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Total 258 results found since Jan 2013.
Prediction of Clinical Outcomes in Acute Ischaemic Stroke Patients: A Comparative Study
Conclusion: Aggregating clinical and imaging information leads to considerably better outcome prediction models. While lesion-symptom mapping is a useful tool to investigate structure-function relationships of the brain, it does not lead to better outcome predictions compared to a simple data-driven feature selection approach, which is less computationally expensive and easier to implement.
Source: Frontiers in Neurology - May 6, 2021 Category: Neurology Source Type: research
A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework
This study reviews the modern and automated methods such as artificial intelligence (AI)-based. Machine learning (ML) and deep learning (DL) can provide automated techniques in the detection and measurement of cIMT and PA from carotid vascular images. Both ML and DL techniques are examples of supervised learning, i.e., learn from “ground truth” images and transformation of test images that are not part of the training. This review summarizes (1) the evolution and impact of the fast-changing AI technology on cIMT/PA measurement, (2) the mathematical representations of ML/DL methods, and (3) segmentation approaches for c...
Source: Journal of Digital Imaging - June 2, 2021 Category: Radiology Source Type: research
Automated Detection of Ischemic Stroke and Subsequent Patient Triage in Routinely Acquired Head CT
ConclusionOur study demonstrates the potential of a weakly supervised anomaly-detection tool to detect stroke findings in head CT. Definite classification into normal/pathological was made with high accuracy in> 2/3 of patients. Anomaly heatmaps further provide guidance towards pathologies, also in cases with inconclusive ratings.
Source: Clinical Neuroradiology - August 31, 2021 Category: Neurology Source Type: research
Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study
ConclusionsWith the assistance of our proposed DL model, radiologists got better performance in the detection of AIS lesions on NCCT.
Source: Insights into Imaging - December 6, 2022 Category: Radiology Source Type: research
Severe paraneoplastic hypoglycemia secondary to a gastrointestinal stromal tumour masquerading as a stroke.
We report the case of a 70-year-old previously healthy female who presented acutely to the Accident and Emergency department with left-sided vasomotor symptoms including reduced muscle tone, weakness upon walking and slurred speech. Physical examination confirmed hemiparesis with VIIth nerve palsy and profound hepatomegaly. A random glucose was low at 1.7 mmol/l, which upon correction resolved her symptoms. In hindsight, the patient recalled having had similar episodes periodically over the past 3 months to which she did not give much attention. While hospitalized, she continued having episodes of symptomatic hypoglycaem...
Source: Diabetes Metab - November 7, 2015 Category: Endocrinology Authors: Dimitriadis GK, Gopalakrishnan K, Rao R, Grammatopoulos DK, Randeva HS, Weickert MO, Murthy N Tags: Endocrinol Diabetes Metab Case Rep Source Type: research
Spontaneous white matter lesion in brain of stroke-prone renovascular hypertensive rats: a study from MRI, pathology and behavior
This study aimed to investigate the WML in RHRSP from MRI, pathology and behavior. RHRSP model was established by two-kidney, two-clipmethod and kept for 20 weeks. WML was decteted by magnetic resonance imaging (MRI) and loyez staining. Cognition was tested by morris water maze (MWM). Vascular changes were observed by HE staining on brain and carotid sections. Ultrastucture of blood brain barrier (BBB) were observed by transmission electron microscope. Immunofluorescence was used to detect albumin leakage and cell proliferation. T2-weighted MRI scans of RHRSP displayed diffuse, confluent white-matter hyperintensities. Pat...
Source: Metabolic Brain Disease - November 11, 2015 Category: Neurology Source Type: research
Stroke
This 18-month-old girl developed left-sided focal seizures, left arm and leg weakness 3 days after an uncomplicated appendicectomy. She had been previously well, and the surgery was uneventful. An urgent cranial MR scan was performed under general anaesthetic within 12 h of the onset of symptoms. Look at the selected images from this study and answer the following questions. Read on to confirm the answers and learn more about the use of diffusion-weighted imaging (DWI) in this condition. Questions There is evidence of acute intracerebral haemorrhage. (True or false?) The abnormality is in the left middle cerebral...
Source: Archives of Disease in Childhood - Education and Practice - May 17, 2016 Category: Pediatrics Authors: Williams, H. Tags: Oncology, Illuminations, Epilepsy and seizures, Stroke, Child health, Other anaesthesia Source Type: research
Deep learning fully convolution network for lumen characterization in diabetic patients using carotid ultrasound: a tool for stroke risk
AbstractManual ultrasound (US)-based methods are adapted for lumen diameter (LD) measurement to estimate the risk of stroke but they are tedious, error prone, and subjective causing variability. We propose an automated deep learning (DL)-based system for lumen detection. The system consists of a combination of two DL systems: encoder and decoder for lumen segmentation. The encoder employs a 13-layer convolution neural network model (CNN) for rich feature extraction. The decoder employs three up-sample layers of fully convolution network (FCN) for lumen segmentation. Three sets of manual tracings were used during the traini...
Source: Medical and Biological Engineering and Computing - January 26, 2019 Category: Biomedical Engineering Source Type: research
Deep Learning in the Prediction of Ischaemic Stroke Thrombolysis Functional Outcomes: A Pilot Study
ConclusionDL models may aid in the prediction of functional thrombolysis outcomes. Further investigation with larger datasets and additional imaging sequences is indicated.
Source: Academic Radiology - May 2, 2019 Category: Radiology Source Type: research
White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts – The MRI-GENIE study
Publication date: Available online 29 May 2019Source: NeuroImage: ClinicalAuthor(s): Markus D. Schirmer, Adrian V. Dalca, Ramesh Sridharan, Anne-Katrin Giese, Kathleen L. Donahue, Marco J. Nardin, Steven J.T. Mocking, Elissa C. McIntosh, Petrea Frid, Johan Wasselius, John W. Cole, Lukas Holmegaard, Christina Jern, Jordi Jimenez-Conde, Robin Lemmens, Arne G. Lindgren, James F. Meschia, Jaume Roquer, Tatjana Rundek, Ralph L. SaccoAbstractWhite matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS)....
Source: NeuroImage: Clinical - May 29, 2019 Category: Radiology Source Type: research
Posterior circulation stroke: machine learning-based detection of early ischemic changes in acute non-contrast CT scans
ConclusionsQuantitative features of early hyperacute NCCTs can be used to detect early ischemic changes in pc-ASPECTS regions. The classifier performance was higher or equal to results of human raters. The proposed approach could facilitate reproducible analysis in research and may allow standardized assessments for outcome prediction and therapy planning in clinical routine.
Source: Journal of Neurology - May 10, 2020 Category: Neurology Source Type: research
C2MA-Net: Cross-Modal Cross-Attention Network for Acute Ischemic Stroke Lesion Segmentation Based on CT Perfusion Scans
Conclusion: This study demonstrates advantages of applying C2MA-network to segment AIS lesions, which yields promising segmentation accuracy, and achieves semantic decoupling by processing different parameter modalities separately. Significance: Proving the potential of cross-modal interactions in attention to assist identifying new imaging biomarkers for more accurately predicting AIS prognosis in future studies.
Source: IEEE Transactions on Biomedical Engineering - December 24, 2021 Category: Biomedical Engineering 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
