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Intima-Media Thickness and Cognitive Function in Stroke-Free Middle-Aged Adults: Findings From the Coronary Artery Risk Development in Young Adults Study Clinical Sciences
Conclusions— We observed an association between greater IMT and worse processing speed—a key component of cognitive functioning—at middle age above and beyond traditional vascular risk factors. Efforts targeted at preventing early stages of atherosclerosis may modify the course of cognitive aging.
Source: Stroke - July 27, 2015 Category: Neurology Authors: Al Hazzouri, A. Z., Vittinghoff, E., Sidney, S., Reis, J. P., Jacobs, D. R., Yaffe, K. Tags: Cerebrovascular disease/stroke, Risk Factors, Epidemiology Clinical Sciences Source Type: research

What Are the Classifications of Perinatal Stroke?
Discussion Perinatal stroke occurs in about 1:1000 live births and is a “focal vascular injury from the fetal period to 28 days postnatal age.” Perinatal stroke is the most common cause of hemiparetic cerebral palsy and causes other significant morbidity including cognitive deficits, learning disabilities, motor problems, sensory problems including visual and hearing disorders, epilepsy, and behavioral and psychological problems. Family members are also affected because of the potential anxiety and guilt feelings that having a child with a stroke presents, along with the care that may be needed over the child&#...
Source: PediatricEducation.org - May 1, 2023 Category: Pediatrics Authors: Pediatric Education Tags: Uncategorized Source Type: news

Prehospital Ultrasound Proves its Worth in the War Against Stroke
Discussion Stroke is a devastating neurologic condition with an alarming prevalence. Each year, an estimated 795,000 people in the United States alone will suffer a stroke. Stroke accounts for one in every 20 deaths in the U.S., and someone dies of stroke in the U.S. every four minutes.1 One third of people who have had a stroke will be left with some degree of long-term disability.2 Eighty-seven percent of all strokes are ischemic, meaning that a clot or other occlusion to blood flow forms within an intracranial vessel, depriving the brain tissue of blood flow.1 If this obstruction isn't rapidly relieved, damage to the brain will occur.
Source: JEMS Patient Care - December 1, 2016 Category: Emergency Medicine Authors: Jenna M. B. White, MD Tags: Patient Care Source Type: news

A Special Report on Changing Trends in Preventive Stroke/Cardiovascular Risk Assessment Via B-Mode Ultrasonography
AbstractPurpose of ReviewCardiovascular disease (CVD) and stroke risk assessment have been largely based on the success of traditional statistically derived risk calculators such as Pooled Cohort Risk Score or Framingham Risk Score. However, over the last decade, automated computational paradigms such as machine learning (ML) and deep learning (DL) techniques have penetrated into a variety of medical domains including CVD/stroke risk assessment. This review is mainly focused on the changing trends in CVD/stroke risk assessment and its stratification from statistical-based models to ML-based paradigms using non-invasive car...
Source: Current Atherosclerosis Reports - April 30, 2019 Category: Cardiology Source Type: research

Object-Specific Four-Path Network for Stroke Risk Stratification of Carotid Arteries in Ultrasound Images
In this study, we propose an object-specific four-path network (OSFP-Net) for stroke risk assessment by integrating ultrasound carotid plaques in both transverse and longitudinal sections of the bilateral carotid arteries. Each path of the OSFP-Net comprises of a feature extraction subnetwork (FE) and a feature downsampling subnetwork (FD). The FEs in the four paths use the same network structure to automatically extract features from ultrasound images of carotid plaques. The FDs use different object-specific pooling strategies for feature downsampling based on the observation that the sizes and shapes in the feature maps ...
Source: Computational and Mathematical Methods in Medicine - May 5, 2022 Category: Statistics Authors: Wei Ma Yujiao Xia Xiaoyan Wu Zheng Yue Xinyao Cheng Aaron Fenster Mingyue Ding Source Type: research

Acute ischemic stroke what is hidden behind?
We present a case of a 58-year-old male patient that presented to ED with sudden onset of headache and left-sided hemiparesis, computed tomography (CT) demonstrated an ischemic stroke of the right middle cerebral artery. When the question of whether to start r-TPA or mechanical thrombectomy was discussed, a cardiac point-of-care ultrasound was performed in ED and showed a type A aortic dissection; immediately a CT aortic angiogram was performed and confirmed the diagnosis. The patient was taken to theater and had a favorable outcome. <Learning objective: Acute aortic dissection (AAD) may present as acute ischemic st...
Source: Journal of Cardiology Cases - August 31, 2017 Category: Cardiology Source Type: research

Can you learn to cough after having a stroke?
A strong cough, requires powerful coordinated contraction of expiratory (abdominal) muscles. The expiratory muscles contract to build up high positive intrapleural and intra-airway pressures for development of peak expiratory Flow rates. Expiratory muscle strength training (EMST) has been shown to improve parameters related to pulmonary function, speech, and cough.However, no one has investigated what changes occur in the activation of abdominal muscles after training. The aim of this study is to clarify which role plays the coordination of abdominal muscles in expiratory flows. The null hypothesis was that stroke patients...
Source: European Respiratory Journal - December 1, 2022 Category: Respiratory Medicine Authors: Dominguez Sanz, N. Tags: 09.02 - Physiotherapists Source Type: research

A Review on Carotid Ultrasound Atherosclerotic Tissue Characterization and Stroke Risk Stratification in Machine Learning Framework
Abstract Cardiovascular diseases (including stroke and heart attack) are identified as the leading cause of death in today’s world. However, very little is understood about the arterial mechanics of plaque buildup, arterial fibrous cap rupture, and the role of abnormalities of the vasa vasorum. Recently, ultrasonic echogenicity characteristics and morphological characterization of carotid plaque types have been shown to have clinical utility in classification of stroke risks. Furthermore, this characterization supports aggressive and intensive medical therapy as well as procedures, including endarterectomy and ...
Source: Current Atherosclerosis Reports - August 2, 2015 Category: Cardiology Source Type: research

Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study
AbstractMachine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the “multiclass machine learning (MCML)-based algorithms” (labelled as AtheroEdge 3.0ML) and assess whether considering carotid ultrasound imaging fused with conventional risk factors can provide better CVD/stroke risk prediction than conventional CVD risk calculators (CCVRC). Carotid ultrasound and coronary angiography were performed on 500 participants. Stenosis in the ...
Source: The International Journal of Cardiovascular Imaging - November 12, 2020 Category: Radiology Source Type: research

Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm
This study proposes an attention-channel-based UNet deep learning (DL) model that identifies the carotid plaques in the internal carotid artery (ICA) and common carotid artery (CCA) images. Our experiments consist of 970 ICA images from the UK, 379 CCA images from diabetic Japanese patients, and 300 CCA images from post-menopausal women from Hong Kong. We combined both CCA images to form an integrated database of 679 images. A rotation transformation technique was applied to 679 CCA images, doubling the database for the experiments. The cross-validation K5 (80% training: 20% testing) protocol was applied for accuracy deter...
Source: Atherosclerosis - October 26, 2022 Category: Cardiology Authors: Pankaj K Jain Abhishek Dubey Luca Saba Narender N Khanna John R Laird Andrew Nicolaides Mostafa M Fouda Jasjit S Suri Neeraj Sharma Source Type: research

Stroke Risk Stratification and its Validation using Ultrasonic Echolucent Carotid Wall Plaque Morphology: A Machine Learning Paradigm
Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has recently been shown to have a promise in classification of high risk versus low risk plaque or symptomatic versus asymptomatic plaques. In previous studies, this stratification has been mainly based on analysis of the far wall of the carotid artery. Due to the multifocal nature of atherosclerotic disease, the plaque growth is not restricted to the far wall alone. This paper presents a new approach for stroke risk assessment by integrating assessment of both the near and far walls of the carotid artery using grayscale morphology of the plaque.
Source: Computers in Biology and Medicine - November 25, 2016 Category: Bioinformatics Authors: Tadashi Araki, Pankaj K. Jain, Harman S. Suri, Narendra D. Londhe, Nobutaka Ikeda, Ayman El-Baz, Vimal K. Shrivastava, Luca Saba, Andrew Nicolaides, Shoaib Shafique, John R. Laird, Ajay Gupta, Jasjit S. Suri Source Type: research

Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm
AbstractSevere atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the m...
Source: Journal of Medical Systems - May 13, 2017 Category: Information Technology Source Type: research

Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors.
CONCLUSION: The AtheroRisk-integrated ML system outperforms the AtheroRisk-conventional ML system using RF classifier. PMID: 32861380 [PubMed - in process]
Source: Indian Heart J - June 30, 2020 Category: Cardiology Authors: Jamthikar A, Gupta D, Khanna NN, Saba L, Laird JR, Suri JS Tags: Indian Heart J 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

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