Articles tagged with Magnetic Resonance Imaging
Researchers developed a non-invasive way to assess fat composition around the heart using magnetic resonance imaging. This technique may help doctors identify patients at greatest risk for cardiac problems and predict treatment outcomes.
Researchers at Karolinska Institutet used AI to analyze brain images from 70-year-olds and found that factors like inflammation and high glucose levels are associated with an older-looking brain. A healthy lifestyle, on the other hand, was linked to brains with a younger appearance.
A study by Charité – Universitätsmedizin Berlin found that an MRI-first approach to detecting prostate cancer is safe and reliable, with normal MRI findings indicating a low risk of aggressive cancer. The strategy involves regular urological checks instead of biopsies for patients without suspicious findings.
A new blood-based biomarker, placental growth factor (PlGF), has been identified as a potential tool for detecting early brain changes associated with cognitive impairment and dementia. Elevated PlGF levels were found to be linked to increased vascular permeability, leading to white matter injury and subsequent cognitive decline.
A phase 2 study conducted by Mayo Clinic found that 56% of participants were alive after 12 months, with a median overall survival of 13.1 months. The treatment, which combines short-course hypofractionated proton beam therapy with advanced imaging techniques, was more effective in patients over 65 with favorable tumor genetics.
A recent study used NMR methods to investigate rare 300-century wooden structures from the Roman Empire, shedding light on their history and behavior in water. The analysis revealed valuable insights into the structure and changes of archaeological wood remains, contributing to the preservation of heritage for future generations.
A new study detects pre-malignant pancreatic lesions using Diffusion Tensor Imaging (DTI), a form of MRI, which could enable early diagnosis and effective therapies. The detection was successful in both transgenic mice and human samples, opening the way to non-invasive diagnostic tools for PanINs.
Artificial intelligence is enhancing breast cancer risk prediction through mammographic analysis, uncovering key features that predict breast cancer risk. These AI-generated features may inform personalized screening strategies, such as more frequent or less frequent screenings for women at high or low risk of breast cancer.
A new portable MRI machine, augmented with machine learning tools, matches conventional MRI in measuring brain characteristics relevant to Alzheimer's disease. The study has the potential to expand neuroimaging in settings with limited MRI access and streamline care for AD patients.
Researchers used MRI to investigate how a gluten-free diet affects people with coeliac disease, finding improved gut symptoms but persistent issues. The study also identified changes in the gut microbiome, suggesting potential prebiotic treatments.
A new MRI-based imaging technique can rapidly assess ovarian cancer subtypes and their response to treatment, allowing for personalized treatment planning. The technique, called hyperpolarised carbon-13 imaging, distinguishes between two different subtypes of ovarian cancer and reveals their sensitivities to treatment.
A Baycrest study has found that high blood sugar may impair brain health even in people without diabetes. Researchers analyzed data from 146 healthy adults and found a correlation between high blood sugar levels and lower brain activity.
This editorial introduces persistence landscapes as a mathematical method to identify and correct biases in medical imaging. Persistence landscapes offer a way to reduce random noise while preserving important details, making it easier for clinicians to focus on meaningful image parts.
A new study in Nature identifies strategies for tying brain function and structure to behavior and health, improving the reliability of brain-wide association studies. By strategically selecting participants and collecting multiple scans, researchers can obtain more dependable results with fewer participants.
Researchers found lower pulmonary gas exchange may be associated with impaired cognitive function in patients with long COVID. The study also showed a potential treatment strategy using methods that target improved gas exchange, suggesting a causative relationship between cognitive dysfunction and lung dysfunction.
Scientists at IOCB Prague have developed a new compound that securely binds metal elements, known as lanthanides, inside molecules of medical drugs. This breakthrough discovery, called 'ClickZip', improves diagnostics and accelerates drug development by making pharmaceuticals more stable.
Researchers introduce a new tool called 'persistence images' that uncovers hidden biases in medical imaging data, advancing fairness in healthcare AI. The technology helps detect bias, filter out noise, and improve overall accuracy, leading to more reliable diagnoses and better patient outcomes.
Researchers at the University of Rochester Medical Center have discovered a potential biomarker for psychosis diagnosis by analyzing brain connectivity patterns. The 'somato-visual' biomarker shows promise in predicting psychosis onset and stratifying patients into clinically meaningful subgroups.
Researchers explore innovative approaches to enhance imaging performance using metasurfaces, offering improved resolution, sharper images, and more accurate diagnostics. This technology has the potential to transform medical diagnostics and scientific discovery by overcoming limitations of conventional optical components.
Researchers have trained AI models to distinguish brain tumors from healthy tissue using convolutional neural networks and transfer learning. The models achieved an average accuracy of 85.99% at detecting brain cancer, with the ability to generate images showing specific areas in its tumor-positive or negative classification.
A new approach using topological data analysis (TDA) enhances the reliability and reduces bias in AI systems used for medical diagnosis in radiology. TDA captures intricate features and provides a holistic view of medical images, leading to more accurate diagnoses and equitable patient care.
Patients receiving MRI-guided SBRT experienced significantly fewer urinary and bowel side effects compared to CT-guided treatment. MRI guidance also correlated with improved scores on specific quality-of-life measures, including bowel function and sexual health.
A Chinese Medical Journal study reveals that patients with prostate cancer can undergo surgical removal without a pre-operative biopsy, using a combination of mpMRI and PSMA PET/CT imaging. This approach reduces costs and complications associated with traditional biopsy methods.
Researchers developed an AI-powered model called FastGlioma that can detect residual tumor tissue with high accuracy in 10 seconds. The technology outperformed conventional methods, reducing the risk of missed tumors by nearly 75%. This innovation could change the field of neurosurgery and minimize reliance on radiographic imaging.
A new PACT system offers rapid imaging of living organisms, enabling the tracking of whole-body dynamics and disease progression. The system achieves spatial resolution of approximately 212 micrometers and enables the visualization of oxygen saturation across complex biological systems.
Researchers at Radboud University Medical Center found that an extra year of education does not protect against brain aging and has no effect on brain structure. Despite positive correlations between education and cognitive benefits, the study suggests caution in assigning causation when only correlation is observed.
Researchers found that improved blood sugar control significantly impacts brain health, slowing down age-related brain atrophy by up to 50%. The Green Mediterranean Diet, rich in polyphenols, shows promise in supporting metabolic and brain health.
The new center will advance multiple areas of active research on campus, including neurocognitive sciences and musculo-skeletal health. With support from across campus, UTA aims to improve research capabilities to enhance undergraduate and graduate educational opportunities.
Researchers developed an AI model that can identify and measure aggressive prostate cancer lesions with high accuracy. The model's estimates of tumor size were associated with the likelihood of cancer recurrence or metastasis.
Radiologists who had access to questionnaire information during MRI interpretation achieved a near statistically perfect agreement with spine specialists. This improved diagnostic accuracy and confidence, avoiding diagnostic discrepancies between radiologists and spine specialists.
Researchers develop transcranial ultrasound stimulation (TUS) as a non-invasive therapy for brain-related issues, with potential for personalized treatments. A 'search and rescue tool' for the brain, TUS enables precise targeting of specific areas before treatment.
A novel collaborative framework integrates semi-supervised learning techniques to improve MRI segmentation accuracy, even with limited labeled data. The approach achieves high Dice scores and demonstrates its potential for practical clinical application.
A comprehensive evidence review on tethered spinal cord found that while surgery can benefit symptomatic patients, data for asymptomatic patients is lacking. The study also highlights the need for more research into conservative management and potential risks of surgical complications.
A new study suggests that MRI can predict patient outcomes and the risk of tumor reccurrence or spread for patients with rectal cancer who have undergone chemotherapy and radiation. This information could help doctors determine the best course of treatment, including whether to spare patients from invasive surgery.
A new image processing strategy for cardiac magnetic resonance imaging identifies areas responsible for complex ventricular tachycardias, enabling preoperative planning and reducing procedure times and complications. The systematic approach eliminates operator bias and increases sensitivity for detecting these regions.
Damage to the brainstem, the brain's control centre, is behind long-lasting physical and psychiatric effects of severe Covid-19 infection. Researchers used ultra-high-resolution scanners to observe the damaging effects of Covid-19 on the brain, finding inflammation in key regions associated with breathlessness, fatigue and anxiety.
A new study has definitively revealed the presence of an efficient waste-clearance system within the human brain, showing that cerebrospinal fluid flows through specific pathways to clear metabolic wastes generated by brain energy. Lifestyle measures and medications can maintain and enhance this system.
A new non-invasive imaging technique has been shown to accurately detect clear-cell renal cell carcinoma, the most common form of kidney cancer. The technique uses a monoclonal antibody drug that targets the protein CA9, highly expressed in up to 95% of clear cell kidney cancers.
A study by Osaka Metropolitan University found that ChatGPT's diagnostic performance for brain tumors was comparable to that of neuroradiologists, with an accuracy rate of 73%. The model's performance varied depending on the type of clinical report written, with higher accuracy when using reports from neuroradiologist writers.
Researchers at TU Graz have developed a new machine learning method that generates precise live MRI images of the beating heart using only a few MRI measurement data. This breakthrough enables faster and cheaper MRI applications, including quantitative MRI for diagnoses.
A new hand-held scanner can generate highly detailed 3D images in seconds, paving the way for earlier disease diagnosis. The technology uses laser-generated ultrasound waves to visualize subtle changes in blood vessels, helping inform patient care and diagnose conditions like cancer and cardiovascular disease.
A new study by Sylvester Comprehensive Cancer Center researchers shows that daily MRI imaging paired with radiation can monitor tumor changes in real-time. The technology has the potential to signal early warning signs of tumor growth, allowing for faster and more targeted treatment adaptations.
UCLA investigators presented data on chemoradiotherapy in rectal cancer, MRI-guided radiotherapy for prostate cancer, and symptom self-reporting during treatment. Researchers developed a predictive model to identify patients most likely to respond to chemoradiotherapy in rectal cancer.
Researchers have developed a new NMR platform using chemical exchange saturation transfer (CEST) MRI to visualize metabolite dynamics in living plants. This breakthrough enables noninvasive monitoring of sugar and amino acid distribution, improving crop improvement through breeding research.
A new study reveals how psilocybin alters brain connectivity to alleviate symptoms of body dysmorphic disorder, potentially aiding treatment. Psilocybin strengthens neural connections between executive functions and emotionally salient stimuli, leading to improved BDD symptoms.
A new study by the University of Minnesota found that developers of portable magnetic resonance imaging (MRI) systems failed to address ethical, legal and social issues as they designed and deployed the technology. The authors recommend that researchers, engineers and companies work with ethics and legal experts to formulate guidelines.
Researchers have successfully visualized and tracked specific cells in deep brain tissue, including along the corpus callosum's nerve fibre highway. This advancement could potentially lead to better diagnostic tools for glioblastoma, a deadly brain cancer.
A new study reveals a significant correlation between entorhinal cortex thickness and financial exploitation vulnerability, a potential early indicator of Alzheimer's disease. The research suggests that assessing financial awareness could help identify cognitive changes in older adults.
The study compares nerve fiber orientation captured with specialized MRI and OCT approaches, laying groundwork for combining these imaging techniques. The findings show strong potential for PS-OCT to validate dMRI data, providing valuable insights about the microstructural organization of nerve fibers.
Researchers at Boston University created an AI tool that can determine the cause of dementia using commonly collected patient data, boosting doctor accuracy by 26%. The algorithm identifies 10 types of dementia, including vascular and frontotemporal dementia, to help doctors manage patients more effectively.
Researchers at Boston University have developed low-cost, high-impact metamaterials solutions to improve MRI technology, enabling clearer imaging in low-resource areas. Wearable and deployable devices can be tailored to specific body parts, boosting signal-to-noise ratio and reducing scanning time.
A new study published in the Stroke journal found that people with brain aneurysms are at higher risk of developing mental health conditions, including anxiety. The study, which analyzed data from over 85,000 people, found that younger adults were particularly vulnerable to this increased risk.
A study of over 900 children with autism spectrum disorder found that brain overgrowth is associated with increased social and communication symptoms. The research used MRI brain images and mini-brain experiments to show that enlarged brains are linked to altered Ndel1 enzyme activity, potentially affecting brain development.
A new heart MRI technique accurately estimates pressures inside the heart to predict heart failure risk in a general population. Key risk factors identified include age over 70, high blood pressure, obesity, alcohol consumption, and male gender.
A new $3.5 million NIH grant will investigate the complex interplay between traumatic brain injury and genetic risk factors in the development of Alzheimer's disease. The three-year study will use rodents to assess disease progression across different age periods, providing insights into potential early intervention strategies.
A new study suggests that MRI scans can help doctors identify patients with more aggressive prostate cancer, allowing for earlier treatment or active surveillance. The research found that suspicious lesions on an MRI test were associated with a higher risk of advanced disease in five years.
A new deep learning model detects clinically significant prostate cancer on MRI with performance comparable to experienced abdominal radiologists. The model's prediction can be used as an adjunct to improve diagnostic performance and reduce false positives.
A new hybrid contrast agent has been developed to combine the benefits of MRI and PET imaging techniques, offering improved accuracy and opening new diagnostic applications. The agent has shown potential in detecting kidney problems and other conditions, paving the way for personalized diagnostics and precise imaging.
Researchers have developed an AI-based system that can predict the risk of prostate cancer more accurately than traditional methods. The new tool combines MRI images and deep learning to identify low-risk patients who may not need a biopsy, potentially sparing them from unnecessary procedures and reducing complications.
A clinical trial found that fish oil supplements slowed neuronal integrity breakdown in older adults with the APOE4 gene variant, a risk factor for Alzheimer's disease. The study showed no benefit for all older adults, but suggested omega-3 fatty acids may be useful for prevention.