Articles tagged with Radiography
Researchers have developed a new framework to detect possible damage in concealed cold-formed steel construction framing materials, utilizing ground-penetrating radar and artificial intelligence. The technology allows for rapid detection of damage, enabling inspectors to verify only flagged spots without removing walls or cladding.
Researchers found that PSMA PET/CT scans can help guide treatment planning and improve long-term outcomes for patients with recurring prostate cancer. The study suggests that incorporating these scans into routine care may lead to better results and reduced side effects.
The new system can reveal early cancers, lung disease, hidden material defects and changes in porosity without multiple exposures or complex mechanical movement. This method produces low-dose and faster images, lowering patients' radiation dose and making clinical translation feasible.
A cohort study found that early extracranial surgery was associated with adverse outcomes in function, cognition, and disability after moderate-severe traumatic brain injury. The study suggests that further research is needed to determine if surgical timing or other interventions can improve long-term deficits.
A study published in The New England Journal of Medicine found that nearly 4 million children and adolescents were at higher risk of developing blood cancers due to radiation exposure from medical imaging. The researchers estimated that up to 10% of pediatric blood and bone marrow cancers may be attributable to radiation exposure.
Researchers at University of East Anglia developed 4D flow MRI scan to diagnose aortic stenosis more accurately and reliably than current ultrasound techniques. The technology offers more accurate measurements of blood flow through heart valves, leading to better prediction of when patients need surgery.
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.
A Colorado State University team has achieved a new milestone in 3D X-ray imaging technology by capturing high-resolution CT scans of the interior of a large, dense object using a compact, laser-driven X-ray source. This breakthrough offers a fast and non-destructive way to obtain detailed views inside dense structures.
The NRL's Mercury Pulsed Power Facility has enabled significant advancements in flash x-ray radiography and nuclear material detection. The facility has been used to develop advanced flash radiography sources and detectors for the Department of Energy and Department of Defense.
Lithium-sulphur batteries have high specific energy densities but are susceptible to degradation due to polysulphide and sulphur phase formation. Researchers investigated lithium-sulphur pouch cells using operando analysis, revealing new insights into cell component design and performance.
A study of 259 adult patients found that many general practitioners prescribe antibiotics despite negative chest X-rays, highlighting a gap between guidelines and practice. The study aimed to explore the relationship between chest radiography results and antibiotic initiation in community-acquired pneumonia management.
Researchers explore AI's role in addressing challenges in immunotherapy, developing new biomarkers for precise disease characterization and predicting treatment response. A comprehensive review applied AI/radiomics to cross-sectional imaging, showcasing the current landscape in IO treatment.
Scientists at the DOE's Princeton Plasma Physics Laboratory have directly observed magneto-Rayleigh Taylor instabilities in plasma, which could aid in understanding how black holes produce vast intergalactic jets. The observation confirms that magnetic fields play a crucial role in forming these jets.
A commercial AI tool was effective in excluding pathology and had lower rates of critical misses on chest X-rays compared to radiologists. The study found that the AI tool could autonomously report more than half of all normal chest X-rays without decreasing standard of care.
Researchers developed an AI model that can estimate lung function from chest radiographs with high accuracy, potentially expanding options for pulmonary function assessment in patients who have difficulty performing spirometry. The study found a remarkably high agreement rate between the AI model's estimates and actual spirometric data.
A new imaging technique developed at Memorial Sloan Kettering Cancer Center shows promise for detecting deadly forms of lung and prostate cancer. The technology targets DLL3, a ligand found on cancer cells, making them more visible on PET scans.
Researchers analyzed three tumor markers for associations with radiographic response and clinical outcomes in NSCLC patients. The study found that CEA, CA-125, and CA-19-9 were associated with progression and radiographic responses in NSCLC.
A comprehensive review examines the impact of osteoporosis on fracture healing and the effects of osteoporosis medications. The study concludes that there is no deleterious effect of osteoporosis medications on fracture healing, and prompt treatment can reduce the risk of secondary fractures.
Outdated medical tools cause delayed recognition and management of adverse reactions in patients of color, leading to significant distress. A more inclusive approach is urgently needed to address structural racism in radiotherapy treatment and education.
Researchers at the University of Surrey have developed new, tissue-equivalent curved organic X-ray detectors that are cheaper, more flexible, and sensitive than traditional detectors. These detectors have the potential to improve accuracy in cancer treatment and reduce radiation risk.
Researchers developed an AI-based method to estimate BMD from plain X-ray images using a hierarchical learning framework. The approach showed high performance and reliability in estimating BMD, with correlation coefficients of 0.88 and 0.92 compared to DXA and QCT.
A new generative AI model enhances clinical accuracy and textual quality of chest radiograph reports, surpassing traditional methods like teleradiology. Its implementation could enable timely alerts for life-threatening conditions, aiding imaging interpretation and documentation.
A study found that ultrasound scans performed by emergency physicians can nearly halve the time patients spend in emergency departments. This technology, known as point-of-care ultrasound (POCUS), enables faster diagnoses and treatment for suspected deep vein thrombosis (DVT).
An AI system by Lunit identified improperly positioned endotracheal tubes with high sensitivity and specificity, allowing for earlier repositioning and reducing complications. The study included 539 chest radiographs from three institutions and showed promising results in detecting ETT presence and improper position.
Researchers developed a deep-learning model to assess CXR images for probable COVID-19 severity. The model achieved an area under the receiver operating characteristic curve of 0.78 when predicting intensive care need within 24 hours.
A study led by University of Missouri neurologist Adnan Qureshi discovered that last year's iodinated media contrast dye shortage impacted the assessment of stroke patients in the US. The shortage resulted in a significant decrease in CT angiograph and CT perfusion scans, affecting blood flow and brain tissue identification.
Researchers developed an AI model that accurately classifies six types of valvular heart disease using chest radiographs, with high accuracy rates. The model's potential applications include supplementing echocardiography in areas where specialists are scarce and improving emergency care.
A deep learning-based model developed in 7,105 patients predicted 30-day all-cause mortality in patients with CAP with AUCs ranging from 0.77 to 0.80. The model showed higher specificity than the CURB-65 score at the same sensitivity.
Researchers observed lithium ions wandering within composite cathodes, revealing limitations in ion delivery that affect battery performance. The findings suggest a previously overlooked development bottleneck for solid-state battery development, highlighting the need to enhance ion transport within cathode composites.
A printable multi-energy X-ray detector made from perovskite thin films has been developed with enhanced flexibility and sensitivity. The detector can operate in a broad energy range, from 0.1 KeV to tens of KeV, making it suitable for real-time detection and imaging applications such as disease diagnosis and explosives detection.
A new study reveals that phase-contrast X-ray imaging can visualize smallest airways and their obstructions, potentially detecting early-stage lung disease. This technique could provide better resolution and contrast than conventional radiography, enabling subtle pathological changes to be seen.
KAUST researchers have designed and built novel organic scintillator materials for detecting X-rays at low doses, overcoming stability issues with existing ceramic or perovskite materials. The new approach uses heavy atoms to improve X-ray absorption capability and exciton utilization efficiency.
The procedure requires thorough pre-procedural evaluation and assessment of anatomical and hemodynamic data. Long-term results indicate that TPVR can effectively restore RVOT function, while improving survival rates and reducing the need for reintervention across age groups. Vigilant testing is recommended to avoid rare but serious com...
A recent study found that AI failed to pass a radiology qualifying examination, with an average accuracy of 79.5%. However, the researchers suggest that further training and revision could lead to improved results.
Researchers developed an AI-based neural network to detect early knee osteoarthritis from x-ray images, matching doctors' diagnoses in 87% of cases. This method could help reduce unnecessary examinations, treatments, and even knee joint replacement surgery.
An AI-based model has been developed to assist radiologists in detecting and identifying leadless implanted electronic devices (LLIEDs) on chest X-ray images. The model achieved high detection and classification accuracy, even with suboptimal image quality, and showed promise for real-world deployment.
Researchers developed a novel three-core optical fiber sensor to accurately measure both the magnitude and direction of spine curvature. The sensor offers advantages like low cost, high sensitivity, and small size, making it a promising tool for doctors to diagnose problems in spine curvature.
A study found that trained radiographers perform as well as radiologists in key areas of double reading mammograms, improving cancer detection rates. The results suggest that focused training and experience are key factors in reader performance, not just medical degree or broad radiology education.
A multicenter study found that radiologists can accurately diagnose rickets and classic metaphyseal lesions (CMLs) with high interobserver agreement and diagnostic performance. The study highlighted the importance of considering age factors in diagnosis, as CMLs mostly occur in children younger than 6 months.
The study compared lung perfusion scans during COVID-19 (April 2020 to July 2021) to pre-COVID V/Q scans (December 2018 to March 2020) in a large tertiary care teaching hospital. The results showed a 30% decline in overall lung scans performed during the pandemic.
Researchers have developed a new approach to micro-computed tomography using phase contrast and high-brilliance x-ray radiation, enabling detailed analysis of microstructures and broad applications in medicine, biology, and material sciences.
The American Roentgen Ray Society has awarded two 2022 ARRS Scholarships to Sean Woolen and Bradley Allen, providing a total of $180,000 in funding for their radiological research projects. The scholarships aim to advance emerging scholars and prepare them for leadership positions.
Researchers at Technical University of Munich have developed a new neutron-based method to detect clogs in underwater pipelines non-destructively. This approach uses prompt gamma neutron activation analysis to measure hydrogen concentration, allowing for the detection of blockages and hydrate formation.
A new imaging method measures individual photons, greatly reducing interference and improving spatial resolution by three times. The technology could also reduce radiation exposure during x-ray imaging, making it ideal for medical applications.
Convolutional neural networks trained to identify abnormalities on upper extremity radiographs are susceptible to a ubiquitous confounding image feature: radiograph labels. Covering these labels increases accuracy, while using them alone leads to decreased performance.
A two-year project led by Dr. Kirsty Squires aims to analyze 41 mummified children from the 19th century using non-invasive methods. The study will provide essential data on juvenile health, development, and identity during this period.
A deep learning algorithm from VUNO improved radiologists' sensitivity for detecting reticular opacity on chest radiographs in patients with mild to severe interstitial lung disease. The algorithm accuracy reached 98.5% and improved interobserver agreement, suggesting its potential for screening suspected ILD patients.
A randomized clinical trial found that semi-annual application of 5% sodium fluoride varnish significantly reduces approximal caries development in primary teeth compared to 38% silver diamine fluoride and placebo controls. The study evaluated 4-6 year-old children with at least one sound approximal surface.
A recent EULAR study found that treatment with tumor necrosis factor inhibitors can slow the progression of radiographic sacroiliitis in patients with axSpA. This effect becomes apparent 2-4 years after treatment initiation, according to the research.
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.
A study found a significant association between carotid artery calcification observed in oral panoramic radiographs and chronic coronary artery disease. The researchers also discovered that patients with severe carotid artery calcification had a significantly higher risk of death from cardiovascular diseases.
Researchers developed computational models of patients with COVID-19 to enhance assessment and analysis tools in CT and radiography. These models were combined with imaging simulators for COVID-19 studies, yielding realistic results.
This retrospective chart review examined the use of static and expandable interbody spacers in minimally invasive LLIF. Patients who underwent MIS LLIF using titanium expandable spacers with adjustable lordosis showed significant positive clinical and radiographic outcomes.
Radiologists at Shanghai Jiao Tong University Medical School implemented strict disinfection measures, including air disinfector use and ultraviolet light, in CT examination rooms to reduce COVID-19 transmission risk. Radiographers followed personal protective equipment protocols, with separate zones for clean and contaminated areas.
Researchers developed AI models for chest X-ray interpretation that can detect fractures, nodules, opacity and pneumothorax as effectively as experienced radiologists. The models were trained on large datasets and evaluated using a panel of radiologists to increase expert consensus and accuracy.
Nonphysician providers, including nurse practitioners and physician assistants, rarely render diagnostic imaging services, with most being radiography and fluoroscopy. Despite growing involvement in imaging-guided procedures, NPPs still represent a small fraction of all diagnostic imaging interpretations.
Researchers at Helmholtz-Zentrum Berlin analyse fragile papyrus with nondestructive methods, detecting lead in blank patch and deciphering blurry image. A new technique allows them to study folded papyri without contact, opening doors for future studies on valuable finds.
The researchers used muon radiography to create the first 3D images of the Derbent fortress's underground space, confirming the hypothesis that it was a Christian temple. The unique shape and orientation of the building suggest an early Christian design, contradicting previous interpretations as an underground water tank.
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.
The article discusses the challenges in managing common ankle fractures, particularly those above and below the level of the syndesmosis. Researchers recommend assessing medial clear space on radiographs and patient pain ratings to guide management. They also emphasize the importance of dynamic imaging with stress radiographs to detect...