Aneurysmal subarachnoid hemorrhage (aSAH) results in significant mortality and disability. Delayed Cerebral Ischemia (DCI) is the leading cause of poor outcome after aSAH among those who survive the initial hemorrhage event. Significant effort is expended to identify patients at risk of DCI, but existing tests, such as trans-cranial Doppler, suffer from relatively poor sensitivity. Tests to identify patients with DCI prospectively are of high interest.

PURPOSE:To investigate whether selected carotid computed tomography angiography (CTA) quantitative features can predict 10-year atherosclerotic cardiovascular disease (ASCVD) risk scores. METHODS:One hundred seventeen patients with calculated ASCVD risk scores were considered. A semiautomated imaging analysis software was used to segment and quantify plaque features. Eighty patients were randomly selected to build models using 14 imaging variables and the calculated ASCVD risk score as the end point (continuous and binarized). The remaining 37 patients were used as the test set to generate predicted ASCVD scores. The predicted and observed ASCVD risk scores were compared to assess properties of the predictive model. RESULTS:Nine of 14 CTA imaging variables were included in a model that considered the plaque features in a continuous fashion (model 1) and 6 in a model that considered the plaque features dichotomized (model 2). The predicted ASCVD risk scores were 18.87% ± 13.26% and 18.39% ± 11.6%, respectively. There were strong correlations between the observed ASCVD and the predicted ASCVDs, with r = 0.736 for model 1 and r = 0.657 for model 2. The mean biases between observed ASCVD and predicted ASCVDs were -1.954% ± 10.88% and -1.466% ± 12.04%, respectively. CONCLUSIONS:Selected quantitative imaging carotid features extracted from the semiautomated carotid artery analysis can predict the ASCVD risk scores.

Carotid artery plaque is a measure of atherosclerosis and is associated with future risk of atherosclerotic cardiovascular disease (ASCVD), which encompasses coronary, cerebrovascular, and peripheral arterial diseases. With advanced imaging techniques, computerized tomography (CT) and magnetic resonance imaging (MRI) have shown their potential superiority to routine ultrasound to detect features of carotid plaque vulnerability, such as intraplaque hemorrhage (IPH), lipid-rich necrotic core (LRNC), fibrous cap (FC), and calcification. The correlation between imaging features and histological changes of carotid plaques has been investigated. Imaging of carotid features has been used to predict the risk of cardiovascular events. Other techniques such as nuclear imaging and intra-vascular ultrasound (IVUS) have also been proposed to better understand the vulnerable carotid plaque features. In this article, we review the studies of imaging specific carotid plaque components and their correlation with risk scores.

Purpose

The aim of this study was to compare coronary and carotid artery imaging and determine which one shows the strongest association with atherosclerotic cardiovascular disease (ASCVD) score.

Patients and methods

Two separate series patients who underwent either coronary computed tomography angiography (CTA) or carotid CTA were included. We recorded the ASCVD scores and assessed the CTA imaging. Two thirds were used to build predictive models, and the remaining one third generated predicted ASCVD scores. The Bland-Altman analysis analyzed the concordance.

Results

A total of 110 patients were included in each group. There was no significant difference between clinical characteristics. Three imaging variables were included in the carotid model. Two coronary models (presence of calcium or Agatston score) were created. The bias between true and predicted ASCVD scores was 0.37 ± 5.72% on the carotid model, and 2.07 ± 7.18% and 2.47 ± 7.82% on coronary artery models, respectively.

Conclusions

Both carotid and coronary artery imaging features can predict ASCVD score. The carotid artery was more associated to the ASCVD score than the coronary artery.

Objective

The aim of this study was to characterize the relationship between computed tomography angiography imaging characteristics of coronary artery and atherosclerotic cardiovascular disease (ASCVD) score.

Methods

We retrospectively identified all patients who underwent a coronary computed tomography angiography at our institution from December 2013 to July 2016, then we calculated the 10-year ASCVD score. We characterized the relationship between coronary artery imaging findings and ASCVD risk score.

Results

One hundred fifty-one patients met our inclusion criteria. Patients with a 10-year ASCVD score of 7.5% or greater had significantly more arterial segments showing stenosis (46.4%, P = 0.008) and significantly higher maximal plaque thickness (1.25 vs 0.53, P = 0.001). However, among 56 patients with a 10-year ASCVD score of 7.5% or greater, 30 (53.6%) had no arterial stenosis. Furthermore, among the patients with a 10-year ASCVD score of less than 7.5%, 24 (25.3%) had some arterial stenosis.

Conclusions

There is some concordance but not a perfect overlap between 10-year ASCVD risk scores and coronary artery imaging findings.

Background

To assess the differences across continental regions in terms of stroke imaging obtained for making acute revascularization therapy decisions, and to identify obstacles to participating in randomized trials involving multimodal imaging.

Methods

STroke Imaging Repository (STIR) and Virtual International Stroke Trials Archive (VISTA)-Imaging circulated an online survey through its website, through the websites of national professional societies from multiple countries as well as through email distribution lists from STIR and the above mentioned societies.

Results

We received responses from 223 centers (2 from Africa, 38 from Asia, 10 from Australia, 101 from Europe, 4 from Middle East, 55 from North America, 13 from South America). In combination, the sites surveyed administered acute revascularization therapy to a total of 25,326 acute stroke patients in 2012. Seventy-three percent of these patients received intravenous (i.v.) tissue plasminogen activator (tPA), and 27%, endovascular therapy. Vascular imaging was routinely obtained in 79% (152/193) of sites for endovascular therapy decisions, and also as part of standard IV tPA treatment decisions at 46% (92/198) of sites. Modality, availability and use of acute vascular and perfusion imaging before revascularization varied substantially between geographical areas. The main obstacles to participate in randomized trials involving multimodal imaging included: mainly insufficient research support and staff (50%, 79/158) and infrequent use of multimodal imaging (27%, 43/158) .

Conclusion

There were significant variations among sites and geographical areas in terms of stroke imaging work-up used tomake decisions both for intravenous and endovascular revascularization. Clinical trials using advanced imaging as a selection tool for acute revascularization therapy should address the need for additional resources and technical support, and take into consideration the lack of routine use of such techniques in trial planning.

Background and purpose

Although arteriopathies are the most common cause of childhood arterial ischemic stroke, and the strongest predictor of recurrent stroke, they are difficult to diagnose. We studied the role of clinical data and follow-up imaging in diagnosing cerebral and cervical arteriopathy in children with arterial ischemic stroke.

Methods

Vascular effects of infection in pediatric stroke, an international prospective study, enrolled 355 cases of arterial ischemic stroke (age, 29 days to 18 years) at 39 centers. A neuroradiologist and stroke neurologist independently reviewed vascular imaging of the brain (mandatory for inclusion) and neck to establish a diagnosis of arteriopathy (definite, possible, or absent) in 3 steps: (1) baseline imaging alone; (2) plus clinical data; (3) plus follow-up imaging. A 4-person committee, including a second neuroradiologist and stroke neurologist, adjudicated disagreements. Using the final diagnosis as the gold standard, we calculated the sensitivity and specificity of each step.

Results

Cases were aged median 7.6 years (interquartile range, 2.8-14 years); 56% boys. The majority (52%) was previously healthy; 41% had follow-up vascular imaging. Only 56 (16%) required adjudication. The gold standard diagnosis was definite arteriopathy in 127 (36%), possible in 34 (9.6%), and absent in 194 (55%). Sensitivity was 79% at step 1, 90% at step 2, and 94% at step 3; specificity was high throughout (99%, 100%, and 100%), as was agreement between reviewers (κ=0.77, 0.81, and 0.78).

Conclusions

Clinical data and follow-up imaging help, yet uncertainty in the diagnosis of childhood arteriopathy remains. This presents a challenge to better understanding the mechanisms underlying these arteriopathies and designing strategies for prevention of childhood arterial ischemic stroke.

Background and purpose

To assess whether initial imaging characteristics independently predict 1-year neurological outcomes in childhood arterial ischemic stroke patients.

Methods

We used prospectively collected demographic and clinical data, imaging data, and 1-year outcomes from the VIPS study (Vascular Effects of Infection in Pediatric Stroke). In 288 patients with first-time stroke, we measured infarct volume and location on the acute magnetic resonance imaging studies and hemorrhagic transformation on brain imaging studies during the acute presentation. Neurological outcome was assessed with the Pediatric Stroke Outcome Measure. We used univariate and multivariable ordinal logistic regression models to test the association between imaging characteristics and outcome.

Results

Univariate analysis demonstrated that infarcts involving uncinate fasciculus, angular gyrus, insular cortex, or that extended from cortex to the subcortical nuclei were significantly associated with poorer outcomes with odds ratios ranging from 1.95 to 3.95. All locations except the insular cortex remained significant predictors of poor outcome on multivariable analysis. When infarct volume was added to the model, the locations did not remain significant. Larger infarct volumes and younger age at stroke onset were significantly associated with poorer outcome, but the strength of the relationships was weak. Hemorrhagic transformation did not predict outcome.

Conclusions

In the largest pediatric arterial ischemic stroke cohort collected to date, we showed that larger infarct volume and younger age at stroke were associated with poorer outcomes. We made the novel observation that the strength of these associations was modest and limits the ability to use these characteristics to predict outcome in children. Infarcts affecting specific locations were significantly associated with poorer outcomes in univariate and multivariable analyses but lost significance when adjusted for infarct volume. Our findings suggest that infarcts that disrupt critical networks have a disproportionate impact upon outcome after childhood arterial ischemic stroke.