GLP-1 receptor agonists are widely prescribed for individuals with diabetes and weight loss. However, these medications may adversely affect the interpretation of cancer imaging, new research finds.
Using PET/CT imaging, researchers discovered that the biological activity of visceral fat may drive the progression of endometrial cancer, offering a novel angle for diagnosis and treatment.
New insights on the mechanisms that cause “brain fog” in Long Covid patients: Researchers use a specialized brain imaging technique to identify a potential biomarker and therapeutic target.
This year, the Journées Francophones de Radiologie (JFR) will carry a clinical ambition as simple as it is essential: to shine a spotlight on those who are often overlooked. Under the presidency of Professor Mathieu Lederlin, thoracic radiologist at Rennes University Hospital, vulnerable patients will be at the heart of the annual meeting of the French Society of Radiology that will unfold…
Study of 3.7 million children reveals small but significant increased risk of blood cancers from medical imaging radiation, with CT scans posing highest risk
Using AI to help detect one of the leading killers of women worldwide: A new machine learning model can successfully predict heart disease risk in women by analysing mammograms.
Misinterpreting the malignancy risk of lung nodules often results in high false-positive rates, unnecessary follow-ups, increased patient anxiety and healthcare costs. A new study suggests that AI can fix this.
Imaging specialist Fujifilm Healthcare Europe and the research and training institute IRCAD France have announced a collaboration focused on surgical education and research programs.
Canon announces the launch of the Aquilion One / Insight Edition 160, a new addition to its computed tomography (CT) portfolio. The new system made its debut at Röntgenveckan (Stockholm, Sweden).
AI may be effective at detecting advanced breast cancer in mammograms, but current models still lack reliability. New research from Korea suggests that up to 14% of invasive cases are missed.
Researchers have developed a machine learning algorithm that uses cardiac MRI images to help identify breast cancer patients who may be at risk of cardiotoxicity during cancer treatment. The research, led by cardiologist Dr Paaladinesh Thavendiranathan from Toronto General Hospital University Health Network, was presented at the European Society of Cardiology's Cardio-Oncology Conference in…
An advanced imaging method that uses the natural glow of tissues could help detect subtle differences in the tissue’s biochemistry, offering a way to earlier detect colorectal cancer via endoscopy.
New AI-powered solutions for cardiac ultrasound: Italian medical imaging specialist Esaote will be present at the European Society of Cardiology (ESC) Congress 2025, which starts today (29th August) in Madrid.
Patient communication facilitated by chatbots, image quality optimized by machine learning: Artificial intelligence (AI) is entering radiology at breakneck speed, transforming the specialty almost beyond recognition. So, how will the future of diagnostic imaging under AI look like, and which role will humans still play in it? At the ECR congress in Vienna, experts explored the societal and…
Postpartum hemorrhage is a leading cause of maternal death. A new method could help predict which women experiencing severe bleeding after giving birth most likely need life-saving interventions.
Henkjan Huisman has been appointed Professor of AI Guided Imaging at Radboud UMC/Radboud University. With a focus on AI applications in medical imaging, his goal is to provide better and more affordable care.
Researchers report they have built a new non-toxic and non-radioactive handheld device that uses the unique properties of diamonds to diagnose metastasized breast cancer.
Mammography image interpretation AI models are unreliable – but so are human readers. A new hybrid strategy could reduce radiologist workload by 38% without compromising diagnostic efficacy.
Using ultrasound imaging, researchers measure the wall thickness of the aorta from within a patient's body, to predict with higher accuracy whether an aneurysm will rupture or not.
Gadolinium-based contrast agents enhance visibility but also pose a significant health risk. A new AI-powered virtual MRI imaging technique is designed to offer a safer diagnostic approach.
More clinically relevant tumors detected at an earlier stage and at lower costs: New research finds that AI can replace the second radiologist in the Dutch breast cancer screening program.
Medical imaging methods are often affected by background noise, which can obscure fine anatomical details. A new approach to solve this problem draws inspiration from quantum mechanics.
Denoising of diffusion-weighted MRI data creates sharper images – but does it actually lead to better diagnostic results? Researchers explored the impact of noise removal on detecting abnormalities.
CT imaging is important to detect residual lung abnormalities after a Covid-19 infection. To avoid confusion with interstitial lung diseases, experts from 14 countries published a best-practice guide.
By directing radiologists' attention to potentially suspicious areas, AI can help spot more lesions indicative of breast cancer in mammograms. This is suggested by a new study.
