AIMC Topic: Brain Ischemia

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Platelet-rich emboli are associated with von Willebrand factor levels and have poorer revascularization outcomes.

Journal of neurointerventional surgery
BACKGROUND AND AIMS: Platelets and von Willebrand factor (vWF) are key factors in thrombosis and thus are likely key components of acute ischemic stroke (AIS) emboli. We aimed to characterize platelet and vWF levels in AIS emboli and to assess associ...

Development of a deep learning model to identify hyperdense MCA sign in patients with acute ischemic stroke.

Japanese journal of radiology
PURPOSE: The aim of this study was to develop an interactive deep learning-assisted identification of the hyperdense middle cerebral artery (MCA) sign (HMCAS) on non-contrast computed tomography (CT) among patients with acute ischemic stroke.

Temporally downsampled cerebral CT perfusion image restoration using deep residual learning.

International journal of computer assisted radiology and surgery
PURPOSE: Acute ischemic stroke is one of the most causes of death all over the world. Onset to treatment time is critical in stroke diagnosis and treatment. Considering the time consumption and high price of MR imaging, CT perfusion (CTP) imaging is ...

Automated label-free detection of injured neuron with deep learning by two-photon microscopy.

Journal of biophotonics
Stroke is a significant cause of morbidity and long-term disability globally. Detection of injured neuron is a prerequisite for defining the degree of focal ischemic brain injury, which can be used to guide further therapy. Here, we demonstrate the c...

Data-efficient deep learning of radiological image data for outcome prediction after endovascular treatment of patients with acute ischemic stroke.

Computers in biology and medicine
Treatment selection is becoming increasingly more important in acute ischemic stroke patient care. Clinical variables and radiological image biomarkers (old age, pre-stroke mRS, NIHSS, occlusion location, ASPECTS, among others) have an important role...

Extreme Gradient Boosting Model Has a Better Performance in Predicting the Risk of 90-Day Readmissions in Patients with Ischaemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECT: Ischemic stroke readmission within 90 days of hospital discharge is an important quality of care metric. The readmission rates of ischemic stroke patients are usually higher than those of patients with other chronic diseases. Our aim was to i...

Acute ischemic stroke lesion core segmentation in CT perfusion images using fully convolutional neural networks.

Computers in biology and medicine
The use of Computed Tomography (CT) imaging for patients with stroke symptoms is an essential step for triaging and diagnosis in many hospitals. However, the subtle expression of ischemia in acute CT images has made it hard for automated methods to e...

Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions: a systematic review.

Journal of neurointerventional surgery
BACKGROUND AND PURPOSE: Acute stroke caused by large vessel occlusions (LVOs) requires emergent detection and treatment by endovascular thrombectomy. However, radiologic LVO detection and treatment is subject to variable delays and human expertise, r...

Predicting post-stroke pneumonia using deep neural network approaches.

International journal of medical informatics
BACKGROUND AND PURPOSE: Pneumonia is a common complication after stroke, causing an increased length of hospital stay and death. Therefore, the timely and accurate prediction of post-stroke pneumonia would be highly valuable in clinical practice. Pre...

Machine Learning-Enabled Automated Determination of Acute Ischemic Core From Computed Tomography Angiography.

Stroke
Background and Purpose- The availability of and expertise to interpret advanced neuroimaging recommended in the guideline-based endovascular stroke therapy (EST) evaluation are limited. Here, we develop and validate an automated machine learning-base...