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CT matches MRI for late-window stroke evaluation
Stroke patients who underwent endovascular therapy had similar improvement...Read more on AuntMinnie.comRelated Reading: Machine learning can predict stroke treatment outcomes Study reveals steep cost of delaying stroke treatment 3 CTA signs show which stroke patients can skip surgery Perfusion imaging expands window for stroke treatment CTA helps direct use of clot removal for stroke patients
Source: AuntMinnie.com Headlines - February 6, 2019 Category: Radiology Source Type: news

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

CT radiomics unlocks basal ganglia stroke onset time
The combination of radiomics and a machine-learning algorithm can determine...Read more on AuntMinnie.comRelated Reading: AI may help improve management of stroke patients AI finds infarction in stroke patients on unenhanced CT CT plus CT perfusion predicts stroke surgery outcomes CTA lowers costs, improves outcomes for minor stroke Can AI find brain hemorrhage as well as radiologists?
Source: AuntMinnie.com Headlines - February 11, 2020 Category: Radiology Source Type: news

Defining reperfusion post endovascular therapy in ischemic stroke using MR-dynamic contrast enhanced perfusion.
CONCLUSION: MR perfusion following EVT provides accurate physiological approach to understanding the relationship of CBF, clinical outcome, and DWI growth. ADVANCES IN KNOWLEDGE: MR perfusion CBF acquired is a robust, objective reperfusion measurement providing following recanalization of the target occlusion which is critical to distinguish potential therapeutic harm from the failed technical success of EVT as well as improve the responsiveness of clinical trial outcomes to disease modification. PMID: 32941770 [PubMed - as supplied by publisher]
Source: The British Journal of Radiology - September 16, 2020 Category: Radiology Authors: d'Esterre CD, Sah RG, Assis Z, Talai AS, Demchuk AM, Hill MD, Goyal M, Lee TY, Forkert ND, Barber PA Tags: Br J Radiol 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

Abstract No. 720 Identification of irreversibly damaged brain tissue on computed tomography perfusion using convolutional neural network to assist selection for mechanical thrombectomy in ischemic stroke patients
Endovascular treatment of ischemic stroke has shown positive clinical outcomes. Further optimization requires identifying patients who will benefit from reperfusion. We propose using deep learning, specifically 3D convolutional neural networks (CNN), to identify infarcted tissue (core) on CT perfusion (CTP) with diffusion weighted imaging (DWI) MRI as gold standard for irreversible brain infarction and evaluate lesion size impact on the network ’s performance.
Source: Journal of Vascular and Interventional Radiology : JVIR - February 20, 2020 Category: Radiology Authors: R. Wang, K. Chang, H. Zhou, J. Wu, G. Cohan, M. Jayaraman, R. Huang, J. Boxerman, L. Yang, F. Hui, J. Woo, H. Bai Tags: Scientific Traditional Poster Source Type: research

Developing new quantitative CT image markers to predict prognosis of acute ischemic stroke patients
CONCLUSIONS: This study demonstrates feasibility of developing a new quantitative imaging method and marker to predict AIS patients' prognosis in the hyperacute stage, which can help clinicians optimally treat and manage AIS patients.PMID:35213340 | DOI:10.3233/XST-221138
Source: Journal of X-Ray Science and Technology - February 25, 2022 Category: Radiology Authors: Gopichandh Danala Bappaditya Ray Masoom Desai Morteza Heidari Seyedehnafiseh Mirniaharikandehei Sai Kiran R Maryada Bin Zheng Source Type: research

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