Research on MRI and what it can reveal. Covers restorative-sleep imaging, new MRI agents for cancer, prostate imaging, and dementia mapping.
A portable, low-field MRI device can be safely used at bedside to evaluate critically-ill patients for suspected stroke or traumatic brain injury. The device produced important neuroimaging findings in 29 of 30 patients and detected abnormal neurologic findings in eight of 20 patients with altered mental status.
Research reveals that Type 2 diabetes affects brain function in older women, leading to sensory and motor deficits. A unique fNIRS technique detects decreased oxygenated blood use in the brain, suggesting underlying mechanisms such as muscle changes and cortical dysfunction.
Researchers at the University of Tokyo have developed a machine learning algorithm that can distinguish between different psychiatric diagnoses, including autism spectrum disorder and schizophrenia. The algorithm uses MRI brain scans to identify variations in brain thickness, surface area, or volume.
The Journal of Medical Imaging and Radiation Sciences special issue shares stories about interpersonal skills beyond technical aspects to care for patients during medical imaging and radiation therapy procedures. Guest Editor Sue Robins curated this issue as a learning experience for technologists, therapists, and patients alike.
Researchers found that breast cancer diagnosis via diffusion-tensor imaging (DTI) was equivalent before and after gadolinium-based contrast agent administration. DTI parameters showed a statistically significant reduction in cancer lesions after contrast enhancement, leading to increased conspicuity for radiologists.
A group of Russian scientists, including ITMO University researchers, has proposed a system to update existing MRI scanners. The device uses electromagnetic coupling with an additional dielectric resonator to localize the magnetic field in the breast.
A new machine learning approach, federated learning, enables hospitals to share patient data securely, improving the accuracy of brain tumor diagnoses. This technique has been successfully tested in a Penn Medicine study, which showed that it can outperform centralized models in identifying brain tumors.
The study's lead researcher found that using a graphics processing unit (GPU) increased the speed of real-time tumor tracking by five times, improving accuracy over previous methods. This breakthrough could lead to safer and possibly fully automated radiation therapy in the future.
A new CSU study found that physical stress at work is linked to faster brain aging and poorer memory in older adults. Those who reported high levels of physical stress had smaller hippocampal volumes and performed poorly on memory tasks.
Physicists at Massachusetts General Hospital have identified superparamagnetic iron oxide nanoparticles as a potential contrast agent for low-field MRI scanners. The nanoparticles could enable the use of low-cost MRI technology in emergency rooms and doctors' offices for routine screenings, revolutionizing disease diagnosis and screening.
A UCalgary research study found that magnetic resonance imaging (MRI) can detect risk of heart failure and death in those with dilated cardiomyopathy. The study confirms about 40% of patients with DCM have scarring patterns on their heart muscle, associated with higher risk of future cardiac events.
A new MED-EL Synchrony cochlear implant design allows children to undergo MRI scans safely and comfortably, reducing the need for sedation or anesthesia. The innovative device eliminates the need for surgical removal of the magnet or a head wrap, increasing accessibility to critical diagnostic tools.
A new study suggests that early initiation of annual breast cancer screening with MRI and mammography may reduce breast cancer mortality by half or more in female childhood cancer survivors previously exposed to chest radiation. The findings highlight the importance of MRI in reducing deaths from breast cancer in this population.
A recent study published in Radiology found that prostate MRI quality is highly variable across institutions, with a significant impact on cancer detection and treatment outcomes. The study's findings suggest that improved standardization and training are needed to ensure consistent imaging results and better patient care.
Researchers found higher brain iron levels associated with cognitive deterioration in Alzheimer's disease, suggesting a potential role for iron chelators in treatment. Iron deposition was linked to amyloid beta and neurofibrillary tangles, disruptors of cell function.
A new study suggests that a type of MRI scan used for heart disease can also pick out aggressive cancers in children. The T1-mapping technique measures how water molecules interact inside cells, allowing clinicians to understand the cellular make-up of tissue and spot early signs of treatment effectiveness.
Researchers developed a new quantum sensing technique that allows high-resolution NMR spectroscopy on small molecules in dilute solution, achieving femtomole molecular sensitivity. This breakthrough enables chemical analysis and magnetic resonance imaging at the level of individual biological cells.
A new multi-institutional study found patterns of abnormal brain MRI findings in patients with severe COVID-19, including signal abnormalities in the medial temporal lobe and non-confluent multifocal white matter hyperintense lesions. The study suggests that imaging and neurological follow-up are crucial to evaluate prognosis.
A study finds that distal femoral cortical irregularities (DFCI) occur in over half of young competitive alpine skiers, primarily due to repetitive stress on tendon attachment sites. DFCI should not be mistaken for cancer or infection and are associated with increased bone remodeling and fibrous proliferation.
Researchers at UT Southwestern Medical Center have developed new MRI techniques to more precisely target brain structures linked to Parkinson's disease and essential tremor. These methods, including diffusion tractography, aim to reduce adverse effects associated with previous treatments.
A new machine learning approach classifies gliomas into low or high grades with near-perfect accuracy, enabling clinicians to choose the most effective treatment strategy. Researchers developed the method using MRI scans from over 200 patients and achieved an accuracy rate of 97.54%, outperforming state-of-the-art approaches.
A new MRI scan algorithm can detect small changes in knee joints over time, enabling researchers to develop new treatments for arthritis. The algorithm creates a three-dimensional model of an individual's knee joint and automatically identifies areas of cartilage breakdown.
High-resolution imaging of human placenta reveals uniform oxygenation levels and efficient blood flow, while also discovering rapid draining from veins and utero-placental pump contractions that facilitate better circulation and fetal growth. These findings improve placental models and optimize MRI protocols for better diagnosis.
Researchers at UC Davis developed a new double-contrast technique that uses magnetic resonance imaging to detect small tumors in normal tissue. The technique, called two-way magnetic resonance tuning (TMRET), increases the signal contrast between tumors and surrounding tissue, enabling more sensitive detection of early-stage tumors.
Researchers found elevated levels of gadolinium in Tokyo river water, particularly near treatment plants, highlighting the need for new policies and removal technologies as MRI become more widespread.
A recent study presents an automatic method to detect and segment the intrauterine cavity using artificial intelligence and deep learning techniques on MRI data from 71 pregnancies. The proposed method achieves high segmentation performance, highlighting its potential for use in daily clinical practice as a surgical planning method.
A new technique uses magnetic core-shell iron nanowires to track live-cell location and migration in real-time over many days, with potential applications in cancer treatment and stem cell therapies. The nanowires can selectively kill cancer cells while also providing noninvasive medical imaging capabilities.
Researchers used magnetic resonance imaging to detect fetal brain impairments in rhesus macaques exposed to alcohol during pregnancy. The study suggests that early detection of fetal-alcohol syndrome could lead to timely therapy and improved outcomes.
A new study developed a non-invasive molecular imaging approach using dynamic MRI to measure glucose level changes in the brain lymphatic system. This method helps identify Alzheimer's disease at early stages, allowing treatments to start promptly. The technique uses glucose as a 'tracer' and is compatible with existing MRI machines, m...
Scientists at Sanford Burnham Prebys and Loma Linda University Health have demonstrated the promise of applying magnetic resonance imaging (MRI) to predict the efficacy of using human neural stem cells to treat a brain injury. The researchers found that rats with larger penumbra areas surrounding brain injury, which received human neur...
A new study suggests that machine learning and AI in medical image reconstruction algorithms can result in myriad artefacts and major errors, leading to false positives and false negatives. The effects were typically not present in non-AI based imaging techniques.
Researchers demonstrated optical polarization and reading of electronic spin color centers in boron nitride. The study proposes a microscopic model of the center, a boron vacancy in a negative charge state, and shows potential for vander Waals materials in atomic-scale quantum technologies.
A study published in Brain found that a lag in blood drainage from the deep region of the brain is associated with ventriculomegaly and can be detected with MRI. The researchers identified this biomarker as a potential predictor for dementia and ventriculomegaly, which can be reversed by removing excess fluid.
Researchers compare whole-body diffusion-weighted MRI to FDG PET and find significant agreement in tracking tumor response to therapy, raising the possibility of using DW MRI as a replacement for CT scanning.
A new AI algorithm can predict Alzheimer's disease risk with high accuracy using a combination of brain MRI scans, cognitive impairment tests, and demographic data. The algorithm also provides interpretable visualizations of individual disease risk, leading to more accurate diagnoses.
Researchers have developed an MRI scanning technique that enables the detection of sodium metal ions in batteries, providing unprecedented insights into their behavior during operation. This allows for the identification of failure mechanisms and the development of longer life and higher performing batteries.
A new randomized control trial will examine the effectiveness of Goal Management Training, a cognitive remediation strategy, in improving functional outcomes among first responders with PTSD. The study aims to understand changes in brain structure and function using magnetic resonance imaging.
Early alcohol exposure affects motor control brain regions in monkeys, and may be detectable via non-invasive in utero MRI. The study suggests that diagnostic tools for fetal alcohol syndrome could be developed as early as the third trimester.
A new approach to combine CT and MRI data in one 3D image helps solve uncertain findings in coronary artery disease diagnosis. The technique correlates specific stenoses with possible cardiac scar tissue and ischemia, guiding revascularization procedures.
A new study found that long-duration space travel can cause expansions in the brain's white matter and combined brain and cerebrospinal fluid volumes. The researchers also observed alterations to the pituitary gland, a pea-sized structure at the base of the skull, suggesting elevated intracranial pressure during spaceflight.
Researchers at Tohoku University have developed a technique to visualize stiffness in soft tissues using x-rays, offering greater resolution than current methods like ultrasound and MRI. This allows for the identification of smaller and deeper tissue problems, such as lesions, which can be indicative of early-stage diseases.
Researchers at the University of Montreal developed an AI technique to better define brain sections in newborns using MRI exams. This innovation enables quick, accurate, and reliable analysis of baby brains, supporting research on brain development and neuroprotection.
Researchers have created a device that uses sound waves to produce high-resolution images of the human brain, potentially revolutionizing brain imaging. The technology could be suitable for continuous monitoring of high-dependency patients and overcome obstacles with current MRI methods.
Assistant Professor Fabrizio Sergi at the University of Delaware received a NSF CAREER Award for his work on motor control and brain-body interaction using MRI-compatible robots. His research aims to improve neurorehabilitation practices for individuals with motor impairment, such as stroke survivors.
A new study published in Radiology: Cardiothoracic Imaging found that healthy men and women have distinct blood flow characteristics in their hearts. The research used 4D flow MRI to analyze gender differences in the left ventricle, revealing higher kinetic energy in men and greater strain in women.
Purdue University researchers have created a novel way of doing some medical imaging using formable and stretchable RF coils. The technology provides an excellent signal-to-noise ratio for enhanced MRI scanning, making it more comfortable and accessible for patients.
A study published in JAMA found abbreviated breast MRI to be more effective than digital breast tomosynthesis in detecting breast cancer in women with dense breasts. The test detected significantly more cancers and showed promise as a new screening tool for these patients.
Researchers at Case Western Reserve University and Cleveland Clinic have developed a new method to determine the relative life expectancy of glioblastoma patients using AI, MRI scans, and genomic analysis. This approach identifies patients who could benefit from experimental clinical trials.
Joint capsule edema and thickness at the axillary recess are useful predictors of stiff shoulders in patients with rotator cuff tears. MRI findings also show associations between tear size, location, and preoperative passive range of motion.
A new collaborative study has developed a way to measure microscopic axons using MRI, revealing unprecedented accuracy and opening up new research possibilities. The method overcomes the long-standing challenge of probing axons non-invasively inside a living brain.
A portable, low-field Magnetic Resonance Imaging (MRI) system has been developed to provide safe and practical brain imaging at a patient's bedside, according to preliminary research. The device used 85 stroke patients, with most completing the exam in under 30 minutes, while factors like claustrophobia halted some tests.
A team of researchers has created a novel organic and biodegradable compound for MRI contrast agents, eliminating the need for heavy metals like gadolinium. The new agent is developed by attaching an organic radical contrast agent to a plant virus and wrapping it in a protective chemical cage.
A UCLA-led study found that six blood proteins can be used to gauge a person's risk for cerebral small vessel disease, which affects an estimated 11 million older adults in the U.S. The test correlates with white matter changes in the brain and provides a more quantitative scale for evaluating the disease.
A recent study published in Scientific Reports found that daily smoking and heavy drinking may be associated with modest increases in relative brain age. Researchers used machine learning methods and MRI to analyze data from over 17,000 individuals and discovered a correlation between smoking habits and increased brain age.
A groundbreaking study published in PNAS used a multi-modal precision health platform to identify adults at risk of key health conditions, including cancer, heart disease, and neurological disorders. The study found that integrating whole-genome sequencing with advanced imaging and blood metabolites led to clinically significant findin...
Hyperpolarized 13C-Magnetic resonance imaging (HP 13C-MRI) reveals the conversion of pyruvate into lactate in breast cancer tumors, associated with higher tumor grades. The study suggests HP 13C-MRI as a noninvasive tool for characterizing and monitoring breast tumors.
Researchers from UMA developed a method using deep learning to increase brain image quality and detection of pathologies with increased accuracy. This breakthrough technique enables specialists to identify brain-related disorders more accurately and definitionally, reducing the need for additional tests.
Researchers found structural brain connectivity changes between migraine patients and healthy volunteers, as well as between episodic and chronic migraine patients. Strengthening connectivity was observed in areas implicated in migraine's pathophysiology, while weakening connectivity patterns were seen in the temporal lobe of migraine ...
Research reveals that early-life deprivation is associated with reduced total brain volume and altered brain structure, even after years of environmental enrichment. This study suggests that early adversity can have lasting impacts on adult brain development.
Researchers found that specific patterns of brain connectivity were associated with the development of attention-deficit/hyperactivity disorder (ADHD) and major depressive disorder. By examining brain architecture at age 7, the study identified potential links between brain development and later mental health symptoms in children.