions on NCCT.

Neck-brain integrated ultrasound as a noninvasive screening tool to identify morphological features of middle cerebral artery disease

BACKGROUND AND AIMS

Endovascular treatment is suitable for middle cerebral artery (MCA) with focal lesion. Therefore, accurate evaluation of the morphological features of MCA disease is critical. Ultrasonography is commonly used to screen for MCA lesions. However, there are few studies on lesion length. Using ultrasonography, we aimed to prospectively evaluate MCA disease with focal stenosis, long stenosis, focal occlusion, and long occlusion.

METHODS

Patients with symptomatic MCA disease scheduled for digital subtraction angiography were enrolled. The ultrasonic parameters recorded included mean flow velocity at MCA (V_MCA) and extracranial internal carotid artery (V_ICA), bilateral V_MCA ratio, bilateral V_ICA ratio, and MCA flow continuity.

RESULTS

A total of 278 MCAs were included. Compared to normal vessels, the bilateral V_MCA ratio increased in the focal stenosis group and decreased in the long lesion and focal occlusion groups (all p < 0.05); the V_ICA and bilateral V_ICA ratio decreased in the long lesion group (all p < 0.01), and there was no significant difference in the focal lesion group (all p > 0.05). The optimal cut-offs were bilateral V_MCA ratio <0.80 to predict long lesions and focal occlusions (sensitivity: 0.898, specificity: 0.975), and bilateral V_ICA ratio <0.84 to predict long lesions (sensitivity: 0.704, specificity: 0.879). The sensitivity and specificity to predict long occlusions were 96.7% and 94.8%, respectively, in the absence of MCA flow continuity.

CONCLUSIONS

Neck-brain integrated ultrasound is an appropriate screening method for identifying MCA lesions with different morphologies. Endovascular treatment might not be recommended when bilateral V_ICA ratio <0.84 in patients with MCA lesions.

Quantitative susceptibility mapping (QSM) and R2* of silent cerebral infarcts in sickle cell anemia

Silent cerebral infarction (SCI) is the most commonly reported radiological abnormality in patients with sickle cell anemia (SCA) and is associated with future clinical stroke risk. To date, there have been few histological and quantitative MRI studies of SCI and multiple radiological definitions exist. As a result, the tissue characteristics and composition of SCI remain elusive. The objective of this work was therefore to investigate the composition of segmented SCI lesions using quantitative MRI for R2 * and quantitative magnetic susceptibility mapping (QSM). 211 SCI lesions were segmented from 32 participants with SCA and 6 controls. SCI were segmented according to two definitions (FLAIR+/-T1w-based threshold) using a semi-automated pipeline. Magnetic susceptibility (χ) and R2 * maps were calculated from a multi-echo gradient echo sequence and mean SCI values were compared to an equivalent region of interest in normal appearing white matter (NAWM). SCI χ and R2 * were investigated as a function of SCI definition, patient demographics, anatomical location, and cognition. Compared to NAWM, SCI were significantly less diamagnetic (χ = -0.0067 ppm vs. -0.0153 ppm, p < 0.001) and had significantly lower R2 * (16.7 s-1 vs. 19.2 s-1, p < 0.001). SCI definition had a significant effect on the mean SCI χ and R2 * , with lesions becoming significantly less diamagnetic and having significantly lower R2 * after the application of a more stringent T1w-based threshold. SCI-NAWM R2 * decrease was significantly greater in patients with SCA compared with controls (-2.84 s-1 vs. -0.64 s-1, p < 0.0001). No significant association was observed between mean SCI-NAWM χ or R2* differences and subject age, lesion anatomical location, or cognition. The increased χ and decreased R2 * in SCI relative to NAWM observed in both patients and controls is indicative of lower myelin or increased water content within the segmented lesions. The significant SCI-NAWM R2 * differences observed between SCI in patients with SCA and controls suggests there may be differences in tissue composition relative to NAWM in SCI in the two populations. Quantitative MRI techniques such as QSM and R2 * mapping can be used to enhance our understanding of the pathophysiology and composition of SCI in patients with SCA as well as controls.

Thrombosis and thromboembolism: Brighton collaboration case definition and guidelines for data collection, analysis, and presentation of immunization safety data

This is a Brighton Collaboration case definition of thrombosis and thromboembolism to be used in the evaluation of adverse events following immunization, and for epidemiologic studies for the assessment of background incidence or hypothesis testing. The case definition was developed by a group of experts convened by the Coalition for Epidemic Preparedness Innovations (CEPI) in the context of active development of SARS-CoV-2 vaccines. The case definition format of the Brighton Collaboration was followed to develop a consensus definition and defined levels of certainty, after an exhaustive review of the literature and expert consultation. The document underwent peer review by the Brighton Collaboration Network and by selected expert reviewers prior to submission.

Metabolomics of ischemic stroke: insights into risk prediction and mechanisms

Ischemic stroke (IS) is the most prevalent type of stroke. The early diagnosis and prognosis of IS are crucial for successful therapy and early intervention. Metabolomics, a tool in systems biology based on several innovative technologies, can be used to identify disease biomarkers and unveil underlying pathophysiological processes. Accordingly, in recent years, an increasing number of studies have identified metabolites from cerebral ischemia patients and animal models that could improve the diagnosis of IS and prediction of its outcome. In this paper, metabolomic research is comprehensively reviewed with a focus on describing the metabolic changes and related pathways associated with IS. Most clinical studies use biofluids (e.g., blood or plasma) because their collection is minimally invasive and they are ideal for analyzing changes in metabolites in patients of IS. We review the application of animal models in metabolomic analyses aimed at investigating potential mechanisms of IS and developing novel therapeutic approaches. In addition, this review presents the strengths and limitations of current metabolomic studies on IS, providing a reference for future related studies.

When Can an Emergency CTA Be Dispensed with for TIA Patients?

Background: Transient ischemic attacks (TIAs) and minor strokes are often precursors of a major stroke. Therefore, diagnostic work-up of the TIA is essential to reduce the patient’s risk of further ischemic events. Purpose: With the help of this retrospective study, we aim to determine for which TIA patients a CT angiography (CTA) is not immediately necessary in order to reduce radiation exposure and nephrotoxicity. Material and Methods: Clinical and imaging data from patients who presented as an emergency case with a suspected diagnosis of TIA at a teaching hospital between January 2016 and December 2021 were evaluated. The included 1526 patients were divided into two groups—group 1, with major pathologic vascular findings in the CTA, and group 2, with minor vascular pathologies. Results: Out of 1821 patients with suspected TIA on admission, 1526 met the inclusion criteria. In total, 336 (22%) had major vascular pathologies on CTA, and 1190 (78%) were unremarkable. The majority of patients with major vascular pathologies were male and had a history of arterial hypertension, coronary heart disease, myocardial infarction, ischemic stroke, TIA, atherosclerotic peripheral vascular disease, smoking, antiplatelet medication, had a lower duration of TIA symptoms, and had lower ABCD2 scores. Conclusions: We were able to demonstrate a direct correlation between major CTA pathologies and a history of smoking, age, hyperlipidemia, history of peripheral arterial disease, and a history of stroke and TIA. We were able to prove that the ABCD2 score is even reciprocal to CTA pathology. This means that TIA patients without described risk factors do not immediately require a CTA and could be clarified in the course of treatment with ultrasound or MRI.

Cerebral Collateral Circulation in the Era of Reperfusion Therapies for Acute Ischemic Stroke

Clinical outcomes of patients with acute ischemic stroke depend in part on the extent of their collateral circulation. A good collateral circulation has also been associated with greater benefit of intravenous thrombolysis and endovascular treatment. Treatment decisions for these reperfusion therapies are increasingly guided by a combination of clinical and imaging parameters, particularly in later time windows. Computed tomography and magnetic resonance imaging enable a rapid assessment of both the collateral extent and cerebral perfusion. Yet, the role of the collateral circulation in clinical decision-making is currently limited and may be underappreciated due to the use of rather coarse and rater-dependent grading methods. In this review, we discuss determinants of the collateral circulation in patients with acute ischemic stroke, report on commonly used and emerging neuroimaging techniques for assessing the collateral circulation, and discuss the therapeutic and prognostic implications of the collateral circulation in relation to reperfusion therapies for acute ischemic stroke.

A novel aGAPSS-based nomogram for the prediction of ischemic stroke in patients with antiphospholipid syndrome

Background

Ischemic stroke (IS) is the most common and life-threatening arterial manifestation of antiphospholipid syndrome (APS). It is related to high mortality and severe permanent disability in survivors. Thus, it is essential to identify patients with APS at high risk of IS and adopt individual-level preventive measures. This study was conducted to identify risk factors for IS in patients with APS and to develop a nomogram specifically for IS prediction in these patients by combining the adjusted Global Anti-Phospholipid Syndrome Score (aGAPSS) with additional clinical and laboratory data.

Methods

A total of 478 consecutive patients with APS were enrolled retrospectively. All patients were randomly assigned to the training and validation cohorts. Univariate and multivariate binary logistic analyses were conducted to identify predictors of IS in the training cohort. Then, a nomogram was developed based on these predictors. The predictive performance of the nomogram for the training and validation cohorts was evaluated by determining areas under the receiver operating characteristic curve (AUROC) and creating calibration plots. A decision curve analysis (DCA) was conducted to compare the potential net benefits of the nomogram with those of the aGAPSS.

Results

During a mean follow-up period of 2.7 years, 26.9% (129/478) of the patients were diagnosed with IS. Binary logistic regression analysis revealed that five risk factors were independent clinical predictors of IS: age (P < 0.001), diabetes (P = 0.030), hyperuricemia (P < 0.001), the platelet count (P = 0.001), and the aGAPSS (P = 0.001). These predictors were incorporated into the nomogram, named the aGAPSS-IS. The nomogram showed satisfactory performance in the training [AUROC = 0.853 (95% CI, 0.802–0.896] and validation [AUROC = 0.793 (95% CI, 0.737–0.843)] cohorts. Calibration curves showed good concordance between observed and nomogram-predicted probability in the training and validation cohorts. The DCA confirmed that the aGAPSS-IS provided more net benefits than the aGAPSS in both cohorts.

Conclusion

Age, diabetes, hyperuricemia, the platelet count, and the aGAPSS were risk factors for IS in patients with APS. The aGAPSS-IS may be a good tool for IS risk stratification for patients with APS based on routinely available data.

Artificially-reconstructed brain images with stroke lesions from non-imaging data: modeling in categorized patients based on lesion occurrence and sparsity

Brain imaging is necessary for understanding disease symptoms, including stroke. However, frequent imaging procedures encounter practical limitations. Estimating the brain information (e.g., lesions) without imaging sessions is beneficial for this scenario. Prospective estimating variables are non-imaging data collected from standard tests. Therefore, the current study aims to examine the variable feasibility for modelling lesion locations. Heterogeneous variables were employed in the multivariate logistic regression. Furthermore, patients were categorized (i.e., unsupervised clustering through k-means method) by the charasteristics of lesion occurrence (i.e., ratio between the lesioned and total regions) and sparsity (i.e., density measure of lesion occurrences across regions). Considering those charasteristics in models improved estimation performances. Lesions (116 regions in Automated Anatomical Labeling) were adequately predicted (sensitivity: 80.0-87.5% in median). We confirmed that the usability of models was extendable to different resolution levels in the brain region of interest (e.g., lobes, hemispheres). Patients' charateristics (i.e., occurrence and sparsity) might also be explained by the non-imaging data as well. Advantages of the current approach can be experienced by any patients (i.e., with or without imaging sessions) in any clinical facilities (i.e., with or without imaging instrumentation).

Comparison of the clinical value of transcranial Doppler ultrasound and computed tomography angiography for diagnosing ischemic cerebrovascular disease

Objective

To compare the clinical value of transcranial Doppler (TCD) ultrasound and computed tomography angiography (CTA) for diagnosing ischemic cerebrovascular disease.

Methods

A retrospective clinical study was conducted in 142 patients with ischemic cerebrovascular disease who were initially diagnosed by digital subtraction angiography. Under the single-blind condition, the patients were diagnosed by using TCD ultrasound and CTA independently. The accuracy of these two methods was compared.

Results

The accuracy of diagnosing bilateral middle cerebral artery, bilateral vertebral artery and bilateral internal carotid artery lesions with a TCD examination was significantly higher than that with a CTA examination. There were no significant differences in the accuracy of diagnosing bilateral anterior cerebral artery, bilateral posterior cerebral artery or basilar artery lesions between TCD ultrasound and CTA. The accuracy of diagnosing all cerebral arterial ischemic lesions was significantly higher with a TCD examination (87.39%) than with a CTA examination (69.75%). The accuracy of diagnosing all cerebral arteries that cause ischemic encephalopathy (cerebrovascular + cervical blood vessels) was significantly higher with a TCD examination (88.03%) than with a CTA examination (69.01%).

Conclusions

TCD ultrasound has several advantages over CTA. Therefore, TCD ultrasound is better for diagnosing ischemic encephalopathy than CTA.

Development and Validation of a Clinical-Based Signature to Predict the 90-Day Functional Outcome for Spontaneous Intracerebral Hemorrhage

We aimed to develop and validate an objective and easy-to-use model for identifying patients with spontaneous intracerebral hemorrhage (ICH) who have a poor 90-day prognosis. This three-center retrospective study included a large cohort of 1,122 patients with ICH who presented within 6 h of symptom onset [training cohort, n = 835; internal validation cohort, n = 201; external validation cohort (center 2 and 3), n = 86]. We collected the patients’ baseline clinical, radiological, and laboratory data as well as the 90-day functional outcomes. Independent risk factors for prognosis were identified through univariate analysis and multivariate logistic regression analysis. A nomogram was developed to visualize the model results while a calibration curve was used to verify whether the predictive performance was satisfactorily consistent with the ideal curve. Finally, we used decision curves to assess the clinical utility of the model. At 90 days, 714 (63.6%) patients had a poor prognosis. Factors associated with prognosis included age, midline shift, intraventricular hemorrhage (IVH), subarachnoid hemorrhage (SAH), hypodensities, ICH volume, perihematomal edema (PHE) volume, temperature, systolic blood pressure, Glasgow Coma Scale (GCS) score, white blood cell (WBC), neutrophil, and neutrophil-lymphocyte ratio (NLR) (p < 0.05). Moreover, age, ICH volume, and GCS were identified as independent risk factors for prognosis. For identifying patients with poor prognosis, the model showed an area under the receiver operating characteristic curve of 0.874, 0.822, and 0.868 in the training cohort, internal validation, and external validation cohorts, respectively. The calibration curve revealed that the nomogram showed satisfactory calibration in the training and validation cohorts. Decision curve analysis showed the clinical utility of the nomogram. Taken together, the nomogram developed in this study could facilitate the individualized outcome prediction in patients with ICH.

Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability

Background

Computed tomography (CT) plays an essential role in classifying stroke, quantifying penumbra size and supporting stroke-relevant radiomics studies. However, it is difficult to acquire standard, accurate and repeatable images during follow-up. Therefore, we invented an intelligent CT to evaluate stroke during the entire follow-up.

Methods

We deployed a region proposal network (RPN) and V-Net to endow traditional CT with intelligence. Specifically, facial detection was accomplished by identifying adjacent jaw positions through training and testing an RPN on 76,382 human faces using a preinstalled 2-dimensional camera; two regions of interest (ROIs) were segmented by V-Net on another training set with 295 subjects, and the moving distance of scanning couch was calculated based on a pre-generated calibration table. Multiple cohorts including 1,124 patients were used for performance validation under three clinical scenarios.

Results

Cranial Automatic Planbox Imaging Towards AmeLiorating neuroscience (CAPITAL)-CT was invented. RPN model had an error distance of 4.46 ± 0.02 pixels with a success rate of 98.7% in the training set and 100% with 2.23 ± 0.10 pixels in the testing set. V-Net-derived segmentation maintained a clinically tolerable distance error, within 3 mm on average, and all lines presented with a tolerable angle error, within 3° on average in all boundaries. Real-time, accurate, and repeatable automatic scanning was accomplished with and a lower radiation exposure dose (all P < 0.001).

Conclusions

CAPITAL-CT generated standard and reproducible images that could simplify the work of radiologists, which would be of great help in the follow-up of stroke patients and in multifield research in neuroscience.

Serum S100B and NSE Levels Correlate With Infarct Size and Bladder-Bowel Involvement Among Acute Ischemic Stroke Patients

Objectives Stroke is a major global health concern. Due to limited availability of neuroimaging particularly in rural and regional areas in India as well as its limitation, the interest in use of biochemical markers for stroke diagnosis, severity, and prognosis is increasing. Only a handful of studies on stroke biomarkers have been conducted in India. Hence, this study was conducted to investigate the correlation of serum neuron-specific enolase (NSE) and S100 calcium-binding protein B (S100B) levels with stroke severity according to infarct size in acute ischemic stroke patients.

Material and Methods Sixty stroke patients were recruited for the study and were evaluated. Noncontrast computed tomography (CT) scan of the brain was performed for all patients within 48 hours of onset of symptoms. Infarct volume was measured by evaluating dimensions in three planes on CT head. Serum NSE and S100B levels were measured by commercially available immunoassay kits. Continuous data was represented as mean ± standard deviation. Categorical data was expressed in terms of percentages and proportions. Pearson's correlation coefficient was applied to assess correlation between NSE and S100B and infarct size. Infarct size was classified arbitrarily into three groups according to infarct volume (low, moderate, and large) and analysis of variance was applied for comparing mean S100B and NSE levels in the three groups. To assess the independent predictors of infarct size among stroke cases, multivariate logistic regression analysis was used. Association between serum S100B or NSE levels and clinical features was done by the Mann–Whitney U test.

Results Correlation between serum S100B protein levels and NSE with larger infarct volume was highly significant (r(S100B) = 0.611, p (S100B) < 0.0001; r(NSE) = 0.258, p(NSE) = 0.047). Using multivariate regression analysis, bladder and bowel involvement, prior stroke history, and dyslipidemia among stroke patients correlated with a larger infarct size. Mann–Whitney U test showed both NSE and S100B levels were significantly associated with bladder bowel involvement among stroke cases.

Conclusion There was a positive correlation between serum S100B and NSE levels with infarct size. In addition, bladder-bowel involvement among stroke patients was associated with increased S100B levels. Therefore, levels of protein S100B and NSE may serve as indicator of infarct size and may be predictors of severe clinical presentations of acute ischemic stroke.

Comparative analysis of functional outcome for CT-based versus MRI-based evaluation in acute ischemic stroke prior to mechanical thrombectomy

Background

This study aims to compare functional outcome for Computed tomography (CT)-based versus Magnetic resonance imaging (MRI)-based evaluation in acute ischemic stroke patients prior to Mechanical thrombectomy (MT) in less than 6-h window period in anterior circulation stroke. Participants were patients admitted from September 2, 2018 to September 2, 2020 with an acute ischemic stroke who underwent mechanical thrombectomy treatment. Total duration of MRI stroke protocol and CT scan with Computed tomography angiography (CTA) was 12 min 57 s, and 9 min 23 s, respectively. Follow-up for periodic Modified Rankin Scale (MRS) was performed at 3 months.

Results

Number of patients included in the study were 152 with mean age of 54.6 (range 22–80) years with male predominance (n = 102). Mean GCS on admission was 12 (4–15) and 13(4–14) in CT and MRI group, respectively. National Institute of Health stroke scale (NIHSS) on admission was 17 (4–30) and 16(4–30) and at discharge was 7 (2–23) and 6(2–22) in CT-based group and MRI-based group, respectively. In the MRI group 65.5% had good outcome with mRS (0–2) at 3-month follow-up compared to 35.51% in CT group.

Conclusion

The current standard neuroimaging in acute ischemic stroke patients is CT and CTA brain. Using MRI over CT scan for acute ischemic stroke may improve clinical outcomes for the subgroup of patients who have an unclear diagnosis and who have higher risk of complications with MT. Even though MRI and MRA take longer period to acquire, patient’s clinical outcome was better in MRI group in comparison to CT group and was comparable to that of the five major endovascular trials.

Role of imaging in early diagnosis of acute ischemic stroke: a literature review

Stroke is a serious health condition that is responsible for more than 5% of total deaths. Near 20% of patients experiencing stroke die every year, resulting in the stroke being at the top of the list of preventable causes of death. Once an acute stroke is suspected, a golden hour of less than an hour is available to prevent the undesirable consequences. Since neuroimaging is mandatory in the diagnosis of stroke, the proper use of neuroimaging could help saving time and planning the right treatment for the patient. Some of the available imaging methods help us with rapid results, while others benefit us from a more accurate diagnosis. Hereby, we aim to provide a clinical review of the advantages and disadvantages of different available neuroimaging methods in approaching acute stroke to help clinicians choose the best method according to the settings.

Posterior Communicating Artery Hypoplasia: A Risk Factor for Vertebral Artery Dissection Causing Subarachnoid Hemorrhage

OBJECTIVE

Subarachnoid hemorrhage due to vertebral artery dissection is often fatal; however, its anatomical predictors remain unclear. We conducted a retrospective hospital-based case-control study to evaluate whether variations in the posterior communicating artery are associated with the risk of vertebral artery dissection with subarachnoid hemorrhage.

MATERIALS AND METHODS

We obtained data from patients who underwent computed tomography angiography at our hospital between April 2010 and March 2020. Based on the connection between the anterior and posterior circulation of the arterial circle of Willis, the patients were categorized into a separated group (posterior communicating artery hypoplasia) and a connected group (all others). We evaluated the association between the development of posterior communicating artery and subarachnoid hemorrhage due to vertebral artery dissection using multivariate logistic regression analysis.

RESULTS

Thirty-eight patients had subarachnoid hemorrhage due to vertebral artery dissection and 76 were identified as age- and sex-matched controls. In conditional multivariate logistic regression analysis, the separated group showed a significant association with subarachnoid hemorrhage due to vertebral artery dissection, with an adjusted odds ratio of 2.8 (95% confidence interval, 1.2-6.5; P = 0.021).

CONCLUSIONS

The present study demonstrates that posterior communicating artery hypoplasia may be associated with subarachnoid hemorrhage due to vertebral artery dissection. Our results highlight the importance of anatomical variations in the cerebral artery and provide evidence to help develop preventive measures against strokes.

Virtual monoenergetic dual-energy CT reconstructions at 80 keV are optimal non-contrast CT technique for early stroke detection

BACKGROUND

Virtual monoenergetic (VM) dual-energy computed tomography (DE-CT) enables grey-to-white matter contrast-to-noise ratio optimization, potentially increasing ischaemic brain oedema visibility. The aim of this study was to compare the diagnostic accuracy of VM and standard DE-CT reconstructions for early stroke detection.

METHODS

Consecutive patients with non-contrast DE-CT of the brain scanned within 12 h of stroke symptom onset were prospectively included in the study. Patients with other significant brain pathology were excluded. Two radiologists jointly evaluated standard and VM reconstructions (from 40 to 190 keV at increments of 10 keV) for early stroke signs on a four-point Likert scale: (a) stroke definitely present, (b) stroke probably present, (c) probably no stroke, and (d) definitely no stroke. Follow-up imaging and clinical data served as the standard of reference. Diagnostic accuracy was evaluated by receiver operating characteristic analysis.

RESULTS

Stroke incidence among 184 patients was 76%. In 64 patients follow-up imaging served as the standard of reference: ischemic brain oedema detection was significantly more accurate on VM reconstructions at 80 keV compared with standard DE-CT reconstructions (area under the curve (AUC) = 0.821 vs. AUC = 0.672, p = 0.002). The difference was most prominent within the first 3 h after symptom onset (at 11%, AUC = 0.819 vs. AUC = 0.709, p = 0.17) and in patients with National Institutes of Health Stroke Scale above 16 (at 37.5%, AUC = 1 vs. AUC = 0.625, p = 0.14).

CONCLUSION

VM DE-CT reconstructions at 80 keV appear to be the optimal non-contrast CT technique for diagnosing early ischaemic stroke, particularly within the first 3 h after symptom onset and in severely ill patients.

Differentiating Carotid Free-Floating Thrombus From Atheromatous Plaque Using Intraluminal Filling Defect Length on CTA: A Validation Study

OBJECTIVE

To validate a previously proposed filling defect length threshold of >3.8 mm on CT angiography (CTA) to discriminate between free-floating thrombus (FFT) and plaque of atheroma.

METHODS

This was a prospective multicenter observational study of 100 participants presenting with TIA/stroke symptoms and a carotid intraluminal filling defect on initial CTA. Follow-up CTA was obtained within 1 week and at weeks 2 and 4 if the intraluminal filling defect was unchanged in length. Resolution or decreased length was diagnostic of FFT, whereas its static appearance after 4 weeks was indicative of plaque. Diagnostic accuracy of FFT length was assessed by receiver operating characteristic analysis.

RESULTS

Ninety-five participants (mean [SD] age 68 [13] years, 61 men, 83 participants with FFT, 12 participants with a plaque) were evaluated. The >3.8-mm threshold had a sensitivity of 88% (73 of 83) (95% confidence interval [CI] 78%-94%) and specificity of 83% (10 of 12) (95% CI 51%-97%) (area under the curve 0.91, p < 0.001) for the diagnosis of FFT. The optimal length threshold was >3.64 mm with a sensitivity of 89% (74 of 83) (95% CI 80%-95%) and specificity of 83% (10 of 12) (95% CI 51%-97%). Adjusted logistic regression showed that every 1-mm increase in intraluminal filling defect length is associated with an increase in odds of FFT of 4.6 (95% CI 1.9-11.1, p = 0.01).

CONCLUSION

CTA enables accurate differentiation of FFT vs plaque using craniocaudal length thresholds.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT02405845.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that in patients with TIA/stroke symptoms, the presence of CTA-identified filling defects of lengths >3.8 mm accurately discriminates FFT from atheromatous plaque.

Fusion of Higher Order Spectra and Texture Extraction Methods for Automated Stroke Severity Classification with MRI Images

This paper presents a scientific foundation for automated stroke severity classification. We have constructed and assessed a system which extracts diagnostically relevant information from Magnetic Resonance Imaging (MRI) images. The design was based on 267 images that show the brain from individual subjects after stroke. They were labeled as either Lacunar Syndrome (LACS), Partial Anterior Circulation Syndrome (PACS), or Total Anterior Circulation Stroke (TACS). The labels indicate different physiological processes which manifest themselves in distinct image texture. The processing system was tasked with extracting texture information that could be used to classify a brain MRI image from a stroke survivor into either LACS, PACS, or TACS. We analyzed 6475 features that were obtained with Gray-Level Run Length Matrix (GLRLM), Higher Order Spectra (HOS), as well as a combination of Discrete Wavelet Transform (DWT) and Gray-Level Co-occurrence Matrix (GLCM) methods. The resulting features were ranked based on the p-value extracted with the Analysis Of Variance (ANOVA) algorithm. The ranked features were used to train and test four types of Support Vector Machine (SVM) classification algorithms according to the rules of 10-fold cross-validation. We found that SVM with Radial Basis Function (RBF) kernel achieves: Accuracy (ACC) = 93.62%, Specificity (SPE) = 95.91%, Sensitivity (SEN) = 92.44%, and Dice-score = 0.95. These results indicate that computer aided stroke severity diagnosis support is possible. Such systems might lead to progress in stroke diagnosis by enabling healthcare professionals to improve diagnosis and management of stroke patients with the same resources.

Metabolomics and metabolites in ischemic stroke

Stroke is a major reason for disability and the second highest cause of death in the world. When a patient is admitted to a hospital, it is necessary to identify the type of stroke, and the likelihood for development of a recurrent stroke, vascular dementia, and depression. These factors could be determined using different biomarkers. Metabolomics is a very promising strategy for identification of biomarkers. The advantage of metabolomics, in contrast to other analytical techniques, resides in providing low molecular weight metabolite profiles, rather than individual molecule profiles. Technically, this approach is based on mass spectrometry and nuclear magnetic resonance. Furthermore, variations in metabolite concentrations during brain ischemia could alter the principal neuronal functions. Different markers associated with ischemic stroke in the brain have been identified including those contributing to risk, acute onset, and severity of this pathology. In the brain, experimental studies using the ischemia/reperfusion model (IRI) have shown an impaired energy and amino acid metabolism and confirmed their principal roles. Literature data provide a good basis for identifying markers of ischemic stroke and hemorrhagic stroke and understanding metabolic mechanisms of these diseases. This opens an avenue for the successful use of identified markers along with metabolomics technologies to develop fast and reliable diagnostic tools for ischemic and hemorrhagic stroke.

Multimodality Imaging in Acute Ischemic Stroke

Stroke is the most common cause of mortality and morbidity worldwide. The prognosis of stroke depends upon the area affected and its early treatment. Time is of the essence in the care of stroke patients as it is estimated that approximately 1.9 million neurons, 14 billion synapses, and 12 km myelinated nerve fibers are lost per minute. Therefore, early diagnosis and prompt treatment are necessary. The primary goal of imaging in acute stroke is to diagnose the underlying cause, estimate the area affected, predict response towards thrombolytic therapy and to exclude the conditions mimicking stroke. With advancements in radiology, multiple imaging modalities are available for diagnosis and predicting prognosis. None of them is considered alone to be perfect. In this era of multimodality imaging, the decision of choosing appropriate techniques depends upon purpose and availability. Non-Contrast Computed Tomography is time effective, and helps in excluding other causes, Trans Cranial Doppler is time-effective and cost-effective with wide availability, however, is operator dependent and less sensitive. It holds a great future in sonothrombolysis. Magnetic Resonance Imaging is so far considered to be the most superior one in terms of early diagnosis, planning for interventional treatment and predicting the response of treatment. However, it is limited due to high cost and lack of availability. The current review gives a detailed account of all imaging modalities available for imaging stroke and their associated pros and cons.