Since its introduction in the 1970s, computed tomography has been a mainstay of radiology. Its overlay-free representation of body structures and the rapid availability of images make CT indispensable in the diagnostic assessment of numerous diseases, especially in emergency medicine. Modern CT systems not only offer innovative procedures for better image quality, but also reduce radiation exposure.
Can CT-derived fractional flow reserve (FFR-CT) be used in patients with angina to predict future major cardiovascular events? A novel AI-based approach for CCTA analysis yields promising results.
Many women over 50 schedule mammograms for breast cancer but miss out on CT lung cancer screenings they're also eligible for. Targeted outreach coul help change this, a new study shows.
Dunlee will present its portfolio of integrated imaging solutions at RSNA 2025 in Chicago, Illinois. The company will demonstrate technologies for diagnostic and therapeutic imaging applications, including developments in Ultra-High Resolution and Photon Counting CT (UHR & PCCT), components for MRI-guided breast biopsies, and onboard imaging systems for radiation therapy.
In a CT scan of the lungs, accidentally inhaled objects can be extremely subtle and easy to miss, even for experienced clinicians. A new AI model acts as a “second set of eyes” to help detect hidden cases.
Cardiac imaging is evolving, and new techniques continue to uncover the secrets of the heart for cardiologists who know how to use them. At the ESC 2025 Congress in Madrid, four experts explored cutting-edge developments across different modalities. Ranging from AI-assisted ultrasound image acquisition and accelerated MRI protocols to advanced prognostic tools for CT and nuclear imaging, these…
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
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.
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).
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.
By analyzing CT images with 3D software, researchers demonstrated that small liver tumors can be successfully treated using ablation. This could enable more confident use of ablation treatments.
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.
New research demonstrates CT colonography outperforms stool DNA testing in both clinical effectiveness and cost savings for colorectal cancer screening.
Lung cancer is the leading cause of cancer death in the EU, yet no organized screening program exists to detect the disease before symptoms appear. This September, France will strike back with an ambitious pilot program that could boost European lung cancer screening. Professor Marie-Pierre Revel presented the details at the French Thoracic Imaging Society Spring Days in Marseille, highlighting…
Survival rates for pancreatic cancer rise drastically the earlier it is detected, but early-stage tumors are notoriously difficult to spot. A new AI-powered diagnostic system is set to improve this.
A deep learning model was able to predict future lung cancer risk from a single low-dose chest CT (LDCT) scan, according to new research published at the ATS 2025 International Conference.
Results of a new retrospective study demonstrate the potential of a novel, CT-based deep learning-driven tool to enhance liver cancer diagnosis, treatment planning, and response evaluation.
To reduce the radiation exposure for patients undergoing frequent CT scans for pneumonia diagnosis, deep learning-based denoising of ultra-low dose CT presents a viable alternative.
A new study reveals that AI can accurately rule out negative low-dose CT (LDCT) scans, potentially reducing the workload of radiologists in lung cancer screening by up to 79%.
Anatomically accurate 3D-printed phantoms for CT imaging and AI training show promise as an alternative to cadavers. The new technology allows for patient-specific phantoms with realistic radiopacity.
