Articles tagged with Magnetic Resonance Imaging
Researchers at USC have developed a groundbreaking brain imaging technique that reveals how tiny blood vessels in the brain pulse with each heartbeat, which may hold clues to aging and diseases like Alzheimer's. The method shows that microvascular pulsatility increases with age, especially in deep white matter, a region critical for co...
Researchers at Linköping University used magnetic cameras to examine blood flow in an artificial heart in real-time, revealing a pulsing pattern similar to that of a healthy heart. The study aims to design the heart to minimize complications such as blood clots and red blood cells breakdown.
Researchers found that bullying activates social and emotional brain networks, as well as autonomic threat response systems, leading to increased risk of mental and somatic health issues. Viewers with previous bullying experiences show stronger neural responses to bullied individuals, highlighting the long-term effects of bullying.
Researchers developed a fully automated finite element analysis pipeline to transform spine diagnostics and personalized treatment planning. The new approach enables rapid, patient-specific simulations that support preoperative planning, spinal implant optimization, and early detection of degenerative spine conditions.
Researchers used quantitative susceptibility mapping MRI to detect changes in brain tissue linked to iron levels, predicting mild cognitive impairment and later Alzheimer's disease. The study showed that higher iron levels in specific brain areas could spot early changes years before symptoms appeared.
A new study published in JAMA finds biparametric magnetic resonance imaging (MRI) to be more efficient than multiparametric MRI for prostate cancer diagnosis. By adopting biparametric MRI, the global healthcare system could see a substantial increase in scanner throughput and cost reduction.
Researchers developed a new method to correct for variations in brain imaging measurements, reducing bias and increasing the accuracy of studies on ADHD. The traveling-subject method demonstrated reduced measurement bias while maintaining sampling bias, revealing decreased brain volume in critical regions for cognitive functions.
A recent study published in Radiology found that AI-assisted mammography catches most advanced breast cancers, but still misses 14% of invasive cases. The AI missed more cases in younger women with tumors 2 cm or smaller, and those with low histologic grade, fewer lymph node metastases, and non-glandular locations.
A new AI-assisted model combines MRI, biochemical, and clinical information to predict worsening knee osteoarthritis with high accuracy. The model showed improved accuracy in predicting worsening pain and joint space narrowing, suggesting its potential to enhance care.
The researchers developed a novel approach to virtual contrast enhancement in MRI imaging, using pixelwise gradient methods with Generative Adversarial Networks. The model excelled in capturing intricate details and textures, outperforming its predecessor in texture representation.
Researchers developed an alginate-based microrobot that can be tracked using Magnetic Particle Imaging (MPI) and performs real-time localization, selective thermal therapy, and cell delivery. The robot is powered by a single magnetic actuation system independent of conventional medical imaging devices.
A new study suggests that subtly adjusting the angle of the foot during walking can reduce knee pain caused by osteoarthritis and slow its progression. By tailoring each patient's foot angle to their unique walking pattern, experts believe an easy and fairly inexpensive way to address early-stage osteoarthritis may be found.
Researchers apply quantum mechanics to denoise medical images by separating localized signal from diffused noise. The method leverages physics-driven principles to automatically separate components of pixels in an image.
Researchers found that the primary somatosensory cortex, responsible for processing sensory information, has a layered structure that ages differently. The middle and upper layers remain stable or even thicken with age, while the lower layers show age-related degeneration, providing evidence for neuroplasticity.
Silvia Blemker, a renowned biomedical engineer, has been elected to lead the American Society of Biomechanics. She aims to bolster industry ties, expand funding for students and early-career researchers, and promote interdisciplinary collaboration.
Researchers from the National Institute of Physiological Sciences evaluated the impact of denoising algorithms on dMRI data for detecting tissue abnormalities in glaucoma. They found that denoising increased signal-to-noise ratio and altered image appearance, but had limited effect on disease-related changes.
Researchers aim to uncover how menopause and lifestyle factors shape brain aging in women during midlife. The three-year project will analyze MRI scans and health data from thousands of women worldwide to track changes in brain structure and connectivity.
Researchers found that external cues alleviated pain for all participants but only half reported less pain with placebo treatment. Predictive cues were less impactful when patients received placebo treatment. The study suggests cue-based expectations have more consistent effects than treatment-based expectations.
Researchers used AI model ChatGPT-4 to extract clinical variables from MRI and CT scans of nearly 1,000 adults with pancreatic cysts. The accuracy rate ranged from 97% for solid components to 99% for calcific lesions, comparable to human performance.
A new computational method combines 4D flow MRI, CFD, and data assimilation to estimate blood flow in brain aneurysms with greater accuracy and efficiency. The approach focuses on the aneurysm region, reducing computational cost while improving flow estimation.
Researchers at the University of Illinois Urbana-Champaign have developed a new non-invasive MRI approach that visualizes brain metabolism and detects metabolic alterations associated with brain diseases. The technique uses magnetic resonance spectroscopic imaging to provide insights into brain function and disease processes.
A cardiac magnetic resonance imaging (MRI) scan usually takes anywhere from 30 to 90 minutes. The AI-assisted model developed by Mizzou researchers can turn low-quality MRI heart scans into high-quality images in less time, while improving patient experience and reducing costs.
Researchers developed a simpler way to identify patients with suspected cardiac sarcoidosis at increased risk of sudden cardiac death. CMR phenotyping can help determine which patients would benefit from an implantable cardioverter-defibrillator for primary prevention, improving decision-making in clinical practice.
The study reveals that white matter microstructure in infants' brains between 3-9 months predicts their emotional development. Infants with certain brain patterns are more likely to exhibit negative emotions or improved self-soothing abilities.
Researchers use MRI and NASA-inspired negative-pressure pants to improve stress tests, revealing hidden heart issues. The technology transforms heart imaging, making it possible to detect real differences in heart performance.
Emerging imaging technologies like Tomosynthesis, Contrast-Enhanced Spectral Mammography, and Molecular Breast Imaging improve detection of high-risk populations and dense breast tissue. AI Integration, Noninvasive Biomarkers, and Hybrid Techniques hold promise for reducing radiation risks and overdiagnosis.
Weizmann Institute researchers developed a nano-MRI device with a resolution of one nanometer, allowing for the imaging of individual molecules. This technology paves the way for high-resolution molecular imaging in materials and pharmaceutical industries.
A new framework for assessing traumatic brain injuries (TBI) will provide more accurate diagnoses and treatments, leading to better patient outcomes. The framework incorporates clinical symptoms, biomarkers, imaging scans, and modifiers to determine the severity of injury and predict recovery.
A new USC-led study found a significant link between type 2 diabetes and cortical thickness in older adults from various populations. The researchers discovered that individuals with T2DM exhibited thinner cortex, particularly in temporal and parietal regions critical for memory and cognitive function.
Researchers found that MRI scans can detect heart inflammation, scarring, and impaired function in carriers of a mutated LMNA gene. This information can help clinicians predict which patients are at higher risk and inform decisions about treatments such as defibrillators or transplants.
A new brain atlas developed by researchers at Duke University will increase precision in measuring changes in brain structure, making it easier to share results. The tool, the Duke Mouse Brain Atlas, provides a detailed map of the entire mouse brain, from large structures down to individual cells and circuits.
A new AI model developed by Uppsala University accurately diagnoses multiple sclerosis (MS) with an overall accuracy of 90%, identifying the transition from relapsing-remitting to secondary progressive MS in almost 87% of cases. This enables earlier diagnosis, reducing the risk of patients receiving ineffective medicines.
New research suggests that patients' muscle quality before hip replacement surgery may predict their risk of poor recovery. Patients with poor muscle quality were more likely to perform poorly on movement tasks after surgery, compared to those with good muscle quality.
Researchers have found that puberty triggers significant changes in brain connectivity patterns in individuals with a rare genetic disorder tied to autism. The study suggests that synaptic dysfunction during development may contribute to the condition's behavioral challenges.
A new study from Boston University School of Medicine found that X-rays can predict common low back pain problems in approximately 75% of cases. In these instances, X-rays may be a preferred initial imaging study, reducing the need for MRI scans and associated costs.
Researchers found larger falcine sinus diameters associated with higher risks of developmental delays, neurological issues and mortality in infants born with VOGM. Fetal MRI can help predict short- and intermediate-term outcomes, enabling early intervention and better care for high-risk patients.
A new editorial in Oncotarget discusses how artificial intelligence can improve liver imaging by recognizing when it might be wrong. The approach, called 'uncertainty quantification,' helps clinicians better detect liver cancer and other diseases by pointing out areas in medical scans that need a second look.
A new AI tool called MindGlide can extract key information from brain images to measure damaged areas and highlight subtle changes in MS patients. The tool performed better than other AI tools and expert clinical analysis, enabling researchers to unlock valuable insights into multiple sclerosis.
An 11-year-old Asian small-clawed otter developed left-sided paralysis after a fall, but improved with treatment for a suspected fibrocartilaginous embolus. Follow-up MRI showed a diminished lesion one year later.
Researchers found that medical imaging experts can solve common optical illusions, including judging the size of objects. Training to improve visual perception can also make experts less susceptible to these illusions. This study has implications for training medical image analysts.
Dr. Christopher Kramer began a one-year term as head of the American College of Cardiology, addressing workforce issues, health equity and AI-driven solutions to improve cardiovascular care. With over 35 years of membership and leadership roles, Kramer brings experience in cardiovascular magnetic resonance imaging.
A new study found significant disparities in the use of MRI to detect prostate cancer, with Black patients and those in rural areas having lower rates of diagnostic testing. The study's findings highlight the need for enhanced access to MRI and improved prostate cancer outcomes.
Researchers found significant differences in brain connectivity between children with autism and typically developing children, particularly in the left hemisphere. The study identified specific white matter tracts linked to core ASD symptoms, providing new insights into how structural differences relate to behavior.
A team of researchers has identified a common brain network that generalized seizures hijack, which is located in the region where deep brain stimulation (DBS) electrodes are placed. This finding could help explain why DBS is effective in alleviating generalized seizures and potentially improve treatment outcomes.
A new study has shown that high-resolution ultrasound can diagnose prostate cancer as effectively as MRI, with improved resolution and lower costs. The technology, called micro-ultrasound, is expected to speed up diagnosis, reduce hospital visits, and make imaging more accessible, particularly in less developed healthcare systems.
A new MRI technique has been successfully used to treat adults with drug-resistant epilepsy, allowing doctors to offer life-changing surgery to patients. The parallel transmit 7T scanner identified previously unseen structural lesions in nine patients, confirming the effectiveness of the treatment option.
Researchers developed an automated MRI processing and machine learning software to diagnose Parkinson’s disease, reducing diagnostic time by up to 96%. The software uses diffusion-weighted MRI and a noninvasive biomarker technique to identify neurodegeneration in the brain, providing more precise diagnoses.
Researchers created a powerful new computational and artificial intelligence tool that can generate high-resolution 3D maps of the brain in mice, allowing users to zoom in and out and peer into the full set of molecules producing energy for brain functions. This breakthrough brings scientists closer to understanding the role of metabol...
Researchers developed an AI tool called Unfold AI to accurately estimate prostate tumor volume and identify patients likely to benefit from partial gland cryoablation. This approach shows promise in reducing treatment failures by over 70% and improving patient outcomes.
Researchers identify how a balance of innate structure and flexible learning produces our remarkably organized visual brains. They found that regions in the ventral temporal cortex have distinct cellular organization and white matter connections from birth.
A POSTECH research team developed a photoacoustic computed tomography (PACT) system that non-invasively monitors cerebrovascular changes in small animals with early stages of an ischemic stroke. The technology also measures oxygen saturation in blood vessels, allowing precise tracking of vascular recovery after stroke.
Researchers are enrolling volunteers for a four-year study that will use advanced imaging, genetics, exercise science, neuroscience, and remote monitoring to investigate age-related health decline. The goal is to help individuals and healthcare practitioners better prevent the impact of disease on older adults.
A new federal mandate aims to improve patient awareness about breast density, which affects cancer detection and risk. Women with dense breasts may need supplemental screening, such as MRI, to detect breast cancer earlier, but this comes with potential downsides.
A unique case study reveals an unexpected discrepancy between Alzheimer's pathology and cognitive function in a woman with Down syndrome. The study highlights the need to expand inclusion criteria for therapeutic drug trials and uncover genetic or lifestyle factors that contribute to cognitive preservation.
A recent study found that a brief consumption of highly processed foods can alter the brain's sensitivity to insulin in healthy individuals, potentially leading to obesity and type 2 diabetes. This effect was observed even after returning to a balanced diet for one week.
A new AI-based system called LILAC can accurately detect changes and predict outcomes in various medical applications. The system has been demonstrated on diverse longitudinal image series covering IVF embryos, healing tissue after wounds, and aging brains.
Researchers at the University of Houston have developed a new technology that uses photon counting detectors to capture X-ray images with multiple energy levels simultaneously. This allows for more precise 3D visualization of different tissues and contrast agents, which can improve cancer detection and other medical applications.
Researchers at TUM developed a new microscopy technique combining magnetic resonance spectroscopy with fluorescence microscopy, enabling high-resolution imaging of individual cells and structures down to the microscopic level. The technique has potential applications in cancer research, pharmaceuticals, and materials science.
A new study uses advanced lung MRI to detect regional blood flow abnormalities in children and adolescents with long COVID, which may explain persistent symptoms. The researchers found reduced blood flow patterns that correlated with fatigue symptom severity, suggesting a possible biological basis for ongoing symptoms.
UTA research projects contributed $59 million to the national economy in 2024, supporting student development and collaboration with other research organizations. The university's research infrastructure, including cutting-edge equipment, helped drive economic impact in North Texas and beyond.