Articles tagged with Cardiac Imaging
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Researchers at U of A are developing an AI-powered system to analyze cardiac images, enabling clinicians to diagnose heart disease more accurately. The project aims to reduce healthcare costs and improve patient outcomes, with potential global implications.
Public health experts recommend continuing routine mask-wearing in healthcare settings to protect vulnerable patients and staff from COVID-19. The authors argue that while severe cases have decreased, asymptomatic spread remains a threat, particularly among high-risk patients and healthcare workers who may not be aware they are infected.
A new imaging method developed by UC researchers can identify specific lung infections in real time, reducing diagnosis time from 2-3 days to hours. The method uses injectable probes that light up under a nuclear imaging machine, enabling faster treatment for critically ill patients.
Researchers found a strong association between certain gut bacteria and coronary atherosclerotic plaques, which can lead to heart attacks. The study analyzed gut bacteria and cardiac imaging data from over 8,900 participants and identified Streptococcus species as key players.
Researchers have developed a new PET model to quantify cardiac amyloidosis, allowing for more accurate diagnoses and monitoring. The study found that a two-tissue reversible compartment model is the best method for quantifying 18F-flutemetamol myocardial uptake.
A new study from researchers at Wake Forest University School of Medicine reveals that cardiac magnetic resonance imaging (MRI) is a safe and accurate tool to evaluate complex patients. Cardiac MRI reduced the need for invasive angiography over the long-term follow-up period, making it a highly reliable first-line testing option.
A Houston Methodist study found that COVID-19 variants and severity affect heart function, with microvascular involvement seen less often after nine months. The study recommends PET scans to check for microvascular dysfunction, which may be reversible.
Researchers developed a novel endoscopic imaging system with a bioinspired sensor that can detect multiple fluorescent probes, enabling more accurate fluorescence-guided cancer surgery. The system showed improved spatial resolution and sensitivity in detecting tumors, paving the way for the adoption of multi-tracer FGS.
A new study found that photon-counting computed tomography (PCCT) provides sharper images and less image noise than dual-source CT (DSCT) in infants with suspected cardiac heart defects. The PCCT images had higher mean overall visual image quality ratings and were more than 97% diagnostic quality, compared to 77% for DSCT.
The study used magnetic resonance imaging (MRI) to measure acute pressure changes inside the heart, discovering that pressure increases when patients receive a specific medication called adenosine. This technology can help doctors better diagnose and monitor patients with heart disease and heart failure.
EuroPCR 2023 brings together experts in interventional cardiovascular medicine to share knowledge, skills, and innovations. The event features 220 workshops, live-streamed sessions, and a scientific abstract competition.
Dr. Miaomiao Zhang's research aims to automate late mechanical activation detection from cardiac magnetic resonance images using machine learning and AI techniques. This could lead to more accurate placement of CRT electrodes and improved patient outcomes.
The program guide for TVT 2023 showcases over 200 world-renowned faculty experts, with a focus on clinical decision-making and strategies for treating valvular heart disease. The summit highlights the latest advances in transcatheter valve therapy and nonsurgical procedures.
A UK Biobank study found that cancer survivors may be at long-term increased risk of cardiovascular disease, regardless of traditional risk factors. Those with previous breast or blood cancers were found to have the greatest risk, with significant changes in heart size and function detected on MRI scans.
Researchers develop a new technique to measure blood attenuation using a fluorophore-coated guidewire, improving the accuracy of near-infrared fluorescence in cardiovascular imaging. The method provides accurate information on vessel walls and outperforms existing correction methods.
A new study published in Nature finds that artificial intelligence (AI) surpasses human sonographers in accurately assessing cardiac function from echocardiogram studies. The research, conducted at the Smidt Heart Institute, demonstrates AI's potential to improve the quality and effectiveness of heart evaluations.
A recent study suggests that cardiac sphericity, or the roundness of the heart, may be a useful indicator for diagnosing cardiovascular conditions. The research used machine learning to analyze medical images and found a link between increased sphericity and future heart troubles.
Researchers from the Smidt Heart Institute found that individuals with spherical hearts are 31% more likely to develop atrial fibrillation and 24% more likely to develop cardiomyopathy. The study identified four genes associated with cardiomyopathy and a greater risk of developing atrial fibrillation.
A recent MRI study by the CNIC has established reference values for anatomical and functional parameters in adolescents' hearts, providing a crucial resource for clinical practice. The study involved 123 adolescents and aimed to fill the knowledge gap on 'normal' cardiac parameter values in this age group.
Researchers found that patients with greater buildup of fatty plaque deposits in the heart's three largest blood vessels had higher chances of developing serious health issues following surgery. This study suggests using existing chest scans to estimate patients' risk of heart attack or death during major surgeries.
A 20-year study reveals that recent advances in surgical and clinical care have significantly reduced brain injuries in babies with congenital heart disease. Infants who received higher postoperative blood pressure had a 20% lower risk of brain injury compared to those in earlier stages.
Researchers validate non-invasive ECGi technique to detect atrial fibrillation, providing detailed information about the electrical activity of the heart. This breakthrough reduces patients' exposure to ionising radiation and costs, making it more universal for clinical practice.
A cohort study of over 600 persons with non-MRI-conditional implantable cardioverter defibrillators found that these devices continue to appropriately treat detected tachyarrhythmias after MRI scans. The findings suggest that patients with non-MRI-conditional ICDs can safely undergo MRI exams without compromising device function.
Engineers and physicians developed a portable, postage-stamp-sized wearable ultrasound device for cardiac imaging. The device measures blood pumping activity in real-time, even during exercise, providing continuous insights into heart health.
Researchers discovered that female and male mouse hearts react uniformly at first to noradrenaline but exhibit differences in recovery time, affecting electrical activity. These findings may contribute to arrhythmia susceptibility between men and women, offering new insights into sex-based responses to stress hormones.
Researchers have developed a novel portable and low-cost macroscopic mapping system for all-optical cardiac electrophysiology using optogenetics and machine vision cameras. The system can stimulate and image engineered networks of human heart cells, providing insights into cardiac wave function and stability.
A Cedars-Sinai study found that even subtle forms of liver disease directly impact heart health, with elevated FIB-4 scores associated with abnormalities in heart function and vascular dimension. Cardiac MRI scans revealed that nearly 86% of patients had at least one heart abnormality.
A new study from Mount Sinai Hospital finds a strong association between age-related macular degeneration and severe forms of heart disease, including heart failure, heart attacks, and stroke. The study highlights the importance of increased screening for eye disorders to diagnose undetected heart disease.
Interdisciplinary researchers at the Beckman Institute have received a four-year, $2M award from the National Institutes of Health to develop a device that can instantly enable real-time 3D ultrasound imaging. The device, named FASTER, is designed to improve high-quality medical imaging accessibility in diverse communities.
Researchers developed an AI algorithm to assess retinal vasculature, predicting cardiovascular disease and death. The model captured half to two-thirds of circulatory disease deaths in those most at risk, outperforming traditional risk frameworks.
A large retrospective study found that visceral fat area from fully automated and normalized abdominal CT analysis predicts subsequent myocardial infarction or stroke in Black and White patients. The study suggests that body composition analysis using machine learning could be widely adopted to add prognostic utility to clinical practice.
Researchers found a 20% decrease in coronary artery dilation and reduced myocardial flow reserve in patients with prior COVID-19 infection. This may lead to poor prognosis and higher risk of adverse cardiovascular events.
The new ultrasound sticker uses a stretchy adhesive layer and rigid array of transducers to produce higher resolution images over a longer duration. It has potential applications in clinical diagnosis and could be made into wearable imaging products that patients can take home or buy at a pharmacy.
A study published in the European Heart Journal found that making small behavioral changes can significantly reduce cardiovascular risk. Participants who received a lifestyle intervention showed improvements in physical activity, diet, and sedentary time, leading to decreased blood pressure and cholesterol levels.
A Spanish study combines genetic and imaging data to predict patient prognosis, identifying those at risk of malignant arrhythmias or severe complications. The findings open the way for personalized medicine in treating dilated cardiomyopathy.
Researchers developed an AI method to automatically detect plaque erosion in heart arteries using OCT images. The new technique uses neural networks and post-processing algorithms to predict regions of possible plaque erosion and refine the initial prediction based on clinically interpretable features.
A new PET imaging agent, <sup>68</sup> Ga-FAPI-46, has been shown to predict the severity of cardiac remodeling after a heart attack by identifying active fibrosis. This biomarker has potential to aid in diagnosis and treatment selection for patients with heart failure.
A new SPECT imaging system performs scans 10-100 times faster than current systems, offering better image quality and increased patient throughput. The self-collimation concept improves traditional SPECT imaging by reducing scan time and radiation exposure.
A Mayo Clinic study found that nearly one-quarter of over 24,000 patients had mitral annulus calcification, a chronic degeneration of tissue at the base of the heart's mitral valve. This condition is associated with higher mortality rates and increased risk of cardiovascular disease.
The Nurses and Allied Professionals community is being recognized for their dedication and skills in advancing cardiovascular care. The Andreas Grüntzig Ethica Award celebrates their expertise, physical presence, and impact on patient care.
The American Journal of Roentgenology has published best practices for managing an iodinated contrast media (ICM) shortage in radiology practices. To mitigate the shortage, practice leaders should prioritize examination findings and reduce overall ICM usage.
The TVT 2022 program features cutting-edge research on transcatheter aortic valve replacement (TAVR) and other structural heart therapies. The meeting will focus on patient evaluation, imaging modalities, and therapeutic options.
Researchers at the University of Missouri-Columbia have developed a novel approach to reprogramming cardiac implantable devices during MRI scans remotely. This technology has shown safe and effective results, saving time and money by eliminating the need for device representatives or on-site personnel.
Researchers have gained unprecedented insights into the heart's dynamic ultrastructure using high-resolution electron microscopy. This knowledge is crucial for developing new therapeutic concepts for heart attacks and cardiac arrhythmias.
The study found a twofold regression of coronary atherosclerosis and stabilization of high-risk plaques in patients who received alirocumab, compared to those who received a placebo. Patients treated with alirocumab also needed significantly fewer repeat stenting procedures.
A study identifies new biomarkers that predict the presence of subclinical atherosclerosis, providing a non-invasive way to detect cardiovascular disease. The research team analyzed blood plasma samples and validated three proteins as biomarkers, improving the prediction of cardiovascular risk.
Researchers at CNIC discover that bone marrow activation is an early event in the development of atherosclerosis, leading to inflammation and plaque formation. The study identifies metabolic syndrome as a key trigger for this process.
A new 3D matrix ultrasound method has been developed to assess cardiovascular risk in healthy individuals, offering a reliable and accurate alternative to traditional methods. The technique shows promise for personalized prevention and treatment strategies by detecting and quantifying an individual's accumulated cardiovascular damage.
Researchers have made a significant breakthrough in predicting heart attacks and strokes by developing a non-invasive method using super-resolution ultrasound imaging. The technology aims to detect high-risk atherosclerotic plaques that are prone to rupture, allowing doctors to prescribe life-saving interventions.
The American Roentgen Ray Society has awarded two 2022 ARRS Scholarships to Sean Woolen and Bradley Allen, providing a total of $180,000 in funding for their radiological research projects. The scholarships aim to advance emerging scholars and prepare them for leadership positions.
Researchers analyzed data from over 35,000 adults who had no history of stroke or dementia. Those with optimal cardiovascular health showed a 2.4% higher brain volume, equivalent to a 7-year younger brain. Good blood pressure control and healthy blood sugar levels also contributed to healthier brain imaging measures.
A prospective observational study found that preoperative shear wave elastography (SWE) can predict successful rotator cuff repair. SWE-derived elasticity was higher in patients with insufficient repair, and the elasticity ratio independently predicted insufficient repair.
Researchers from King's College London discovered how obesity affects the heart's shape and structure in children, leading to potential future cardiovascular risks. The study used data from over 2,600 children aged 10, showing significant changes at a BMI of 19.
Researchers from Göttingen University and Hannover Medical School have detected changes in heart muscle tissue of people who died from Covid-19. The study used innovative X-ray imaging to visualize the affected tissue in three dimensions, revealing a network of chaotic vessel formations.
A recent study published in the Journal of the American College of Cardiology found that fetal MRI can detect at least one other abnormality in almost 57% of fetuses with heart defects. Additionally, approximately a quarter of all fetuses had structural brain abnormalities, regardless of the severity of the heart defect.
A new contrast agent has been developed to detect and image blood clots noninvasively, using a targeted approach to find clots anywhere in the body. The agent was tested in patients with atrial fibrillation and showed promising results.
A recent study published in the American Journal of Roentgenology found a link between COVID-19 mRNA vaccination and myocarditis in adolescent males. Cardiac MRI was used to assess suspected myocarditis post-vaccination, with late gadolinium enhancement persisting in two patients undergoing repeat MRI.
A new AI-based computer algorithm created by Mount Sinai researchers can identify subtle changes in electrocardiograms to predict heart failure. The algorithm was 94% accurate at predicting healthy ejection fractions and 87% accurate at detecting weakened hearts, offering a promising alternative to traditional diagnosis methods.
A new AI technology enhances magnetic resonance imaging (MRI) images to capture scar tissue in the heart, eliminating the need for contrast injections. The approach, called Virtual Native Enhancement (VNE), produces higher-quality images and better captures evidence of scar without contrast.
Researchers developed a deep learning network using data from over 20,000 patients to predict annualized risk for heart attack or death. The network identified regions of the heart associated with high-risk patients and provided rapid risk scores.