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Total 112 results found since Jan 2013.

The Great Contrast Shortage of 2022 —Lessons learnt in Australia
ConclusionOur findings demonstrate that the IBCM shortage crisis had a very significant impact on the delivery of healthcare. While V/Q scans could (partially) substitute for CTPA studies in suspected pulmonary emboli, there appeared to be no valid alternative for CTNA studies in stroke calls. The unexpected and critical shortage of IBCM forced healthcare professionals to conserve resources, prioritise indications, triage patients based on risk, explore alternate imaging strategies and prepare for similar events recurring in the future.
Source: Journal of Medical Imaging and Radiation Oncology - May 18, 2023 Category: Radiology Authors: Giles Kisby, James H Seow, Greg Schie, Constantine C Phatouros, Kay ‐Vin Lam, Tracey Muir, Sally Burrows, Paul M Parizel Tags: Medical Imaging —Original Article Source Type: research

Percutaneous management of acute ischaemic stroke
Learning objectives To understand both the rationale and principles behind percutaneous management of stroke. To be aware of the evidence base for this treatment. To appreciate the current logistical challenges and how they might be overcome. Introduction In principle, the similarity between opening an occluded cerebral artery and an occluded coronary artery, when the perfusion to that organ is acutely compromised, is inescapable: to re-establish antegrade flow as quickly as possible to minimise downstream damage. There are, of course, important differences between an acute myocardial infarction (MI) and an acute ischaemic...
Source: Heart - April 25, 2023 Category: Cardiology Authors: Routledge, H., Curzen, N. Tags: Education in Heart Source Type: research

Machine learning segmentation of core and penumbra from acute stroke CT perfusion data
We present an alternative model for the estimation of tissue fate using multiple perfusion measures simultaneously.MethodsWe used machine learning (ML) models based on four different algorithms, combining four CTP measures (cerebral blood flow, cerebral blood volume, mean transit time and delay time) plus 3D-neighborhood (patch) analysis to predict the acute ischemic core and perfusion lesion volumes. The model was developed using 86 patient images, and then tested further on 22 images.ResultsXGBoost was the highest-performing algorithm. With standard threshold-based core and penumbra measures as the reference, the model d...
Source: Frontiers in Neurology - February 23, 2023 Category: Neurology Source Type: research

A deep learning approach to predict collateral flow in stroke patients using radiomic features from perfusion images
We present a multi-stage deep learning approach to predict collateral flow grading in stroke patients based on radiomic features extracted from MR perfusion data. First, we formulate a region of interest detection task as a reinforcement learning problem and train a deep learning network to automatically detect the occluded region within the 3D MR perfusion volumes. Second, we extract radiomic features from the obtained region of interest through local image descriptors and denoising auto-encoders. Finally, we apply a convolutional neural network and other machine learning classifiers to the extracted radiomic features to ...
Source: Frontiers in Neurology - February 21, 2023 Category: Neurology Source Type: research

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients
CONCLUSION: Reliable TSPO PET quantification is achievable by using a single late PET frame divided by a late blood sample activity concentration.PMID:36682921 | DOI:10.1016/j.zemedi.2022.11.008
Source: Zeitschrift fur Medizinische Physik - January 22, 2023 Category: Radiology Authors: Artem Zatcepin Anna Kopczak Adrien Holzgreve Sandra Hein Andreas Schindler Marco Duering Lena Kaiser Simon Lindner Martin Schidlowski Peter Bartenstein Nathalie Albert Matthias Brendel Sibylle I Ziegler Source Type: research

Image-to-image generative adversarial networks for synthesizing perfusion parameter maps from DSC-MR images in cerebrovascular disease
Stroke is a major cause of death or disability. As imaging-based patient stratification improves acute stroke therapy, dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is of major interest in image brain perfusion. However, expert-level perfusion maps require a manual or semi-manual post-processing by a medical expert making the procedure time-consuming and less-standardized. Modern machine learning methods such as generative adversarial networks (GANs) have the potential to automate the perfusion map generation on an expert level without manual validation. We propose a modified pix2pix GAN with a tempo...
Source: Frontiers in Neurology - January 10, 2023 Category: Neurology Source Type: research

Machine learning based outcome prediction of large vessel occlusion of the anterior circulation prior to thrombectomy in patients with wake-up stroke
CONCLUSION: Machine learning algorithms have the potential to aid in the decision making for thrombectomy in patients with wake-up stroke especially in hospitals, where emergency CTP or MRI imaging is not available.PMID:36344011 | DOI:10.1177/15910199221135695
Source: Interventional Neuroradiology - November 7, 2022 Category: Radiology Authors: Ludger Feyen Christian Blockhaus Marcus Katoh Patrick Haage Christina Schaub Stefan Rohde Source Type: research

Image level detection of large vessel occlusion on 4D-CTA perfusion data using deep learning in acute stroke
Acute ischemic stroke (AIS) secondary to LVOs represent approximately 30-40% of all stroke cases and are associated with disproportionately higher morbidity and mortality.1, 2 The importance of endovascular thrombectomy (EVT) in patients with acute ischemic stroke (AIS) has been well established in multiple randomized controlled trials for patients in both early and late stroke windows.3-6 A critical aspect of the patient triage is the accurate and timely detection of underlying large vessel occlusion (LVO).
Source: Journal of Stroke and Cerebrovascular Diseases - September 10, 2022 Category: Neurology Authors: Girish Bathla, Dhruba Durjoy, Sarv Priya, Edgar Samaniego, Colin P. Derdeyn Source Type: research

Collateral-Core Ratio as a Novel Predictor of Clinical Outcomes in Acute Ischemic Stroke
AbstractThe interaction effect between collateral circulation and ischemic core size on stroke outcomes has been highlighted in acute ischemic stroke (AIS). However, biomarkers that assess the magnitude of this interaction are still lacking. We aimed to present a new imaging marker, the collateral-core ratio (CCR), to quantify the interaction effect between these factors and evaluate its ability to predict functional outcomes using machine learning (ML) in AIS. Patients with AIS caused by anterior circulation large vessel occlusion (LVO) were recruited from a prospective multicenter study. CCR was calculated as collateral ...
Source: Translational Stroke Research - July 25, 2022 Category: Neurology Source Type: research