The Pulmonary Embolism Reporting and Data Systems (PE-RADS) framework provides a simple, 0-4 grading scale for classifying acute pulmonary embolism using CT and MR angiography. The system aims to improve communication and patient care with standardized terminology and risk stratification.
Researchers successfully acquired diagnostic X-rays in space, expanding crew health capabilities and paving the way for mission-critical non-medical tasks. The study found that portable X-ray machines are feasible in space, with no significant differences in image quality between pre-flight and inflight images.
Researchers used AI to analyze mammograms and found that women who developed breast cancer had increasing risk scores over time, while those who did not had stable scores. The study suggests that image-based AI risk scores can predict future breast cancer risk in women without a known genetic mutation or family history.
A new study published in Radiology found that embolization of abnormal blood vessels using rapidly resorbable gelatin-based microspheres is safe and effective in providing significant, lasting pain relief and functional improvement for patients with osteoarthritis-related knee pain. The procedure significantly reduces inflammation and ...
Researchers found that long-term exposure to air pollution is associated with more advanced coronary artery disease, even at moderate levels. The study analyzed data from 11,128 adults and found that exposure to fine particulate matter and nitrogen dioxide increased the risk of coronary artery disease.
A study published in Radiology found that three commercially available AI-based computer-assisted detection (AI-CAD) systems can identify early mammographic signs of breast cancer up to 6 years before diagnosis. This could help radiologists spot potential future cancers and allow for earlier intervention.
A study published in Radiology used AI to analyze whole-body MRI scans from over 66,000 participants, revealing that skeletal muscle quality is a strong predictor of diabetes, major cardiovascular events, and mortality. The researchers also found that high visceral fat and low skeletal muscle were associated with increased risks of the...
Researchers used MRI to analyze muscle composition in 11,348 participants and found that higher intermuscular fat and lower muscle mass were associated with increased cardiometabolic risk factors. Lean muscle mass was only protective against these risks in men, while women's muscle mass declined after age 40.
A large sample of US Special Operations Forces personnel were found to have a higher prevalence of intracranial aneurysms with greater repeated blast exposure. The study suggests that repeated low-level blast exposure during years of service may leave a measurable vascular signature in the brain.
Researchers found a diet high in ultra-processed foods is associated with higher amounts of fat stored inside thigh muscles. This increased intramuscular fat may increase the risk for knee osteoarthritis. The study suggests that addressing obesity and improving dietary quality are crucial to preserving muscle health.
The study found that AI-enhanced single-shot cine MRI produces better image quality compared to conventional cine MRI, particularly in participants with arrhythmia. The technique demonstrated a 100% success rate for image acquisition, outperforming conventional cine sequences.
A study found that deepfake X-rays can be indistinguishable from authentic images, posing a risk to patient diagnoses and digital medical records. Radiologists and AI models struggled to detect synthetic images, with accuracy ranging from 58% to 92%. Experts recommend implementing advanced digital safeguards to prevent tampering.
A nationwide Danish study comparing outcomes between patients treated with minimally invasive ablation and surgery found no difference in cancer progression but more frequent local recurrence of the disease following ablation. Ablation patients had shorter hospital stays and fewer complications.
Researchers developed a new MRI technique that simultaneously displays heart tissue and blood flow, enabling precise planning for surgical repairs. This innovation provides high-quality flow images without radiation, making it essential for repeated imaging in children.
A study published in Radiology found that photon-counting CT reduced radiation exposure by 66.34% and improved image quality compared to conventional CT in lung cancer patients. The technology also showed fewer adverse reactions, including contrast-induced acute kidney injury.
A new study discovered two previously unidentified fat distribution types associated with extensive gray matter atrophy and accelerated brain aging in men and women. Individuals with 'pancreatic-predominant' and 'skinny fat' profiles showed increased risk of neurological diseases, cognitive decline, and brain health issues.
A large-scale study of over 11,000 adults found that even low-level air pollution is associated with advanced coronary artery disease, often before symptoms appear. Long-term exposure to fine particulate matter and nitrogen dioxide was linked to higher calcium scores and more severe narrowing of the arteries in both men and women.
A new study uses ultrasound to detect vascular complications from cosmetic fillers, such as absent blood flow to perforator vessels. Clinicians can now target exact areas for treatment, reducing the need for blind injections and minimizing complications like blindness and stroke.
Victims of intimate partner violence with suicidal behavior show distinct injury patterns on medical imaging, including head, face, neck and upper limb injuries. The study aims to improve screening and intervention for vulnerable populations.
A new study published at the Radiological Society of North America annual meeting found that individuals with obesity have a 95% faster increase in Alzheimer's disease biomarkers compared to non-obese individuals. Blood tests were more sensitive than PET scans in capturing the impact of obesity on Alzheimer's pathology.
A new study using advanced imaging found that abdominal obesity is associated with more harmful changes in heart structure than overall body weight alone. The research, presented at the Radiological Society of North America annual meeting, suggests that male patients may be more vulnerable to structural effects of obesity on the heart.
A study of seven outpatient facilities found that 20-24% of all breast cancers diagnosed between 2014 and 2024 were in women aged 18-49. Invasive cancer cases accounted for 80.7%, often with aggressive types, challenging age-based screening cutoffs.
The study found significant differences in injury patterns between men and women, with men experiencing more ACL tears and women more frequent meniscal and MCL tears. These findings can help radiologists tailor imaging protocols and risk assessments to optimize patient outcomes.
Repeated head impacts in professional boxers and mixed martial artists can lead to cognitive decline and neurodegenerative disorders. The glymphatic system, responsible for clearing waste from the brain, is compromised in fighters with higher numbers of knockouts.
A new AI image-only model has been shown to provide stronger and more precise risk stratification for five-year breast cancer prediction than traditional breast density assessment. The model was trained on 421,499 mammograms and showed a fourfold higher cancer incidence in high-risk women compared to those with average risk.
Researchers used MRI 3D mapping to analyze changes in gluteus maximus shape over time and its association with type 2 diabetes. The study found that men showed muscle shrinkage, while women showed enlarged muscle, highlighting sex-specific differences in response to insulin tolerance.
Researchers developed a deep learning model to measure adrenal gland volume on existing CT scans, identifying the first imaging biomarker of chronic stress. The AI-derived biomarker correlates with validated stress questionnaires, cortisol levels, and future cardiovascular outcomes.
Researchers found that higher muscle mass combined with a lower visceral fat to muscle ratio tracks with a younger brain age. Building muscle and reducing visceral fat are actionable goals for improving brain health. The study used whole-body MRI and AI algorithms to quantify muscle volume, fat tissue, and brain age.
A study published in Radiology found that soccer fans' brain activity is triggered by positive and negative emotions when watching their favorite team play. The researchers used fMRI to examine the brain's response to goal sequences from matches, revealing patterns of neural activation associated with social identity and fanaticism.
Researchers developed an AI tool to identify women at higher risk of developing interval breast cancers, which have a worse prognosis. The tool predicted 42.4% of interval cancers for women with the top 20% scores, suggesting it could optimize breast cancer screening programs by identifying those who need supplemental imaging.
A new study examines the radiology department's experience during a mass casualty terror attack in southern Israel. Researchers found that rapid staff mobilization, versatile imaging resources management, and AI-enabled safety checks were crucial in guiding clinical decisions.
A new study found that combining molecular breast imaging (MBI) and digital breast tomosynthesis (DBT) increases invasive cancer detection while moderately increasing recall rates. MBI detected an additional 6.7 cancers per 1,000 screenings in women with dense breasts.
A new AI-powered deep learning model has been shown to accurately estimate the malignancy risk of lung nodules, achieving high detection rates while reducing false-positive results. The model outperformed existing probability-based tools in a retrospective study, with a relative reduction of 39.4% in false positives.
A special MRI technique detecting brain iron levels can predict mild cognitive impairment and cognitive decline in cognitively unimpaired older adults. Elevated brain iron is linked to higher risk of developing Alzheimer's disease and faster cognitive decline.
Emphysema detected on low-dose chest CT scans in asymptomatic adults increases mortality risk over a 25-year follow-up period. The study found that emphysema severity is associated with higher COPD and cardiovascular disease mortality rates, suggesting it as a distinct disease entity linked to poorer health outcomes.
A new AI hybrid reading strategy for screening mammography reduces radiologist workload by 38% while maintaining comparable cancer detection and recall rates. The strategy incorporates uncertainty quantification, allowing AI to provide certainty estimates for predictions.
Researchers evaluated over 1,500 AI algorithms for detecting breast cancers on mammography images, achieving median rates of 98.7% specificity and 27.6% sensitivity. Combining top-performing algorithms resulted in sensitivity boosts to 60.7% and 67.8%, comparable to average screening radiologists.
A new AI algorithm has been shown to detect nearly one-third of interval breast cancers missed at screening using digital breast tomosynthesis (DBT), according to a study published in Radiology. The algorithm improved the performance of DBT, reducing interval cancers.
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 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.
An AI model accurately detected tumor locations and outperformed benchmark models in detecting breast cancer, according to a study published in Radiology. The model learned a robust representation of benign cases to better identify abnormal malignancies, even with underrepresented data.
A study published in Radiology found that AI decision support systems improve breast cancer detection accuracy and visual search patterns among radiologists. With AI assistance, radiologists spend more time examining regions with actual lesions, leading to better performance and efficiency.
Research using cardiac MRI found that long-term exposure to air pollution is associated with early signs of heart damage, including diffuse myocardial fibrosis. The study suggests that fine particulate matter in the air may contribute to changes in the heart structure, potentially setting the stage for future cardiovascular disease.
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.
Researchers found that carotid artery plaques can undergo changes over time, becoming more complex and increasing the risk of internal bleeding. This study emphasizes the importance of ongoing plaque monitoring and proactive risk factor management to prevent stroke.
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.
Researchers found corticosteroid injections accelerated structural knee degeneration, while hyaluronic acid injections slowed down damage. The study challenges common clinical practice and suggests alternative pain management strategies for patients with osteoarthritis.
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.
The article highlights key pitfalls in evaluating AI algorithmic biases in radiology, such as the lack of representation in medical imaging datasets and inconsistent demographic definitions. To address these issues, radiologists recommend collecting and reporting more demographic variables and establishing standard notions of bias eval...
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.