Initial Noncontrast Computed Tomography Research Articles

Cerebrospinal fluid volume as an early radiological factor for clinical course prediction after aneurysmal subarachnoid hemorrhage. A pilot study

BackgroundThe pathological mechanisms following aneurysmal subarachnoid hemorrhage (SAH) are poorly understood. Limited clinical evidence exists on the association between cerebrospinal fluid (CSF) volume and the risk of delayed cerebral ischemia (DCI) or cerebral vasospasm (CV). In this study, we raised the hypothesis that the amount of CSF or its ratio to hemorrhage blood volume, as determined from non-contrast Computed Tomography (NCCT) images taken on admission, could be a significant predictor for CV and DCI. MethodsThe pilot study included a retrospective analysis of NCCT scans of 49 SAH patients taken shortly after an aneurysm rupture (33 males, 16 females, mean age 56.4 ± 15 years). The SynthStrip and Slicer3D software tools were used to extract radiological factors – CSF, brain, and hemorrhage volumes from the NCCT images. The “pure” CSF volume (VCSF) was estimated in the range of [−15, 15] Hounsfield units (HU). ResultsVCSF was negatively associated with the risk of CV occurrence (p = 0.0049) and DCI (p = 0.0069), but was not associated with patients’ outcomes. The hemorrhage volume (VSAH) was positively associated with an unfavorable outcome (p = 0.0032) but was not associated with CV/DCI. The ratio VSAH/VCSF was positively associated with, both, DCI (p = 0.031) and unfavorable outcome (p = 0.002). The CSF volume normalized by the brain volume showed the highest characteristics for DCI prediction (AUC = 0.791, sensitivity = 0.80, specificity = 0.812) and CV prediction (AUC = 0.769, sensitivity = 0.812, specificity = 0.70). ConclusionIt was demonstrated that “pure” CSF volume retrieved from the initial NCCT images of SAH patients (including CV, Non-CV, DCI, Non-DCI groups) is a more significant predictor of DCI and CV compared to other routinely used radiological biomarkers. VCSF could be used to predict clinical course as well as to personalize the management of SAH patients. Larger multicenter clinical trials should be performed to test the added value of the proposed methodology.

The prevalence of non-contrast CT imaging abnormalities in reversible cerebral vasoconstriction syndrome: A systematic review and meta-analysis.

Reversible cerebral vasoconstriction syndrome (RCVS) is a syndrome of recurrent thunderclap headaches and reversible vasoconstriction of the cerebral arteries on neuroimaging within 3 months of onset. Initial non-contrast computed tomography (CT) can reveal abnormalities such as ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage (SAH) can be present in patients with RCVS and may delay diagnosis. We conducted a systematic review and meta-analysis in accordance with the PRISMA guidelines. We aimed to estimate the prevalence of imaging abnormalities on initial non-contrast CT head in adult patients with RCVS. We searched electronic databases including MEDLINE, EMBASE, and the Cochrane Register of Clinical Trials from inception to August 2, 2022. Eligible studies included articles reporting the prevalence of non-contrast CT abnormalities on initial neuroimaging in patients with RCVS, aged 18 and older. Case series, observational studies and clinical trials were included. Data was extracted directly from included papers using a standardized data charting form. The search yielded 722 titles with duplicates removed. Twenty studies that included 379 patients with RCVS met inclusion criteria. We classified non-contrast CT abnormalities as either ischemic stroke, ICH, or SAH. We pooled prevalence data using a random effects model with the inverse-variance weighted method. The most common imaging finding was SAH with a pooled prevalence of 24% (95% CI:17%-33%), followed by ICH at 14% (95% CI:8%-22%), and ischemic stroke at 10% (95% CI:7%-14%). The pooled prevalence of any of these imaging abnormalities on initial non-contrast CT was 31% (95% CI:23%-40%). Risk of bias was moderate to very-high-risk for case-series and low-risk for observational studies. Our review demonstrates that one-third of patients with RCVS will have an abnormality on initial non-contrast CT head, including either an ischemic stroke, ICH, or SAH. These findings highlight the diagnostic challenges of RCVS imaging and contribute to our understanding of this disease.

Radiological features of brain hemorrhage through automated segmentation from computed tomography in stroke and traumatic brain injury.

Radiological assessment is necessary to diagnose spontaneous intracerebral hemorrhage (ICH) and traumatic brain injury intracranial hemorrhage (TBI-bleed). Artificial intelligence (AI) deep learning tools provide a means for decision support. This study evaluates the hemorrhage segmentations produced from three-dimensional deep learning AI model that was developed using non-contrast computed tomography (CT) imaging data external to the current study. Non-contrast CT imaging data from 1263 patients were accessed across seven data sources (referred to as sites) in Norway and Sweden. Patients were included based on ICH, TBI-bleed, or mild TBI diagnosis. Initial non-contrast CT images were available for all participants. Hemorrhage location frequency maps were generated. The number of estimated haematoma clusters was correlated with the total haematoma volume. Ground truth expert annotations were available for one ICH site; hence, a comparison was made with the estimated haematoma volumes. Segmentation volume estimates were used in a receiver operator characteristics (ROC) analysis for all samples (i.e., bleed detected) and then specifically for one site with few TBI-bleed cases. The hemorrhage frequency maps showed spatial patterns of estimated lesions consistent with ICH or TBI-bleed presentations. There was a positive correlation between the estimated number of clusters and total haematoma volume for each site (correlation range: 0.45-0.74; each p-value < 0.01) and evidence of ICH between-site differences. Relative to hand-drawn annotations for one ICH site, the VIOLA-AI segmentation mask achieved a median Dice Similarity Coefficient of 0.82 (interquartile range: 0.78 and 0.83), resulting in a small overestimate in the haematoma volume by a median of 0.47 mL (interquartile range: 0.04 and 1.75 mL). The bleed detection ROC analysis for the whole sample gave a high area-under-the-curve (AUC) of 0.92 (with sensitivity and specificity of 83.28% and 95.41%); however, when considering only the mild head injury site, the TBI-bleed detection gave an AUC of 0.70. An open-source segmentation tool was used to visualize hemorrhage locations across multiple data sources and revealed quantitative hemorrhage site differences. The automated total hemorrhage volume estimate correlated with a per-participant hemorrhage cluster count. ROC results were moderate-to-high. The VIOLA-AI tool had promising results and might be useful for various types of intracranial hemorrhage.

Abstract Number ‐ 18: Potential impact in low and middle‐income countries stroke networks of a deep learning triage tool

Introduction Early and accurate identification of large vessel occlusion (LVO) and intracranial hemorrhage (ICH) on initial neuroimaging is essential in a stroke network. A machine learning algorithm (MLA) able to predict LVO or ICH on non‐contrast computed tomography (NCCT) may accelerate workflows.We performed a validation analysis to measure the MLA accuracy among suspected stroke patients transferred to a Comprehensive Stroke Centre (CSC) in Mexico and the possible impact on the workflow in low and middle income countries (LMIC) . Methods From February 2021 to March 2022 consecutive patients with suspected acute stroke who underwent NCCT and computed tomography angiography (CTA) were included. MLA prediction of LVO and ICH was tested against expert physicians readings and clinical follow‐up. We calculated sensitivity, specificity, positive predictive value and negative predictive value. Receiver operating curves were generated for MLA‐LVO, MLA‐ICH and; areas under the curve were calculated. Potential time savings and impact on workflow times were calculated for a scenario in which MLA could analyse initial NCCT at PSC avoiding imaging repetition at CSC. Results 140 consecutive patients admitted from march 2021 to February 2022 were included in the study, final physicians diagnostics were: 22 ICH (15.7%) and 53 LVO (37.8%) MLA detected 22 ICH (15.7%) and 58 LVO (41.4%).The area under the curve for the identification of ICH with MLA was 0.97 (sensitivity: 94%, specificity: 91%, positive predictive value: 83.3%[MR1][JL2], negative predictive value: 100%). The area under the curve for the identification of LVO with MLA was 0.91 (sensitivity: 100%, specificity: 95.8%, positive predictive value: 85.7%, negative predictive value: 96.4%). Implementation of MLA‐LVO in the network could save CTA acquisition times of 40 (IQR 26) minutes by taking patients directly to the angiosuite for endovascular treatment. Conclusions In patients with suspected acute stroke, a MLA can quickly and reliably predict ICH and LVO. Such a tool could accelerate the diagnosis, mitigate the contrast imaging dependency and improve the workflow efficiency in stroke networks in LMIC where access to contrast imaging is often limited.

Quality assurance for non-contrast CT of the abdomen and pelvis during a period of supply chain disruption leading to iodinated contrast shortage in the emergency department setting.

Iodinated contrast media (ICM) shortage crisis due to COVID-19 lockdowns led to a need for alternate imaging protocols consisting of non-contrast computed tomography (CT) for abdominal complaints and related trauma indications in emergency department (ED) settings. This quality assurance study aims to evaluate clinical outcomes of protocol modifications during ICM shortage and identify potential imaging misdiagnosis of acute abdominal complaints and related trauma. The study included 424 ED patients with abdominal pain, falls, or motor vehicle collision (MVC)-related trauma who had non-contrast CT of the abdomen and pelvis in May 2022. We accessed the initial complaint, order indication, non-contrast CT results, any acute or incidental findings, and any follow-up imaging of the same body region with their results. We evaluated their association utilizing Chi-squared tests. We assessed sensitivity, specificity, and positive/negative predictive values using follow-up scan confirmation. Across initial complaint categories, 72.9% of cases were abdominal pain, and 37.3% received positive findings. Only 22.6% of patients had follow-up imaging. Most confirmed original reports were for abdominal pain. We also found three reports of missed findings. There were significant associations between complaint categories and initial non-contrast CT report results (P < 0.001), as well as initial complaint categories and whether the patient received follow-up imaging or not (P < 0.004). No significant associations were found between follow-up imaging results and initial report confirmation. Non-contrast CT had 94% sensitivity and 100% specificity, with positive and negative predictive values 100% and 94%, respectively. Rate of missed acute diagnoses using non-contrast CT for patients presenting to the ED with acute abdominal complaints or related trauma has been low during the recent shortage, but further investigation would be needed to verify and quantify the implications of not routinely giving oral or intravenous contrast in the ED.

The comprehensive comparison of imaging sign from CT angiography and noncontrast CT for predicting intracranial hemorrhage expansion: A comparative study.

Expansion of intracranial hemorrhage (ICH) is an important predictor of poor clinical outcomes. Various imaging markers on non-contrast computed tomography (NCCT) or computed tomographic angiography (CTA) have been reported as predictors of ICH expansion. We aimed to compare the associations between various CT imaging markers and ICH expansion. Patients with spontaneous ICH who underwent initial NCCT, CTA, and subsequent NCCT between January 2016 and December 2019 were retrospectively identified. ICH expansion was defined as a volume increase of > 33% or > 6 mL. We analyzed the presence of imaging markers such as the black hole sign, blend sign, island sign, or swirl sign on initial NCCT or spot sign on CTA. An alternative free-response receiver operating characteristic curve analysis was performed using a 4-point scoring system based on the consensus of the reviewers. The predictive value of each marker was assessed using univariate and multivariate logistic regression analyses. A total of 250 patients, including 60 (24.0%) with ICH expansion, qualified for the analysis. Among the patients with spontaneous ICH, 118 (47.2%) presented with a black hole sign, 52 (20.8%) with a blend sign, 93 (37.2%) with an island sign, 79 (31.6%) with a swirl sign, and 56 (22.4%) with a spot sign. In univariate logistic regression, the initial ICH volume (P = .038), initial intraventricular hemorrhage (IVH) presence (P < .001), swirl sign (P < .001), and spot sign (P < .001) were associated with ICH expansion. Multivariate analysis confirmed that the presence of initial IVH (odds ratio, 4.111; P = .002) and spot sign (odds ratio, 109.5; P < .001) were independent predictors of ICH expansion. Initial ICH volume, IVH, swirl sign, and spot sign are associated with ICH expansion. The presence of spot signs and IVH were independent predictors of ICH expansion.

A non-contrast computed tomography-based radiomics nomogram for the prediction of hematoma expansion in patients with deep ganglionic intracerebral hemorrhage.

Background and purposeHematoma expansion (HE) is a critical event following acute intracerebral hemorrhage (ICH). We aimed to construct a non-contrast computed tomography (NCCT) model combining clinical characteristics, radiological signs, and radiomics features to predict HE in patients with spontaneous ICH and to develop a nomogram to assess the risk of early HE.Materials and methodsWe retrospectively reviewed 388 patients with ICH who underwent initial NCCT within 6 h after onset and follow-up CT within 24 h after initial NCCT, between January 2015 and December 2021. Using the LASSO algorithm or stepwise logistic regression analysis, five models (clinical model, radiological model, clinical-radiological model, radiomics model, and combined model) were developed to predict HE in the training cohort (n = 235) and independently verified in the test cohort (n = 153). The Akaike information criterion (AIC) and the likelihood ratio test (LRT) were used for comparing the goodness of fit of the five models, and the AUC was used to evaluate their ability in discriminating HE. A nomogram was developed based on the model with the best performance.ResultsThe combined model (AIC = 202.599, χ2 = 80.6) was the best fitting model with the lowest AIC and the highest LRT chi-square value compared to the clinical model (AIC = 232.263, χ2 = 46.940), radiological model (AIC = 227.932, χ2 = 51.270), clinical-radiological model (AIC = 212.711, χ2 = 55.490) or radiomics model (AIC = 217.647, χ2 = 57.550). In both cohorts, the nomogram derived from the combined model showed satisfactory discrimination and calibration for predicting HE (AUC = 0.900, sensitivity = 83.87%; AUC = 0.850, sensitivity = 80.10%, respectively).ConclusionThe NCCT-based model combining clinical characteristics, radiological signs, and radiomics features could efficiently discriminate early HE, and the nomogram derived from the combined model, as a non-invasive tool, exhibited satisfactory performance in stratifying HE risks.

Development and validation of a clinical-radiomics nomogram for predicting a poor outcome and 30-day mortality after a spontaneous intracerebral hemorrhage

BackgroundNoncontrast computed tomography (NCCT) is often performed for patients with a suspected spontaneous intracerebral hemorrhage (ICH) at the time of admission. Both clinical and radiomic features on the initial NCCT can predict the outcomes of those with ICH, but satisfactory model performance remains challenging.MethodsA total of 258 acute ICH patients from the Central Hospital of Wuhan (CHW) between January 2018 and December 2020 were retrospectively assigned to training and internal validation cohorts at a ratio of 7:3. An independent external testing cohort of 87 patients from January 2021 to July 2021 from the Fifth Affiliated Hospital of Nanchang University (FAHNU) was also used. Based on the least absolute shrinkage and selection operator (LASSO) algorithm, radiomics (rad)-scores were generated from 9 quantitative features on the initial NCCT images. Three models (radiomics, clinical, and hybrid) were established using stepwise logistic regression analysis. The Akaike information criterion and the likelihood ratio test were used to compare the goodness of fit of the three models. Receiver operating characteristic (ROC) curve analysis was performed and bar charts were constructed to evaluate the discrimination of constructed model for predicting a poor outcome following ICH.ResultsThe three cohorts had similar baseline clinical characteristics, including demographic features and outcomes. In the clinical model, hematoma expansion [2.457 (0.297, 2.633); P=0.014], intracerebral ventricular hemorrhage [2.374 (0.180, 1.882); P=0.018], and location [−2.268 (−2.578, −0.188); P=0.023] were independently associated with a poor clinical outcome. In the hybrid model, location [−2.291 (−2.925, −0.228); P=0.022], and rad-score [5.255 (0.680, 11.460); P<0.001] were independently associated with a poor outcome. The hybrid model achieved satisfactory discriminability, with areas under curve (AUCs) of 0.892 [95% confidence interval (CI): 0.847 to 0.937], 0.893 (95% CI: 0.820 to 0.966), and 0.838 (95% CI: 0.755 to 0.920) in the training, internal validation, and external testing cohorts, respectively. The hybrid model also achieved good discriminability in the prediction of 30-day mortality, with AUCs of 0.840, 0.823, and 0.883 in the training, internal validation, and external testing cohorts, respectively. The rad-score [2.861 (1.940, 4.220); P<0.001] was the predominant risk factor associated with 30-day mortality.ConclusionsRadiomic analysis based on initial NCCT scans showed added value in predicting a poor outcome after ICH. A clinical-radiomics model yielded improved accuracy in predicting a poor outcome and 30-day death following ICH compared with radiomics alone.

Noncontrast Computed Tomography-Based Radiomics Analysis in Discriminating Early Hematoma Expansion after Spontaneous Intracerebral Hemorrhage.

ObjectiveTo determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH).Materials and MethodsWe retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power.ResultsThe AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively. The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively.ConclusionNCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.

Not aString, not aTangle, not an Aneurysm : Emerging Pattern of Large Parenchymal Bleeding in Younger Patients Associated with Abnormal Vessels on Imaging.

PurposeIntracerebral hemorrhage (ICH) accounts for up to 20% of all strokes, and there is a high rate of associated morbidity and mortality. Computed tomography (CT) findings, such as a spot sign have been shown to be an independent predictor of poor outcome. We have recently encountered a succession of ICH patients who presented with a peculiar imaging finding, which we term the spot on a string sign. This is a rare imaging finding, and interestingly, all these patients presented to our institution over the last few weeks.MethodsThis was a single high-volume center series of patients who presented to our institution between 1 April and 21 May 2020. All patients underwent initial non-contrast CT brain and subsequent CT angiography (CTA). We also present laboratory and clinical data. Our primary measure was the presence of the spot on a string sign on the CTA. We also report the clinical course of these patients.ResultsIn this study seven large-volume ICH patients with this imaging sign were identified, with a median age of 48 years (range 30–68 years). All had tested negative for coronavirus disease 19 (COVID-19).ConclusionWe have described an unusual imaging finding in a cohort of younger patients with large-volume ICH, all of whom presented in a 2-month period to a high-volume neurovascular unit. The cause of these ICH presentations and associated imaging findings are unclear, but we encourage other clinicians to be aware of and vigilant for this rare phenomenon, especially in younger patients with such a bleeding pattern.

Noncontrast computed tomography markers of outcome in intracerebral hemorrhage patients

ABSTRACTObjectives: The characterization of markers capable of predicting clinically significant hematoma growth (HG) in patients with intracerebral hemorrhage (ICH) may be useful for the selection of patients for clinical trials. The use of several noncontrast computed tomography (NCCT) markers has been suggested to stratify the risk of HG. The aim of this study was to analyze HG prediction using different NCCT markers in patients with spontaneous ICH.Methods: Single-hospital retrospective study of patients with spontaneous ICH, who underwent initial NCCT <24 hours after symptom onset. Clinical characteristics were collected and two independent observers analyzed hemorrhage characteristics, volumes and 8 NCCT markers. HG was defined as a growth of ≥33% or ≥6mL in follow-up CT and 30-day survival was collected.Results: 328 patients were included. The most frequent NCCT marker was ‘any hypodensity’ (68.0%) and the less frequent was the blend sign (11.6%). HG occurred in 22.1% of patients and the only independent predictors for HG were ‘any hypodensity’ (OR=3.32, 95%CI=1.18–9.34, p=0.023) and the swirl sign (OR=3.98, 95%CI=1.41–11.21, p=0.009). Although all NCCT markers were more frequent in patients who died within 30 days, the only independent predictors were ‘irregular margins’ (OR=4.54, 95%CI=1.63–12.66, p=0.004) and the satellite sign (OR=2.49, 95%CI=1.07–5.75, p=0.034). NCCT markers with greater sensitivity for HG were ‘any hypodensity’ and the swirl sign, although with poor positive predictive values and poor areas under the curve.Conclusion: Even though some NCCT markers are independent predictors of HG and 30-day survival, they have suboptimal diagnostic test performances for such outcomes.Abbreviation: OR: odds ratio; 95%CI: 95% confidence interval

Diagnostic value of swirl sign on noncontrast computed tomography and spot sign on computed tomographic angiography to predict intracranial hemorrhage expansion

ObjectiveIntracranial hemorrhage (ICH) expansion is a predictor of poor clinical outcome. ICH expansion can be predicted with a swirl sign on noncontrast computed tomography (NCCT) and/or a spot sign on computed tomographic angiography (CTA). In this study, we aimed to evaluate the diagnostic value of a swirl sign and a spot sign in identifying hematoma expansion. Patients and methodsPatients with spontaneous ICH between January 2013 and August 2018 who underwent an initial NCCT and CTA, and a subsequent NCCT at a single center were retrospectively identified. Two experienced neuroradiologists reviewed all images for swirl sign and spot sign presence using a 4-point scale for receiver-operative characteristic analysis. ICH expansion was defined as volume growth of >33% or >6 mL. ResultsA total of 227 patients, including 54 with ICH expansion, qualified for analysis. For both observers, the area under the curve (AUC) of spot sign was significantly higher than that of swirl sign (observer 1: 0.748 vs. 0.577, p = .002; observer 2: 0.749 vs. 0.589, p = .004). The sensitivities of ICH expansion in patients with a spot sign was significantly higher than patients with a swirl sign (observer 1: 54.1% vs. 28.0%, p = .002; observer 2: 56.9% vs. 30.3%, p = .002). Patients with a spot sign had the highest risk of ICH expansion (odds ratio: observer 1 = 8.14, observer 2 = 9.30, p < 0.001). ConclusionsA spot sign on CTA was identified and associated with ICH expansion. A swirl sign on NCCT had a relatively low sensitivity and AUC, and will not be able to replace spot sign on CTA.

Abstract TP87: Gaze Deviation on Initial CT as Predictor of Large Vessel Occlusion

Introduction: Treatment of large vessel occlusion (LVO) stroke is traditionally preceded by imaging evaluation of vessels using computed tomographic angiography (CTA). However, CTA may not be feasible due to renal dysfunction or contrast allergy; in smaller hospitals, CTAs may not be easily obtainable. Given this, early LVO signs on initial non-contrast computed tomography (CT) could prove practical, such as the hyperdense vessel sign (HVS). We aimed to investigate the sensitivity of another potential indicator of LVO on CT, gaze deviation, and to compare it to HVS. Methods: We conducted a retrospective analysis of consecutive patients with anterior circulation LVO stroke admitted to a comprehensive stroke center from July 2015 to July 2018, who underwent endovascular therapy (ET). All patients had confirmed LVO on CTA prior to ET. Initial head CTs were reviewed for HVS and gaze deviation by two neurology-trained examiners and compared to official diagnostic radiology reports. Two analyses were performed: detection of HVS and gaze deviation by each examiner, diagnostic radiologist with sensitivity calculation; and interrater agreement for identification of HVS and gaze deviation using a Kappa Coefficient between the two primary examiners and between diagnostic radiologist. Results: A total of 121 patients were included. Sensitivity of HVS by examiner 1 was 46% (56/121) and 2 was 60% (72/121). Sensitivity of HVS by in-house radiology was 36% (42/116) and OSH radiology was 27% (24/90). Sensitivity of gaze deviation by examiner 1 was 65% (79/121) and 2 was 79% (95/121). Inter-rater reliability of HVS for examiners 1 and 2 had substantial agreement (K=0.64), and for in-house and OSH radiology had fair agreement (K=0.27). Inter-rater reliability of gaze deviation for examiners 1 and 2 had substantial agreement (K=0.69). No radiology report noted gaze deviation, despite 2 reports of unrelated ocular findings. Conclusions: Gaze deviation may be a more sensitive and more reliable indicator of LVO on initial non-contrast head CT than the hyperdense vessel sign. This is the largest sample size to examine and directly compare signs of LVO. More research should be invested in this and other indicators of LVO that can assist in the efficient triage and treatment of these severe strokes.

Reliability and Utility of the Alberta Stroke Program Early Computed Tomography Score in Hyperacute Stroke

The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) on non-contrast computed tomography (NCCT) is dependent on the visibility of early ischemic change. The goal of our study was to evaluate whether time from ischemic stroke onset to initial NCCT influences the inter-rater variability and prognostic accuracy of ASPECTS for a 3-month functional outcome. Ischemic stroke patients treated with intravenous tissue plasminogen activator (IV-tPA) from 2007 to 2014 at the Royal Melbourne Hospital were included. ASPECTS were blindly assessed by 2 independent raters with inter-rater agreement determined by weighted kappa. Onset time to computed tomography time was dichotomized at the median (≤100 and >100 minutes). Outcome was assessed using the modified Rankin Scale. Logistic regression and receiver operating characteristic analysis were used to assess the prognostic utility of ASPECTS in the early and later time periods. There were 379 patients included. Inter-rater agreement was significantly lower in the early time period: kappa = .75 (95% confidence interval (CI), .59-.84) ≤ 100 minutes versus .92 (95% CI, .91-.93) > 100 minutes, P < .001. The distributions of absolute inter-rater differences in ASPECTS differed significantly between time epochs (P = .03). The prognostic accuracies of ASPECTS across time epochs were area under the receiver operating characteristic curve ≤ 100 minutes = .57 (95% CI, .50-.64) and >100 minutes = .66 (95% CI, .59-.73), P = .055. This study demonstrated a significantly lower inter-rater agreement and a trend toward reduced prognostic accuracy of ASPECTS in earlier time periods. The use of ASPECTS to select patients for revascularization in early time windows may be unreliable.

Utility of Urgent Computed Tomography Angiography in the Setting of Intraparenchymal Brain Hemorrhage

Patients presenting with an intracerebral hemorrhage (ICH) generally have an initial noncontrast computed tomography (NCCT) of the brain. Computed tomography angiography (CTA) can help identify secondary causes of ICH and detect a "spot sign." We hypothesized that performing an urgent CTA in the setting of a presumed primary ICH has only limited utility and did not alter urgent management. This was a retrospective study of consecutive patients presenting with a primary ICH identified from the Duke University Stroke Registry from 2010 to 2013 who had an ICH detected on an initial NCCT. Patients with hemorrhages related to tumor, hemorrhagic conversion of an ischemic stroke, and known secondary causes were excluded. CTA within the first 10 hours of presentation was considered "urgent." Of 246 patients meeting the inclusion criteria, 53% had an urgent CTA. Those who underwent a CTA were younger (61 ± 1 versus 70 ± 1 years, P < .0001) and more commonly had deep bleeds (50% versus 45%, P = .048). CTA identified 12 aneurysms (10 incidental) and 2 arteriovenous malformations; 87% were normal. Urgent CTA was associated with a change in management in 3 cases (2.2%); each had historic or other findings suggestive of a secondary cause of hemorrhage and none led to urgent treatment changes. In the absence of features suggesting a secondary cause, the results of an urgent CTA did not alter the urgent management of a consecutive series of patients with ICH. CTAs may be safely delayed until after the acute period in these patients.

Should CT Angiography be a Routine Component of Acute Stroke Imaging?

Should CT Angiography be a Routine Component of Acute Stroke Imaging?

A Case of Cerebral Venous Thrombosis in a 77-Year-Old White Man

A Case of Cerebral Venous Thrombosis in a 77-Year-Old White Man

Early Post-Traumatic Seizures in Moderate to Severe Pediatric Traumatic Brain Injury: Rates, Risk Factors, and Clinical Features

We performed a retrospective, observational study at a level I pediatric trauma center of children with moderate-to-severe traumatic brain injury (TBI) from January 2002 to September 2006 to identify clinical and radiographic risk factors for early post-traumatic seizures (EPTS). Two hundred and ninety-nine children ages 0-15 years were evaluated, with 24 excluded because they died before the initial head computed tomography (CT) was obtained (n=20), or because their medical records were missing (n=4). Records were reviewed for accident characteristics, pre-hospital hypoxia or hypotension, initial non-contrast head CT characteristics, seizure occurrence, antiepileptic drug (AED) administration, and outcome. All care was at the discretion of the treating physicians, including the use of AEDs and continuous electroencephalogram (EEG) monitoring in patients receiving neuromuscular blocking agents. The primary outcome was seizure activity during the first 7 days as determined by clinician observation or EEG analysis. Of the 275 patients included in the study, 34 had identified EPTS (12%). Risk factors identified on bivariable analysis included pre-hospital hypoxia, young age, non-accidental trauma (NAT), severe TBI, impact seizure, and subdural hemorrhage, while receiving an AED was protective. Independent risk factors identified by multivariable analysis were age <2 years (OR 3.0 [95% CI 1.0,8.6]), Glasgow Coma Scale (GCS) score ≤8 (OR 8.7 [95% CI 1.1,67.6]), and NAT as a mechanism of injury (OR 3.4 [95% CI 1.0,11.3]). AED treatment was protective against EPTS (OR 0.2 [95% CI 0.07,0.5]). Twenty-three (68%) patients developed EPTS within the first 12 h post-injury. This early peak in EPTS activity and demonstrated protective effect of AED administration in this cohort suggests that to evaluate the maximal potential benefit among patients at increased risk for EPTS, future research should be randomized and prospective, and should intervene during pre-trauma center care with initiation of continuous EEG monitoring as soon as possible.