Research on MRI and what it can reveal. Covers restorative-sleep imaging, new MRI agents for cancer, prostate imaging, and dementia mapping.
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.
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.
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 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.
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 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.
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 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 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 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.
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.
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.
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.
A rare case of adenomyosis in an 81-year-old postmenopausal woman closely resembles invasive endometrial cancer, emphasizing the challenges of diagnosing this condition. Further studies are needed to refine diagnostic protocols and determine risk factors for postmenopausal patients.
Researchers developed a robust AI model that automates segmenting of MRI images, reducing radiologist workload and improving consistency. The TotalSegmentator MRI model achieved high performance on various anatomical structures, with a Dice score of 0.839.
Researchers at Tohoku University used MRI to directly observe metal-ion dissolution in lithium battery cathodes, detecting small amounts of manganese with high sensitivity. The technique identified an alternative electrolyte system that suppresses dissolution, promising improvements in battery performance.
People with musical anhedonia still derive pleasure from groovy tunes, and the urge to move appears to drive their experience of pleasure. Research found no differences in either pleasure or urge to move in anhedonics compared to controls, suggesting that the urge to move may itself generate pleasure.
A recent study published in JAMA Network Open found that heavy cannabis users exhibited reduced brain activity during working memory tasks, associated with worse performance. Abstaining from cannabis before cognitive tasks may help improve performance.
Researchers found AI-based imaging technology improves disease diagnosis accuracy, particularly in cardiology, oncology, neurology, and ophthalmology. The technology also enhances diagnostic efficiency and reduces healthcare disparities by delivering high-quality diagnostics to underserved areas.
A new trial has found that patients with suspected invasive bladder cancer treated with initial MRI imaging and biopsy are faster than those assessed with TURBT alone. The BladderPath trial showed a median time of 53 days from referral to correct treatment, compared to 98 days for usual care.
Researchers developed an AI model to detect brain cancer spread in surrounding tissue using MRI scans, showing 85-per-cent accuracy. This non-surgical method offers insights into patients' cancer without aggressive surgery, potentially improving treatment and survival.
A study published in the Journal of the American College of Cardiology found that people exposed to high aircraft noise levels had stiffer and thicker heart muscles, which contracted and expanded less easily. This was especially true for those exposed to higher noise at night, potentially due to impaired sleep and stress responses.
A new study found that exposure to high aircraft noise levels can lead to stiffer and thicker heart muscles, increasing the risk of poor heart function and major cardiac events. People exposed to night-time aircraft noise were particularly at risk, with increased risks of heart attacks, life-threatening rhythms, and strokes.
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 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 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 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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.