Articles tagged with Magnetic Resonance Imaging
Scientists developed a novel quantum sensor that can detect oxidative stress in organs during MRI scans, which could lead to early diagnosis of diseases like cancer and kidney dysfunction. The sensor uses a ring-shaped sugar-like compound and nitroxide derivatives to identify reduced cell/tissue capacity.
Researchers used MRI technology to investigate a new strategy for managing sodium levels in hemodialysis patients. Four weeks of low-sodium meals significantly reduced weight gain, thirst, and phosphorus levels in participants.
Research suggests that radiologists' diagnoses of lumbar spine pain generators are highly accurate when using patient-reported symptom information from brief questionnaires. The study found almost perfect agreement between radiologists' diagnoses using symptom information and those without it, improving diagnostic certainty levels.
Scientists used MRI to study brain activity during sleep, discovering that overall activity decreases but communication among brain regions becomes more dynamic. The findings suggest a breakdown in neural networks during transitions between light and deep sleep stages, with implications for understanding human consciousness.
A study of 419 breast MRI examinations found new suspicious findings in 5.5% of patients, but all were benign; results suggest biopsies may not be necessary for patients responding well to neoadjuvant therapy.
A study by Vanderbilt University Medical Center found lower degrees of myocarditis in athletes with a history of COVID-19 compared to previously reported rates. The research highlights the importance of considering cardiac MRI as an additional screening tool for detecting myocarditis in athletes.
A new imaging technique has been developed to identify non-ferromagnetic projectiles that are safe for MRI, enabling patients with ballistic embedded fragments to receive medical treatment. The technique uses radiography and CT images to distinguish between ferromagnetic and non-ferromagnetic bullets, allowing for safer MRI scans.
Drs. Kelil and Jaimes will investigate personalized breast cancer risk assessment and fetal diffusion tensor imaging to improve conventional risk prediction models and characterize normal brain development in fetuses with congenital heart disease. Their studies aim to harness cutting-edge MRI processing tools to correct for fetal motion.
Researchers in Japan have used machine intelligence to fine-tune algorithms for brain mapping by MRI, improving the accuracy and reliability of connectome estimation. The new technique generates more convincing results, particularly in detecting long-range nerve fibers, crucial for understanding brain function.
The study investigated factors affecting upper limb motor recovery after a stroke and found that structural integrity of the corticospinal tract is a key predictor. The researchers used transcranial magnetic stimulation (TMS) and magnetic resonance imaging (MRI) to assess the condition of the corticospinal tract in 35 patients.
A study of 40,000 adults found that lonely individuals have distinct brain regions and networks, including a stronger default network and preserved fornix nerve fibers. This could help prevent neurological disease and develop better treatments for loneliness.
Researchers developed a manganese-based contrast agent that is diagnostically equivalent to gadolinium-based contrast agents but without the toxicity, offering a safer alternative for patients with chronic kidney disease. The new agent, Mn-PyC3A, is rapidly and completely eliminated from the body and does not accumulate in tissues.
Researchers at the Beckman Institute created a subspace mass spectrometry imaging approach to accelerate data acquisition without sacrificing quality. This technique can detect biomolecules across a wide range of sizes and has implications for analytical chemistry, clinical studies, and neurochemical research.
A new method, nnU-Net, has been developed to configure self-learning algorithms for a large number of different imaging datasets, enabling the interpretation of three-dimensional imaging data and distinguishing between tumor and non-tumor tissue.
Researchers at Massachusetts General Hospital have created a compact, low-power 'head only' MRI scanner for brain imaging. The device can be mounted in ambulances or clinics and emits less noise than traditional scanners.
A long-term study of over 1,000 people found that childhood lead exposure was associated with structural brain changes and a significant loss of IQ points by age 45. The study revealed subtle but detectable differences in brain structure, including reduced cortical surface area and hippocampal volume.
Researchers found that additional imaging tests revealed hidden causes of heart damage and inflammation in 84% of women with MINOCA, a type of non-obstructive coronary artery disease. The study suggests that women are more likely to have this condition than men, and it has the potential to guide medical therapy for secondary prevention.
Researchers observed that brain ventricles expanded in MS patients during inflammation, but then shrunk back to normal size after symptoms subsided. This finding suggests that ventricle volume fluctuations may be reversible and have clinical relevance for monitoring disease progression.
A new three-dimensional imaging technique has been developed to improve the visibility of brain tumors in MRI scans, doubling contrast between tumors and normal brain tissue. This could enable earlier detection and more effective treatment of malignant tumors.
A new 'fast' MRI test has been shown to detect breast cancers that 3-D mammograms may miss in women with dense breasts. The test, which is an abbreviated version of traditional breast MRI, detected 27 cancers per 1,000 women screened.
Researchers found that fluorine-18-labeled fluciclovine PET/MRI accurately identified prostate cancer lesions, suspicious lymph nodes, and detected nodal metastases not visible on conventional imaging. The technology also showed promise in evaluating response to androgen deprivation therapy.
Researchers propose new method to verify star and planet formation theory by simulating the Princeton Magnetorotational Instability (MRI) Experiment. The study finds that instabilities can be seen before the upper limit of experimental rotation rate is reached, shedding light on the growth of celestial bodies.
Researchers are combining global MRI data to predict outcomes and develop new treatments for traumatic brain injury, a major cause of disability. By pooling resources and analyzing large datasets, they aim to tackle complex questions about brain function and recovery.
A study published in Radiology: Cardiothoracic Imaging demonstrates the safety of performing MRI exams in patients with non-MR compatible cardiac devices, including those who are pacemaker-dependent or have abandoned leads. The results showed no adverse events and improved diagnosis and treatment plans for patients.
A study of secondary body MRI interpretations at tertiary care centers found a high rate of discrepancies, with cognitive errors being the most common type. The researchers suggest that subspecialty interpretations and additional resources are needed to address these errors and their potential impact on patient outcomes.
Researchers developed SeSBAT, a computer program that analyzes magnetic resonance images to detect early signs of neurodegenerative diseases. The tool identifies biomarkers before symptoms appear, allowing for individualized monitoring and more accurate management.
The availability of mpMRIp in Australia has led to a significant reduction in prostate biopsies by an average of 354.7 per month. This is estimated to save $13.2 million annually, making it a financially sensible policy from a healthcare perspective.
Researchers at King's College London have developed a new method for detecting congenital heart disease in babies, using 4D visualizations of the heart to measure blood flow and vessel function. This technology could become a new tool for aiding diagnosis, potentially improving outcomes for babies born with the condition.
Skoltech researchers propose a fast and accurate numerical method to address the low spatial resolution of EEG studies. The new approach directly backpropagates measured signals from the skin down to the cortex, increasing accuracy for source localization while speeding up processing.
Researchers developed an AI-based deep learning platform, DystoniaNet, to diagnose dystonia from brain MRIs with high accuracy. The platform detected cases of dystonia with 98.8 percent accuracy and identified a new microstructural neural network biological marker.
A research team has discovered a remarkable echo effect in phosphorus atoms on silicon, allowing for the detection of multiple spin echoes. This effect is due to strong coupling between atomic spins and microwave photons, enabling the processing of quantum information.
Researchers at HSS are using magnetic resonance neurography to study Parsonage-Turner Syndrome, a painful nerve disorder that can cause sudden weakness. High-resolution images of peripheral nerves will be obtained to discover biomarkers for detection and monitoring, as well as aid in surgical planning.
A study found that COVID-19 recovery in competitive college athletes can lead to myocardial inflammation, as detected by cardiac magnetic resonance imaging (MRI). The researchers identified a high-risk group of athletes who should be carefully monitored before returning to play.
Researchers used modest data and basic engineering AI to solve complex MRI appointment no-shows. The study found a 17.2% improvement in no-show rates after implementing phone call reminders for high-risk patients.
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.
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 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.
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 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.
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.
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.