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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

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

Ultrasound imaging gauges muscle tightness after stroke
Ultrasound strain imaging can be an effective tool for assessing poststroke...Read more on AuntMinnie.comRelated Reading: MRI links lifestyle factors to stroke, dementia risk 5 risk factors help predict brain hemorrhage on CT AI algorithm can triage head CT exams for urgent review Ultrasound elastography helps identify invasive breast cancer AIUM: Can deep learning classify liver fibrosis on US?
Source: AuntMinnie.com Headlines - August 22, 2018 Category: Radiology Source Type: news

Women less likely to receive poststroke imaging
Women who have experienced ischemic stroke are less likely than men to be evaluated...Read more on AuntMinnie.comRelated Reading: Start-up BURL develops ultrasound-based 'ECG for stroke' Machine learning can predict stroke treatment outcomes Medical groups urge endovascular training for stroke 3 CTA signs show which stroke patients can skip surgery Northwestern Medicine hastens stroke care with mobile CT unit
Source: AuntMinnie.com Headlines - January 31, 2019 Category: Radiology Source Type: news

Contrast-enhanced ultrasound to predict the risk of microembolization during carotid artery stenting
Conclusion Contrast enhancement of the carotid plaque is strongly associated with post-procedural microembolization and for this reason it can be considered a reliable tool for an accurate selection of patients undergoing this endovascular treatment. However, the neurocognitive test scores performed in this study are not enough sensible to appreciate the impact of the neurological injury on the day life activities.
Source: La Radiologia Medica - March 25, 2015 Category: Radiology Source Type: research

AI comparable to rads for interpreting wrist x-rays
An artificial intelligence (AI) deep-learning algorithm performs comparably...Read more on AuntMinnie.comRelated Reading: Ultrasound can benefit daily rheumatology practice Skip ultrasound for treatment decisions in rheumatoid arthritis AI accurately estimates bone age on 3D hand MRI AI can detect, localize fractures on wrist x-rays Ultrasound imaging gauges muscle tightness after stroke
Source: AuntMinnie.com Headlines - March 17, 2020 Category: Radiology Source Type: news

Brain lesions on DWI-MRI linked to poor outcomes for some
Lesions that appear on diffusion-weighted imaging (DWI) MRI scans represent...Read more on AuntMinnie.comRelated Reading: Deep-learning model detects cerebral microbleeds on MRI Key MRI markers link vascular brain injury to health risks 5 risk factors help predict brain hemorrhage on CT Combination of ultrasound, tPA may boost stroke treatment CT guidance helps brain hemorrhage outcomes
Source: AuntMinnie.com Headlines - July 21, 2020 Category: Radiology Source Type: news

Ultrasound-based internal carotid artery plaque characterization using deep learning paradigm on a supercomputer: a cardiovascular disease/stroke risk assessment system
AbstractVisual or manual characterization and classification of atherosclerotic plaque lesions are tedious, error-prone, and time-consuming. The purpose of this study is to develop and design an automated carotid plaque characterization and classification system into binary classes, namely symptomatic and asymptomatic types via the deep learning (DL) framework implemented on a supercomputer. We hypothesize that on ultrasound images, symptomatic carotid plaques have (a) a low grayscale median because of a histologically large lipid core and relatively little collagen and calcium, and (b) a higher chaotic (heterogeneous) gra...
Source: The International Journal of Cardiovascular Imaging - January 9, 2021 Category: Radiology Source Type: research

Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study
ConclusionsThe DL model based on US videos corresponding to real examinations showed robust performance for plaque detection and significantly improved the diagnostic performance of junior radiologists.Key Points• The deep learning model based on US videos conforming to real examinations showed robust performance for plaque detection.• Computer-aided diagnosis can significantly improve the diagnostic performance of junior radiologists in clinical practice.
Source: European Radiology - December 13, 2022 Category: Radiology Source Type: research

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