Articles tagged with Radiology
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
A study published in the Journal of Neurology, Neurosurgery and Psychiatry found increased connectivity between motor regions and the multimodal integration network in patients with FND. Symptom severity also correlated with increased coupling between the insula and the amygdala, which improved response to treatment.
A new study found that AI systems can perform as accurately as radiologists in detecting breast cancer in digital mammography screening. This breakthrough suggests that AI may be a viable alternative to current methods, which are labor-intensive and facing staff shortages.
A new study explores an episodic bundled payment model for breast cancer screening reflecting the widespread adoption of DBT. The analysis found that non-DBT approaches to bundled payment models remain viable, but higher DBT-inclusive prices highlight the need to explore societal costs more broadly.
A study published in Radiology found that radiologists can identify patterns of injury indicative of intimate partner violence. The research suggests that medical images can offer early clues of this type of violence, particularly among women and those with certain socioeconomic factors.
A new study finds that women's brains are metabolically three years younger than men's of the same age, which may contribute to their greater mental sharpness in later years. The researchers used PET scans and machine-learning algorithms to measure brain metabolism and calculate each person's brain age.
A novel AI system can reduce average delay in reporting abnormal chest X-rays from 11 days to less than 3 days. The system uses computer vision and NLP algorithms to quickly identify critical findings, prioritizing exams for expert radiologist opinion.
A new AI system can interpret and prioritize abnormal chest X-rays with critical findings, reducing the backlog of exams and bringing urgently needed care to patients more quickly. The system distinguishes abnormal from normal chest X-rays with high accuracy and can perform this task significantly faster than human radiologists.
Researchers at the University of Cincinnati are studying the use of neuroimaging to pinpoint the risk factors of stroke recurrence, which affects nearly 800,000 people annually in the US. The study aims to identify patients at higher risk for recurrent strokes by assessing imaging for signs of small vessel disease in the brain.
A Massachusetts General Hospital team developed an AI system to diagnose and classify brain hemorrhages using CT scan images. The system can provide the basis for its decisions by highlighting key features of each subtype.
Researchers from Ben-Gurion University of the Negev developed a system to monitor outgoing commands from CT equipment, detecting anomalies and alerting operators before execution. A second study looked at the potential to tamper with mammogram results using AI-powered image manipulation.
Researchers found a link between shoulder muscle brightness on ultrasound and type 2 diabetes, with low glycogen levels suspected as the cause. The study's findings suggest that radiologists can use ultrasound images to predict diabetic status in nearly nine out of ten patients.
A new study published in Radiology uses deep learning to predict Alzheimer's disease from brain imaging, achieving 100% sensitivity in detecting the disease an average of more than six years prior to final diagnosis. The algorithm has the potential to complement existing tests and provide opportunities for early intervention.
A deep-learning model has been successfully used on real patients to assess dense breast tissue in mammograms with high accuracy. The model outperforms traditional prediction models, achieving a kappa score of 0.85 in clinical applications, and could lead to more consistent screening procedures nationwide.
A new AI algorithm measures breast density at a high level of accuracy, comparable to experienced mammographers. The system has been successfully implemented in routine clinical practice and has the potential to standardize and automate breast density assessment.
A deep learning approach can identify nuanced mammographic imaging features specific to recalled but benign (false-positive) mammograms, distinguishing them from those identified as malignant or negative. The study achieved an area under the curve (AUC) of 0.76-0.91, indicating high performance in detecting false recalls.
A new study found that abdominal aortic calcification measured by CT scans is a strong predictor of future cardiovascular events, outperforming the widely used Framingham risk score. The research suggests that detecting calcification via routine CT scans could help identify patients at high risk and enable early interventions.
Researchers developed a new MRI technique that analyzes overlooked data to reveal brain cell density and connectivity. This may aid in diagnosing brain conditions such as Alzheimer's disease, multiple sclerosis, traumatic brain injury, and autism.
The study found a significant increase in secondary imaging interpretations across various modalities and body regions, driven by high-volume service families. Denial rates for these services were uniformly low, below 25%, contradicting conventional wisdom.
IVC filter placement and retrieval procedures declined over the last decade, with a notable shift towards radiologists and cardiologists performing placements in hospital outpatient settings. Retrieval rates increased but remained less than 15% across all specialties.
Richard L. Wahl, MD, has been recognized for his pioneering work in radioimmunotherapy, PET scans, and fusion imaging. His research has significantly contributed to understanding cancer prognosis, treatment response, and the importance of metabolic activity.
A study found that damage to brain pathways can lead to attention deficit in patients with subcortical stroke. The research used voxel-based lesion-symptom mapping and diffusion tensor tractography to identify the responsible impaired connections.
Ali Guermazi, the first radiologist to receive the award, has made significant contributions to identifying structural risk factors for osteoarthritis. His research and clinical trials have been published in top-tier journals and presented at international conferences.
Recent studies by Case Western Reserve University's Anant Madabhushi show that his diagnostic imaging lab's 'deep learning' computers can accurately diagnose heart failure and detect various cancers. The machines offer valuable tools for pathologists and radiologists, helping them become more efficient in their work.
PARP-1 levels are linked to targeted therapy resistance in ovarian cancer. Researchers have developed a method to image and measure PARP-1 using PET scans, which may predict efficacy and resistance to PARP inhibitors.
A new study presents contrast-enhanced subharmonic imaging (SHI) as a promising tool for detecting prostate cancers not identified by MRI. SHI provides improved contrast signal and tissue suppression, leading to better visualization of microvascular architecture.
A study using machine-learning algorithms and MRI analysis predicts the severity of neurologic impairment after spinal cord injury. The results show variable accuracy in classifying patients and identifying potential prognostic texture features.
A radiologist at the University of Virginia Health System has created a virtual reality teaching tool that puts viewers in the midst of complex procedures, revolutionizing medical education. The tool allows physicians and trainees to experience intricate procedures like an 'interventional radiology heptathlon' with unparalleled clarity.
Researchers found that talimogene laherparepvec, a genetically modified herpes virus, can be safely administered into active cancer in the liver to stimulate the immune system and destroy cancer cells. The treatment has been well-tolerated with minimal side effects.
A new machine learning model can accurately predict which patients are most likely to benefit from prostate multiparametric MRI (mpMRI), allowing for optimized patient selection and resource allocation. The model showed high accuracy in predicting PI-RADS category 4 or 5 lesions, with a sensitivity of 75% and specificity of 82%.
A pilot study demonstrates the safety and feasibility of freezing the posterior vagal trunk nerve, which carries hunger signals to the brain, resulting in significant weight loss. The procedure, known as cryovagotomy, showed a 3.6% average weight loss and nearly 14% decline in excess BMI.
A new study found that 3D-printed models of blood vessels are as effective as commercial models in training medical students, providing a more realistic experience. The 3D printing technology can reproduce patient anatomy, allowing trainees to practice with variations before real procedures.
A study finds that interrupting radiologists does not reduce diagnostic accuracy but changes their focus and increases time spent on cases, with more time spent on dictation screens.
A minimally invasive treatment called geniculate artery embolization (GAE) has been shown to significantly reduce knee pain and disability in patients with osteoarthritis. The treatment involves blocking key arteries in the knee to reduce inflammation and pain, resulting in improved range of motion and function.
A new study shows that interactive virtual reality (VR) technology improves accuracy and confidence among interventional radiologists when treating complex conditions like splenic artery aneurysms. The VR platform provides a 3D view of internal anatomy, allowing physicians to better plan their approach.
Despite significant increases in female radiology research, rates of publication have leveled off since 2000. The proportion of female authors in top radiology journals has increased, but progress remains slow.
A new study published in Radiology found that imaging services played a crucial role in managing Olympic athletes with sports-related injuries and disorders. The study showed that MRI was used for nearly 60% of all imaging performed for diagnosis, highlighting its importance in fast and relevant diagnoses.
A study presented at the ARRS 2018 Annual Meeting found that emergency patients are often given unnecessary head CT scans, leading to radiation exposure and healthcare costs. Motor vehicle accidents were associated with a higher rate of non-indicated CT examinations.
A study found that patients and caregivers seek information on their own after receiving inadequate pre-examination information from providers. RadiologyInfo.org is an online resource providing detailed information on medical imaging procedures and preparation.
A study found that full integration of digital breast tomosynthesis (DBT) significantly reduced false positive rates in breast cancer screening exams. DBT was also associated with a higher cancer-detection rate compared to traditional digital mammography.
Measurements taken on projected augmented reality holographic models are highly accurate, rivaling traditional 'gold standard' methods. The study's results demonstrate the potential of AR technology for educational, training, and research purposes.
Researchers trained machine learning models on radiologist reports to identify clinical concepts in CT scans, achieving an accuracy of 91%. This technology will help develop artificial intelligence to diagnose diseases and improve patient care.
Dr Mark Griswold PhD has been elected as a fellow of the National Academy of Inventors for his highly prolific spirit of innovation in creating outstanding inventions that have made a tangible impact on quality of life and economic development. He is renowned for pioneering research and innovations in biomedical imaging.
A high prevalence of complications related to opioid use disorders has been seen in emergency radiology patients, with skin and soft tissue infections, respiratory issues, and back pain being common. Imaging results often provided critical information to aid management plans and reduce mortality rates.
A new study presented at the Radiological Society of North America meeting found that hip steroid injections are associated with a higher incidence of bone death and collapse compared to control groups. The research showed that 22-24% of patients who received hip injections developed osteonecrosis, while 15-17% experienced bone collapse.
A new image-guided pulsed radiofrequency treatment has shown extraordinary results in relieving low back pain and sciatica. The procedure involves inserting a probe to deliver energy to the affected area, resolving herniation without thermal damage, and patients were largely pain-free within a day.
A study presented at the Radiological Society of North America annual meeting found characteristic injuries among patients referred to domestic abuse and sexual assault programs. These injuries, including soft tissue injuries and extremity fractures, can alert radiologists to potential intimate partner violence. The findings suggest a ...
A study by Brigham and Women's Hospital reveals common clinical and radiologic patterns indicative of intimate partner violence (IPV) in radiology images. Radiologists can identify soft tissue injuries, extremity fractures, and facial fractures to spark a conversation with referring physicians about potential IPV.
Researchers at Massachusetts General Hospital have developed a potential alternative to gadolinium-based contrast agents for magnetic resonance imaging (MRI). The new manganese-based agent Mn-PyC3A produced comparable image enhancement to the standard of care with rapid clearance and less likelihood of toxicity. The study used a baboon...
Researchers found infrared imaging to be more accurate than tactile inspection in detecting defects in lead aprons used to shield patients from radiation exposure. The technology reduces ionizing radiation exposure for inspectors and can identify smaller holes that may be missed through visual inspection.
Studies found that female athletes in track and field experienced more bone stress injuries and tendon abnormalities than other Olympic events. Researchers recommend early MRI imaging for early detection of bone stress reactions and pre-competition screening data for chronic lesion detection.
Collaborative nuclear medicine and radiology training options are proposed to address evolving practice needs, while an alternative view emphasizes the importance of independent training programs. Innovative theranostics advances in nuclear medicine are highlighted as a result of dedicated training programs.
Researchers found significant differences between mobile mammography patients and those at a cancer center, including higher recall rates and racial diversity. The study aims to develop targeted programs to increase screening rates among underserved populations.
A study found that less than half of detectable vertebral fractures are reported by radiologists, particularly in non-musculoskeletal radiologists. This under-reporting can lead to delayed diagnosis and treatment of osteoporosis, increasing the risk of future hip fractures.
The study found that utilization rates for musculoskeletal extremity imaging modalities increased significantly between 1994 and 2013, with MRI experiencing an initial period of rapid growth. The four most common modalities - radiography, ultrasound, MRI, and CT - saw increases in volume and per-beneficiary utilization.
Cinematic rendering technology produces photorealistic 3D images from CT and MRI data, enhancing medical education, patient-physician communication, and early disease detection. The technique has potential applications in surgical planning and improves physician-patient relationships.
As more adults are diagnosed with cystic fibrosis, radiologists must monitor the disease's complex and heterogeneous spectrum. The condition affects approximately 70,000 people worldwide, with up to 7% of cases diagnosed in adulthood, often with subtle manifestations.
Practical imaging evaluation of neonatal soft-tissue tumors is crucial for accurate diagnosis, and clear understanding of imaging techniques can improve patient outcomes. Characteristic clinical and imaging findings aid in diagnosing these neoplasms, which may require biopsy or excision for definitive diagnosis.
Researchers at UT Austin discovered systematic laws for perception in natural scenes, predicting object detection based on background properties. This finding has potential applications in radiology, security imaging, and camouflage design.
A survey of radiologists found that while they agree on the importance of patient-centered care, current practices are hindered by time and workload constraints. Social media and integrating reading rooms into clinics offer opportunities for better communication with patients.
A new ultrasound scoring system has been developed to identify thyroid nodules that require biopsy or follow-up. The system uses a risk stratification approach to classify nodule appearance and size, reducing unnecessary biopsies and improving cancer diagnosis accuracy.