Articles tagged with Radiology
Scientists investigated how Pr content impacts perovskite oxide crystal structure and oxygen exchange. Higher Pr content led to disorder phase transition and improved orbital hybridization, accelerating oxygen exchange. The discovery provides guidance for designing high-performance SOEC anodes.
Experts suggest a clear separation of roles between AI systems and radiologists to overcome challenges such as cognitive biases and misaligned incentives. A framework for role separation is proposed, including three models that can be adapted to specific needs, enabling institutions to implement hybrid approaches.
The tripartite agreement has driven $100M in NIH funding, 217 invention disclosures, 136 U.S. patents, and 31 international patents, accelerating MRI technology adoption and improving patient care. Technologies developed through this collaboration have shaped multiple FDA-approved products used worldwide.
The International radiology consensus outlines best practices for post-COVID CT imaging, including standardized terminology and low-dose protocols. The guidelines aim to standardize the indications for chest CT and improve patient management.
Researchers found Galectin-1, a sugar-binding protein, plays a critical role in helping hepatocellular carcinoma cells resist thermal ablation and thrive after being treated with high heat. Blocking Gal-1 can make thermal ablation more effective and reduce the risk of recurrence.
A new study demonstrates that retrieval-augmented generation can eliminate hallucinations in clinical LLMs while protecting patient privacy. The RAG-enhanced model responds significantly faster than cloud-based systems, delivering safer results without compromising data security.
Researchers at the University of Illinois Urbana-Champaign have developed a new non-invasive MRI approach that visualizes brain metabolism and detects metabolic alterations associated with brain diseases. The technique uses magnetic resonance spectroscopic imaging to provide insights into brain function and disease processes.
A new survey conducted by Ohio State University Wexner Medical Center found that only 1% of men are concerned about bone density, with cancer and heart disease being top concerns. Men can build back bone density through exercise, nutrition, and lifestyle changes, and early intervention can prevent deadly fractures.
A landmark review highlights how diabetes alters bone microarchitecture and increases fracture risk in people with type 2 diabetes, despite normal or elevated bone mineral density. The authors advocate for updated diagnostic tools, including a revised TBS algorithm, to more accurately reflect bone quality in individuals with central ob...
A study published in Radiology found that CT colonography is more effective and cost-effective than stool DNA testing for colorectal cancer screening, reducing incidence by 70-75% compared to 59%. CT colonography is also a cost-saving option with an estimated cost of $9,000 per QALY gained.
A new AI system has been developed that improves radiology productivity and accuracy, offering a breakthrough solution to the global radiologist shortage. The tool boosts efficiency by up to 40% without compromising accuracy and flags life-threatening conditions in real-time.
A new quality initiative at Mass General Brigham improved radiologists' follow-up imaging recommendations, reducing diagnostic errors and potential harm. The initiative resulted in a 44% reduction in imaging recommendations and increased actionability of recommendations, leading to better patient outcomes.
Patients with breast cancer detected through routine screening mammography have improved clinical outcomes, including lower odds of advanced stage breast cancer and death. In contrast, symptom-detected cases were more frequent in older women and had higher mortality rates.
A new study published in Radiology found that abbreviated breast MRI is an effective screening method for women with extremely dense breasts, detecting cancer while reducing scan times by up to 80%. The abbreviated protocol retains a high level of diagnostic accuracy comparable to the full protocol MRI.
A new AI system, MedGaze, is designed to emulate how radiologists visually interpret chest X-rays. By replicating expert attention, it helps train future specialists and improve the efficiency of hospitals through better workflow management.
A new study reveals that fine-tuned large language models (LLMs) greatly improve error detection in radiology reports, outperforming other NLP tools. The LLMs successfully identify various types of errors, including transcription and directional mistakes, providing a promising solution for medical proofreading.
Dr. Tarek Hanna joins UMSOM from Emory University School of Medicine with expertise in emergency and trauma imaging, clinical operations optimization, and faculty development. He will advance clinical excellence and expand radiology services across central Maryland.
Researchers at the University of Chicago Medicine discovered a new phenomenon where high doses of radiation cause growth in existing metastatic tumors. The 'badscopal effect' is attributed to increased production of amphiregulin, which weakens the immune system and makes cancer cells more resistant.
FLT3 mutations significantly impact AML prognosis and treatment response; next-gen sequencing enhances mutation detection and MRD monitoring. FLT3 inhibitors offer promising avenues for durable remission.
The IOF Advanced Course on Osteoporosis is a comprehensive, 18-hour online training programme designed to equip healthcare professionals with the latest knowledge in osteoporosis prevention, diagnosis, and management. The course aims to promote timely diagnosis and treatment, reduce patient burden, and improve global outcomes.
Researchers at TUM developed an AI-powered algorithm to predict kidney damage in prostate cancer patients undergoing lutetium-177 PSMA therapy. Early detection could enable personalized treatment adjustments to prevent organ damage.
The treatment demonstrated early signals of efficacy, with 65.7% of patients experiencing lasting stable disease, and was generally well-tolerated, with most adverse events being mild and manageable.
A Phase II trial found durable antitumor activity in patients with BRCA1/2 mutations treated with olaparib and pembrolizumab, with 8.3% complete response rate
A survey of patients who underwent breast cancer screening mammograms found most support AI's role as a second reader, but concerns about data privacy and bias persisted. Demographic factors such as education and racial background played a significant role in shaping patient perceptions of AI.
Dr. Elizabeth M. Curtis has been awarded the ESCEO-IOF Pierre Meunier Young Scientist Award for her groundbreaking research on musculoskeletal health and bone disease. Her work focuses on the epidemiology of bone, muscle health, and joint health across the lifespan.
A new study suggests that CT scans could account for 5% of all cancer cases each year, primarily due to radiation exposure. The largest risk is among infants, followed by children and adolescents. To mitigate this risk, reducing the number of scans and doses per scan can help save lives.
Twelve young researchers from around the world receive ESCEO-IOF Young Investigator Awards for their groundbreaking studies on osteoporosis. The prestigious awards were presented during the World Congress on Osteoporosis, Osteoarthritis & Musculoskeletal Diseases (WCO-IOF-ESCEO 2025) in Rome, Italy.
Dr Ambrish Mithal, an Indian endocrinologist, has been awarded the prestigious IOF CSA Medal of Achievement for his groundbreaking work in advancing the field of osteoporosis. His pioneering efforts have significantly increased understanding and awareness of osteoporosis globally.
AMMOM has been recognized by the IOF for its significant contributions to osteoporosis awareness and bone health in Mexico. The organization has collaborated extensively with the IOF on various initiatives, including joint scientific meetings and advocacy efforts.
Professor Atsushi Suzuki, Chair of Endocrinology at Fujita Health University School of Medicine, Japan, received the IOF President's Award for his exceptional contributions to IOF. He has shared his expertise as a mentor and engaged member of the Capture the Fracture Governance.
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.
A new framework helps clinicians choose phrases that more accurately reflect the likelihood of certain pathologies in X-rays, improving the reliability of critical clinical information. The approach treats certainty phrases as probability distributions, capturing nuances of what each word means.
The new Keck Medicine of USC – Newport Beach Radiation Oncology and Imaging Center offers biology-guided radiation therapy, using up-to-the-minute signals to track and treat cancer cells in real time. The center is equipped with state-of-the-art technology and will be the first in Orange County to provide this treatment option.
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 new study published in Radiology found that higher blast exposure correlated with changes in brain function and structure, even when standard MRI exams appeared normal. The researchers discovered weaker connectivity in key areas and more severe symptoms such as memory problems and post-traumatic stress disorder.
Dr. David Winchester will lead the American College of Cardiology's Board of Governors, guiding chapters representing all 50 states and promoting heart health improvement in communities. His term aims to address practice challenges through advocacy and chapter support.
Researchers developed a deep learning algorithm to denoise ultra-low dose CT scans, improving image quality and accuracy. The study found that this approach can diagnose pneumonia in immunocompromised patients using only 2% of the radiation dose of standard CT scans.
A new study has developed CoLDiT, a conditional latent diffusion model capable of generating high-resolution breast ultrasound images. The model achieved comparable performance to real images in BI-RADS classification and realism evaluation, while safeguarding patient privacy through nearest neighbor analysis.
A team of researchers from Chiba University has developed a novel radioactive drug that targets and treats metastatic melanoma. The treatment utilizes astatine-211 labeled peptide analog, which shows high accumulation in tumors, rapid clearance from non-target organs, and significant tumor suppression.
Scientists repurposed the drug edaravone as an imaging probe to detect oxidative stress in brain tissue using PET scans. This technique can help diagnose neurological conditions such as ALS and Alzheimer's disease earlier, when treatment is more effective.
A new radiology screening tool can help detect intimate partner violence (IPV) in patients, enabling healthcare providers to identify victims earlier. The study found that imaging studies and injury patterns differ between women who have reported IPV and those who have not.
Researchers developed ItpCtrl-AI, a transparent AI framework that reads chest X-rays like a radiologist, providing accurate diagnoses and increasing trust in medical technology. The framework uses a gaze heat map to show the computer where to search for abnormalities and what section of the image requires less attention.
A consensus statement by the Chinese College of Interventionalists promotes CBCT use in liver malignancy therapies, addressing limitations and challenges. The integration of artificial intelligence and technological innovations are expected to refine CBCT's efficacy and safety.
A study of Viking skulls using CT scans reveals a range of diseases including sinus and ear infections, osteoarthritis, and dental diseases. The results provide greater understanding of the health and wellbeing of the Viking population.
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.
A study found racial and ethnic minorities are less likely to receive standard-of-care diagnostic imaging after abnormal screening mammograms compared to white patients. Minority groups were also less likely to have access to same-day biopsy services, despite similar availability of most diagnostic services.
A new study published in The Lancet Digital Health found that AI-supported breast cancer screening increased the detection of early-stage invasive cancers by 24% compared to traditional screening. AI also identified pre-cancerous lesions with a 51% higher rate, without increasing false positives.
A study by Bonn researchers has shown that local Large Language Models (LLMs) can structure radiological findings in a privacy-safe manner, without transferring data to external servers. The open-source LLMs performed equally well as commercial models with advantages of being developed locally.
Mayo Clinic is developing foundation models with Microsoft Research and Cerebras Systems to personalize patient care, accelerating diagnostic time and improving accuracy. These multimodal models integrate radiology images and genomic sequencing data to transform clinical diagnosis and treatment.
A recent study published in Nature Medicine found that AI significantly improves breast cancer detection rates, detecting an additional cancer case per 1,000 women screened. The results show improved efficiency without increasing false positives or unnecessary follow-ups.
A deep learning model developed by researchers at San Diego State University can accurately diagnose chronic obstructive pulmonary disease (COPD) using a single inhalation lung CT scan. The study found that the model performed similarly to traditional two-phase CT measurements, with added clinical data improving accuracy.
Fogarty's research aims to monitor language function and recovery in post-stroke patients using DOT. She hopes to establish the feasibility of brain-computer interfaces to restore inter-personal communication for post-stroke patients.
The study found a significant increase in late-stage breast cancer diagnoses among U.S. women, with annual percentage increases of up to 2.9% between 2004 and 2021. The researchers attribute the trend to factors such as lack of national screening programs, inconsistent guidelines, and increasing obesity rates.
A new research paper published in Oncotarget introduces an innovative AI tool combining CT scans and body composition data to predict severe liver problems in primary sclerosing cholangitis (PSC) patients. The model achieved impressive results, correctly identifying at-risk patients with 97% accuracy.
Teletrix's VIZRAD AR platform simulates ionizing radiation behavior using augmented reality technology, providing a safe and immersive way to learn about radiation without exposure. The platform offers improved training capabilities for workers in radiation-controlled areas.
Researchers have developed a new coronary risk score specifically for women, accurately predicting and categorizing the risk of major adverse cardiovascular events. The findings suggest that this novel approach can help identify high-risk women earlier, reducing the risk of heart attacks and sudden cardiac death.
A new study found significantly higher injury rates among transgender women compared to cisgender women, with increased risk of head, facial, and chest injuries. The findings emphasize the need for timely IPV screening and support for vulnerable populations.
A study found that skeletal muscle loss, particularly in the temporalis muscle, is associated with an increased risk of developing Alzheimer's disease dementia. Participants with smaller temporalis muscle size were more than twice as likely to develop dementia over a median follow-up period of 5.8 years.
Researchers at the University of Bonn are developing an AI foundation model to improve radiology and detect Parkinson's disease earlier. The 'Re-Start PD' project aims to identify the condition before symptoms appear, with potential applications in diagnosis, treatment, and prevention.