Background and Purpose— Automatic segmentation of cerebral infarction on diffusion-weighted imaging (DWI) is typically performed based on a fixed apparent diffusion coefficient (ADC) threshold. Fixed ADC threshold methods may not be accurate because ADC values vary over time after stroke onset. Deep learning has the potential to improve the accuracy, provided that a large set of correctly annotated lesion data is used for training. The purpose of this study was to evaluate deep learning–based methods and compare them with commercial software in terms of lesion volume measurements. Methods— U-net, an encoder-decoder convolutional neural network, was adopted to train segmentation models. Two U-net models were developed: a U-net (DWI+ADC) model, trained on DWI and ADC data, and a U-net (DWI) model, trained on DWI data only. A total of 296 subjects were used for training and 134 for external validation. An expert neurologist manually delineated the stroke lesions on DWI images, which were used as the ground-truth reference. Lesion volume measurements from the U-net methods were compared against the expert’s manual segmentation and Rapid Processing of Perfusion and Diffusion (RAPID; iSchemaView Inc) analysis. Results— In external validation, U-net (DWI+ADC) showed the highest intraclass correlation coefficient with manual segmentation (intraclass correlation coefficient, 1.0; 95% CI, 0.99–1.00) and sufficiently high correlation with the RAPID results (intraclass correlation coefficient, 0.99; 95% CI, 0.98–0.99). U-net (DWI+ADC) and manual segmentation resulted in the smallest 95% Bland-Altman limits of agreement (−5.31 to 4.93 mL) with a mean difference of −0.19 mL. Conclusions— The presented deep learning–based method is fully automatic and shows a high correlation of diffusion lesion volume measurements with manual segmentation and commercial software. The method has the potential to be used in patient selection for endovascular reperfusion therapy in the late time window of acute stroke.
Background and aims: Atrial fibrillation (AF) is a major cause of ischemic stroke; however, detailed clinical data and prognostic factors for stroke patients with AF are lacking in Korea. We aimed to investigate clinical information and factors associated with functional outcomes of stroke patients with AF from the Korean nationwide ATrial fibrillaTion EvaluatioN regisTry in Ischemic strOke patieNts (K-ATTENTION) database.Methods: From January 2013 to December 2015, consecutive clinical information from acute stroke patients with AF or history of AF was collected from 11 centers in Korea. Collected data included demographics, risk factors, pre-stroke medication, stroke severity, stroke subtypes, concomitant cerebral atherosclerosis, brain image findings, recanalization therapy, discharge medication, and functional outcome at 3 months after index stroke.Results: A total of 3,213 stroke patients (mean age, 73.6 ± 9.8 years; female, 48.6%) were included. The mean CHA2DS2-VASc score was 4.9. Among the 1,849 (57.5%) patients who had brain image and functional outcome data, poor outcome (modified Rankin scale > 2) was noted in 53.1% (981/1,849) of patients. After adjusting for age, sex, and variables that had a p < 0.05 in univariate analysis or well-known factors for functional outcome, presence of asymptomatic extracranial cerebral atherosclerosis [odd ratio (OR): 1.96, 95% confidence interval (CI): 1.36–2.82, p = 0.001] and less frequent prior stroke statin intake (OR: 0.69, 95% CI: 0.49–0.98, p = 0.038) were associated with poor functional outcome.Conclusion: Our results suggest that presence of non-relevant extracranial cerebral atherosclerosis may affect poor functional outcome and prior stroke statin therapy may be feasible in Korean stroke patients with AF.
An electromagnetic pulse (EMP) explodes in real-time and causes critical damage within a short period to not only electric devices, but also to national infrastructures. In terms of EMP shielding rooms, metal plate has been used due to its excellent shielding effectiveness (SE). However, it has difficulties in manufacturing, as the fabrication of welded parts of metal plates and the cost of construction are non-economical. The objective of this study is to examine the applicability of the arc thermal metal spraying (ATMS) method as a new EMP shielding method to replace metal plate. The experimental parameters, metal types (Cu, Zn-Al), and coating thickness (100–700 μm) used for the ATMS method were considered. As an experiment, a SE test against an EMP in the range of 103 to 1010 Hz was conducted. Results showed that the ATMS coating with Zn-Al had similar shielding performance in comparison with metal plate. In conclusion, the ATMS method is judged to have a high possibility of actual application as a new EMP shielding material.
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