Filtered By:
Specialty: Neurology
Education: Learning
Procedure: PET Scan

This page shows you your search results in order of relevance.

Order by Relevance | Date

Total 45 results found since Jan 2013.

Predicting Future Brain Tissue Loss From White Matter Connectivity Disruption in Ischemic Stroke Clinical Sciences
Conclusions— ChaCo scores varied, but the most affected regions included those with sensorimotor, perception, learning, and memory functions. Correlations between baseline ChaCo and subsequent tissue loss suggest that the Network Modification Tool could be used to identify regions most susceptible to remote degeneration from acute infarcts.
Source: Stroke - February 24, 2014 Category: Neurology Authors: Kuceyeski, A., Kamel, H., Navi, B. B., Raj, A., Iadecola, C. Tags: Computerized tomography and Magnetic Resonance Imaging, Pathology of Stroke Clinical Sciences Source Type: research

Boosted Tree Model Reforms Multimodal Magnetic Resonance Imaging Infarct Prediction in Acute Stroke Clinical Sciences
Background and Purpose—Stroke imaging is pivotal for diagnosis and stratification of patients with acute ischemic stroke to treatment. The potential of combining multimodal information into reliable estimates of outcome learning calls for robust machine learning techniques with high flexibility and accuracy. We applied the novel extreme gradient boosting algorithm for multimodal magnetic resonance imaging–based infarct prediction.Methods—In a retrospective analysis of 195 patients with acute ischemic stroke, fluid-attenuated inversion recovery, diffusion-weighted imaging, and 10 perfusion parameters were derived from...
Source: Stroke - March 26, 2018 Category: Neurology Authors: Michelle Livne, Jens K. Boldsen, Irene K. Mikkelsen, Jochen B. Fiebach, Jan Sobesky, Kim Mouridsen Tags: Magnetic Resonance Imaging (MRI), Ischemic Stroke Original Contributions Source Type: research

Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis
ConclusionA fast and fully automatic method can be used for stroke subtype risk assessment and classification based on fundus photographs alone.
Source: Frontiers in Neurology - August 22, 2022 Category: Neurology Source Type: research

A study on the natural history of scanning behaviour in patients with visual field defects after stroke
DiscussionThe longitudinal comparison of patients who do and do not learn compensatory scanning techniques may reveal important prognostic markers of natural recovery. Importantly, it may also help to determine the most effective treatment window for visual rehabilitation.
Source: BMC Neurology - April 24, 2015 Category: Neurology Authors: Tobias LoetscherCelia ChenSophie WignallAndreas BullingSabrina HoppeOwen ChurchesNicole ThomasMichael NichollsAndrew Lee Source Type: research

Clinical Evaluation of the Patient With Acute Stroke
This article reviews the clinical evaluation of the patient with acute stroke, including key questions in the focused stroke history, important aspects of the National Institutes of Health Stroke Scale and focused neurologic examination, and the significance of the basic head CT scan in informing a timely treatment decision. Recent Findings: Advances in both stroke treatment and enhanced diagnostics support an evolving paradigm for acute stroke care, ranging from the prehospital setting to the rehabilitative setting. An international emphasis on best practice strategies promotes efficiency and standardization in stroke sy...
Source: CONTINUUM: Lifelong Learning in Neurology - February 1, 2017 Category: Neurology Tags: Review Articles Source Type: research

Application of Machine Learning Techniques to Identify Data Reliability and Factors Affecting Outcome After Stroke Using Electronic Administrative Records
Conclusion: Electronic administrative records from this cohort produced reliable outcome prediction and identified clinically appropriate factors negatively impacting most outcome variables following hospital admission with stroke. This presents a means of future identification of modifiable factors associated with patient discharge destination. This may potentially aid in patient selection for certain interventions and aid in better patient and clinician education regarding expected discharge outcomes.
Source: Frontiers in Neurology - September 27, 2021 Category: Neurology Source Type: research

Cognitive state following mild stroke: A matter of hippocampal mean diffusivity
This article is protected by copyright. All rights reserved.
Source: Hippocampus - July 27, 2015 Category: Neurology Authors: Efrat Kliper, Einor Ben Assayag, Amos D. Korczyn, Eitan Auriel, Ludmila Shopin, Hen Hallevi, Shani Shenhar‐Tsarfaty, Anat Mike, Moran Artzi, Ilana Klovatch, Natan M. Bornstein, Dafna Ben Bashat Tags: Research Article Source Type: research

Accelerating Prediction of Malignant Cerebral Edema After Ischemic Stroke with Automated Image Analysis and Explainable Neural Networks
ConclusionsAn LSTM neural network incorporating volumetric data extracted from routine CT scans identified all cases of malignant cerebral edema by 24  h after stroke, with significantly fewer false positives than a fully connected neural network, regression model, and the validated EDEMA score. This preliminary work requires prospective validation but provides proof of principle that a deep learning framework could assist in selecting patients f or surgery prior to deterioration.
Source: Neurocritical Care - August 20, 2021 Category: Neurology Source Type: research

Domain-general subregions of the medial prefrontal cortex contribute to recovery of language after stroke
AbstractWe hypothesized that the recovery of speech production after left hemisphere stroke not only depends on the integrity of language-specialized brain systems, but also on ‘domain-general’ brain systems that have much broader functional roles. The presupplementary motor area/dorsal anterior cingulate forms part of the cingular-opercular network, which has a broad role in cognition and learning. Consequently, we have previously suggested that variability in the rec overy of speech production after aphasic stroke may relate in part to differences in patients’ abilities to engage this domain-general brain region. T...
Source: Brain - June 27, 2017 Category: Neurology Source Type: research

Connectomic insight into unique stroke patient recovery after rTMS treatment
This study demonstrates for the first time the feasibility of using individualized connectivity analyses in differentiating unique phenotypes in rTMS treatment responses and recovery. This personalized connectomic approach may be utilized in the future to better understand patient recovery trajectories with neuromodulatory treatment.
Source: Frontiers in Neurology - July 6, 2023 Category: Neurology Source Type: research

Neurofunctional correlates of a neurorehabilitation system based on eye movements in chronic stroke impairment levels: A pilot study
ConclusionThese promising results have a potential application as a new game-based neurorehabilitation approach to enhance the motor activity of stroke patients.
Source: Brain and Behavior - July 12, 2023 Category: Neurology Authors: B árbara R. García‐Ramos, Rebeca Villarroel, José L. González‐Mora, Consuelo Revert, Cristián Modroño Tags: ORIGINAL ARTICLE Source Type: research

Quantifying the Impact of Chronic Ischemic Injury on Clinical Outcomes in Acute Stroke With Machine Learning
Acute stroke is often superimposed on chronic damage from previous cerebrovascular events. This background will inevitably modulate the impact of acute injury on clinical outcomes to an extent that will depend on the precise anatomical pattern of damage. Previous attempts to quantify such modulation have employed only reductive models that ignore anatomical detail. The combination of automated image processing, large-scale data, and machine learning now enables us to quantify the impact of this with high-dimensional multivariate models sensitive to individual variations in the detailed anatomical pattern. We introduce and ...
Source: Frontiers in Neurology - January 23, 2020 Category: Neurology Source Type: research

Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability
ConclusionsCAPITAL-CT generated standard and reproducible images that could simplify the work of radiologists, which would be of great help in the follow-up of stroke patients and in multifield research in neuroscience.
Source: Frontiers in Neurology - March 11, 2022 Category: Neurology Source Type: research

DWI Negative Stroke: Learning Points For Imaging In Acute Stroke (P1.037)
CONCLUSIONS: Clinical exam bears more weight than imaging in suspected brainstem infarcts. With the increasing use of DWI as the imaging of choice in acute stroke, DWI negative stroke must be considered in patients who present with classic brain stem infarcts with negative imaging to prevent delay in therapy as these patients may still be a candidate for thrombolysis.Disclosure: Dr. Nalleballe has nothing to disclose. Dr. JADEJA has nothing to disclose. Dr. Bollu has nothing to disclose. Dr. Onteddu has nothing to disclose.
Source: Neurology - April 8, 2015 Category: Neurology Authors: Nalleballe, K., Jadeja, N., Bollu, P., Onteddu, S. Tags: Cerebrovascular Disease and Interventional Neurology: Case Reports Source Type: research

Collateral Automation for Triage in Stroke: Evaluating Automated Scoring of Collaterals in Acute Stroke on Computed Tomography Scans
In conclusion, ­e-CTA provides a real-time and fully automated approach to collateral scoring with the potential to improve consistency of image interpretation and to independently quantify collateral scores even without expert rater input.Cerebrovasc Dis
Source: Cerebrovascular Diseases - June 19, 2019 Category: Neurology Source Type: research