CT angiography and CT perfusion improve prediction of infarct volume in patients with anterior circulation stroke

Introduction: We investigated whether baseline CT angiography (CTA) and CT perfusion (CTP) in acute ischemic stroke could improve prediction of infarct presence and infarct volume on follow-up imaging. Methods: We analyzed 906 patients with suspected anterior circulation stroke from the prospective multicenter Dutch acute stroke study (DUST). All patients underwent baseline non-contrast CT, CTA, and CTP and follow-up non-contrast CT/MRI after 3 days. Multivariable regression models were developed including patient characteristics and non-contrast CT, and subsequently, CTA and CTP measures were added. The increase in area under the curve (AUC) and R2 was assessed to determine the additional value of CTA and CTP. Results: At follow-up, 612 patients (67.5 %) had a detectable infarct on CT/MRI; median infarct volume was 14.8 mL (interquartile range (IQR) 2.8–69.6). Regarding infarct presence, the AUC of 0.82 (95 % confidence interval (CI) 0.79–0.85) for patient characteristics and non-contrast CT was improved with addition of CTA measures (AUC 0.85 (95 % CI 0.82–0.87); p < 0.001) and was even higher after addition of CTP measures (AUC 0.89 (95 % CI 0.87–0.91); p < 0.001) and combined CTA/CTP measures (AUC 0.89 (95 % CI 0.87–0.91); p < 0.001). For infarct volume, adding combined CTA/CTP measures (R2 = 0.58) was superior to patient characteristics and non-contrast CT alone (R2 = 0.44) and to addition of CTA alone (R2 = 0.55) or CTP alone (R2 = 0.54; all p < 0.001). Conclusion: In the acute stage, CTA and CTP have additional value over patient characteristics and non-contrast CT for predicting infarct presence and infarct volume on follow-up imaging. These findings could be applied for patient selection in future trials on ischemic stroke treatment

No relation between body temperature and arterial recanalization at three days in patients with acute ischaemic stroke

Background: Recanalization of an occluded intracranial artery is influenced by temperature-dependent enzymes, including alteplase. We assessed the relation between body temperature on admission and recanalization. Methods: We included 278 patients with acute ischaemic stroke within nine hours after symptom onset, who had an intracranial arterial occlusion on admission CT angiography, in 13 participating centres. We calculated the relation per every 0.1°Celsius increase in admission body temperature and recanalization at three days. Results: Recanalization occurred in 80% of occluded arteries. There was no relation between body temperature and recanalization at three days after adjustments for age, NIHSS score on admission and treatment with alteplase (adjusted odds ratio per 0.1°Celsius, 0.99; 95% confidence interval, 0.94-1.05; p = 0.70). Results for patients treated or not treated with alteplase were essentially the same. Conclusions: Our findings suggest that in patients with acute ischaemic stroke there is no relation between body temperature on admission and recanalization of an occluded intracranial artery three days later, irrespective of treatment with alteplase

Temporal profile of body temperature in acute ischemic stroke: Relation to infarct size and outcome

Background: High body temperatures after ischemic stroke have been associated with larger infarct size, but the temporal profile of this relation is unknown. We assess the relation between temporal profile of body temperature and infarct size and functional outcome in patients with acute ischemic stroke. Methods: In 419 patients with acute ischemic stroke we assessed the relation between body temperature on admission and during the first 3 days with both infarct size and functional outcome. Infarct size was measured in milliliters on CT or MRI after 3 days. Poor functional outcome was defined as a modified Rankin Scale score ≥3 at 3 months. Results: Body temperature on admission was not associated with infarct size or poor outcome in adjusted analyses. By contrast, each additional 1.0 °C in body temperature on day 1 was associated with 0.31 ml larger infarct size (95% confidence interval (CI) 0.04-0.59), on day 2 with 1.13 ml larger infarct size(95% CI, 0.83-1.43), and on day 3 with 0.80 ml larger infarct size (95% CI, 0.48-1.12), in adjusted linear regression analyses. Higher peak body temperatures on days two and three were also associated with poor outcome (adjusted relative risks per additional 1.0 °C in body temperature, 1.52 (95% CI, 1.17-1.99) and 1.47 (95% CI, 1.22-1.77), respectively). Conclusions: Higher peak body temperatures during the first days after ischemic stroke, rather than on admission, are associated with larger infarct size and poor functional outcome. This suggests that prevention of high temperatures may improve outcome if continued for at least 3 days

Prediction of outcome in patients with suspected acute ischaemic stroke with CT perfusion and CT angiography: The Dutch acute stroke trial (DUST) study protocol

Background: Prediction of clinical outcome in the acute stage of ischaemic stroke can be difficult when based on patient characteristics, clinical findings and on non-contrast CT. CT perfusion and CT angiography may provide additional prognostic information and guide treatment in the early stage. We present the study protocol of the Dutch acute Stroke Trial (DUST). The DUST aims to assess the prognostic value of CT perfusion and CT angiography in predicting stroke outcome, in addition to patient characteristics and non-contrast CT. For this purpose, individualised prediction models for clinical outcome after stroke based on the best predictors from patient characteristics and CT imaging will be developed and validated.Methods/design: The DUST is a prospective multi-centre cohort study in 1500 patients with suspected acute ischaemic stroke. All patients undergo non-contrast CT, CT perfusion and CT angiography within 9 hours after onset of the neurological deficits, and, if possible, follow-up imaging after 3 days. The primary outcome is a dichotomised score on the modified Rankin Scale, assessed at 90 days. A score of 0-2 represents good outcome, and a score of 3-6 represents poor outcome. Three logistic regression models will be developed, including patient characteristics and non-contrast CT (model A), with addition of CT angiography (model B), and CT perfusion parameters (model C). Model derivation will be performed in 60% of the study population, and model validation in the remaining 40% of the patients. Additional prognostic value of the models will be determined with the area under the curve (AUC) from the receiver operating characteristic (ROC) curve, calibration plots, assessment of goodness-of-fit, and likelihood ratio tests.Discussion: This study will provide insight in the added prognosti

Predicting Poor Outcome Before Endovascular Treatment in Patients With Acute Ischemic Stroke

Background: Although endovascular treatment (EVT) has greatly improved outcomes in acute ischemic stroke, still one third of patients die or remain severely disabled after stroke. If we could select patients with poor clinical outcome despite EVT, we could prevent futile treatment, avoid treatment complications, and further improve stroke care. We aimed to determine the accuracy of poor functional outcome prediction, defined as 90-day modified Rankin Scale (mRS) score ≥5, despite EVT treatment. Methods: We included 1,526 patients from the MR CLEAN Registry, a prospective, observational, multicenter registry of ischemic stroke patients treated with EVT. We developed machine learning prediction models using all variables available at baseline before treatment. We optimized the models for both maximizing the area under the curve (AUC), reducing the number of false positives. Results: From 1,526 patients included, 480 (31%) of patients showed poor outcome. The highest AUC was 0.81 for random forest. The highest area under the precision recall curve was 0.69 for the support vector machine. The highest achieved specificity was 95% with a sensitivity of 34% for neural networks, indicating that all models contained false positives in their predictions. From 921 mRS 0–4 patients, 27–61 (3–6%) were incorrectly classified as poor outcome. From 480 poor outcome patients in the registry, 99–163 (21–34%) were correctly identified by the models. Conclusions: All prediction models showed a high AUC. The best-performing models correctly identified 34% of the poor outcome patients at a cost of misclassifying 4% of non-poor outcome patients. Further studies are necessary to determine whether these accuracies are reproducible before implementation in clinical practice

Diagnostic yield and accuracy of CT angiography, MR angiography, and digital subtraction angiography for detection of macrovascular causes of intracerebral haemorrhage: Prospective, multicentre cohort study

Study question What are the diagnostic yield and accuracy of early computed tomography (CT) angiography followed by magnetic resonance imaging/angiography (MRI/MRA) and digital subtraction angiography (DSA) in patients with non-traumatic intracerebral haemorrhage? Methods This prospective diagnostic study enrolled 298 adults (18-70 years) treated in 22 hospitals in the Netherlands over six years. CT angiography was performed within seven days of haemorrhage. If the result was negative, MRI/MRA was performed four to eight weeks later. DSA was performed when the CT angiography or MRI/MRA results were inconclusive or negative. The main outcome was a macrovascular cause, including arteriovenous malformation, aneurysm, dural arteriovenous fistula, and cavernoma. Three blinded neuroradiologists independently evaluated the images for macrovascular causes of haemorrhage. The reference standard was the best available evidence from all findings during one year's follow-up. Study answer and limitations A macrovascular cause was identified in 69 patients (23%). 291 patients (98%) underwent CT angiography; 214 with a negative result underwent additional MRI/MRA and 97 with a negative result for both CT angiography and MRI/MRA underwent DSA. Early CT angiography detected 51 macrovascular causes (yield 17%, 95% confidence interval 13% to 22%). CT angiography with MRI/MRA identified two additional macrovascular causes (18%, 14% to 23%) and these modalities combined with DSA another 15 (23%, 18% to 28%). This last extensive strategy failed to detect a cavernoma, which was identified on MRI during follow-up (reference strategy). The positive predictive value of CT angiography was 72% (60% to 82%), of additional MRI/MRA was 35% (14% to 62%), and of additional DSA was 100% (75% to 100%). None of the patients experienced complications with CT angiography or MRI/MRA; 0.6% of patients who underwent DSA experienced p

Automated entire thrombus density measurements for robust and comprehensive thrombus characterization in patients with acute ischemic stroke

Background and Purpose: In acute ischemic stroke (AIS) management, CT-based thrombus density has been associated with treatment success. However, currently used thrombus measurements are prone to inter-observer variability and oversimplify the heterogeneous thrombus composition. Our aim was first to introduce an automated method to assess the entire thrombus density and then to compare the measured entire thrombus density with respect to current standard manual measurements. Materials and Method: In 135 AIS patients, the density distribution of the entire thrombus was determined. Density distributions were described usingmedians, interquartile ranges (IQR), kurtosis, and skewedness. Differences between themedian of entire thrombusmeasurements and commonly applied manualmeasurements using 3 regions of interest were determined using linear regression. Results: Density distributions varied considerably with medians ranging from 20.0 to 62.8 HU and IQRs ranging from 9.3 to 55.8 HU. The average median of the thrombus density distributions (43.5 ± 10.2 HU) was lower than the manual assessment (49.6 ± 8.0 HU) (p<0.05). The difference between manual measurements and median density of entire thrombus decreased with increasing density (r = 0.64; p<0.05), revealing relatively higher manual measurements for low density thrombi such that manual density measurement tend overestimates the real thrombus density. Conclusions: Automatic measurements of the full thrombus expose a wide variety of thrombi density distribution, which is not grasped with currently used manual measurement. Furthermore, d

Intracranial Cerebrospinal Fluid Volume as a Predictor of Malignant Middle Cerebral Artery Infarction

Background and Purpose— Predicting malignant middle cerebral artery (MCA) infarction can help to identify patients who may benefit from preventive decompressive surgery. We aimed to investigate the association between the ratio of intracranial cerebrospinal fluid (CSF) volume to intracranial volume (ICV) and malignant MCA infarction. Methods— Patients with an occlusion proximal to the M3 segment of the MCA were selected from the DUST (Dutch Acute Stroke Study). Admission imaging included noncontrast computed tomography (CT), CT perfusion, and CT angiography. Patient characteristics and CT findings were collected. The ratio of intracranial CSF volume to ICV (CSF/ICV) was quantified on admission thin-slice noncontrast CT. Malignant MCA infarction was defined as a midline shift of >5 mm on follow-up noncontrast CT, which was performed 3 days after the stroke or in case of clinical deterioration. To test the association between CSF/ICV and malignant MCA infarction, odds ratios and 95% CIs were calculated for 3 multivariable models by using binary logistic regression. Model performances were compared by using the likelihood ratio test. Results— Of the 286 included patients, 35 (12%) developed malignant MCA infarction. CSF/ICV was independently associated with malignant MCA infarction in 3 multivariable models: (1) with age and admission National Institutes of Health Stroke Scale (odds ratio, 3.3; 95% CI, 1.1–11.1), (2) with admission National Institutes of Health Stroke Scale and poor collateral score (odds ratio, 7.0; 95% CI, 2.6–21.3), and (3) with terminal internal carotid artery or proximal M1 occlusion and poor collateral score (odds ratio, 7.7; 95% CI, 2.8–23.9). The performance of model 1 (areas under the receiver operating characteristic curves, 0.795 versus 0.824; P=0.033), model 2 (areas under the receiver operating characteristic curves, 0.813 versus 0.850; P<0.001), and model 3 (areas under the receiver operating characteristic curves, 0.811 versus 0.856; P<0.001) improved significantly after adding CSF/ICV. Conclusions— The CSF/ICV ratio is associated with malignant MCA infarction and has added value to clinical and imaging prediction models in limited numbers of patients

Een cellulair automata model voor voetgangersstromen in stations

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