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Thrombectomy

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A Machine Learning Approach to First Pass Reperfusion in Mechanical Thrombectomy: Prediction and Feature Analysis.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: Novel machine learning (ML) methods are being investigated across medicine for their predictive capabilities while boasting increased adaptability and generalizability. In our study, we compare logistic regression with machine learning ...

Alberta Stroke Program Early CT Score Calculation Using the Deep Learning-Based Brain Hemisphere Comparison Algorithm.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is a promising tool for the evaluation of stroke expansion to determine suitability for reperfusion therapy. The aim of this study was to validate deep learning-based AS...

Deep Learning-Based Automated Thrombolysis in Cerebral Infarction Scoring: A Timely Proof-of-Principle Study.

Stroke
BACKGROUND AND PURPOSE: Mechanical thrombectomy is an established procedure for treatment of acute ischemic stroke. Mechanical thrombectomy success is commonly assessed by the Thrombolysis in Cerebral Infarction (TICI) score, assigned by visual inspe...

Improved Stroke Care in a Primary Stroke Centre Using AI-Decision Support.

Cerebrovascular diseases extra
BACKGROUND: Patient selection for reperfusion therapies requires significant expertise in neuroimaging. Increasingly, machine learning-based analysis is used for faster and standardized patient selection. However, there is little information on how s...

Spatio-temporal deep learning for automatic detection of intracranial vessel perforation in digital subtraction angiography during endovascular thrombectomy.

Medical image analysis
Intracranial vessel perforation is a peri-procedural complication during endovascular therapy (EVT). Prompt recognition is important as its occurrence is strongly associated with unfavorable treatment outcomes. However, perforations can be hard to de...

Transcarotid access for remote robotic endovascular neurointerventions: a cadaveric proof-of-concept study.

Neurosurgical focus
OBJECTIVE: The purpose of this proof-of-concept study was to demonstrate the setup and feasibility of transcarotid access for remote robotic neurointerventions in a cadaveric model.

Deep learning-based classification of DSA image sequences of patients with acute ischemic stroke.

International journal of computer assisted radiology and surgery
PURPOSE: Recently, a large number of patients with acute ischemic stroke benefited from the use of thrombectomy, a minimally invasive intervention technique for mechanically removing thrombi from the cerebrovasculature. During thrombectomy, 2D digita...

Machine learning based outcome prediction of large vessel occlusion of the anterior circulation prior to thrombectomy in patients with wake-up stroke.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
PURPOSE: Outcome prediction of large vessel occlusion of the anterior circulation in patients with wake-up stroke is important to identify patients that will benefit from thrombectomy. Currently, mismatch concepts that require MRI or CT-Perfusion (CT...

Preliminary experience of oblique occlusion technique in robot-assisted infrahepatic inferior vena cava thrombectomy: step-by-step procedures and short term outcomes.

BMC surgery
BACKGROUND: We aimed to compare the oncological outcomes between the oblique occlusion technique and the traditional technique for robot-assisted radical nephrectomy (RARN) with inferior vena cava (IVC) thrombectomy, and to explore the safety and eff...