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Radiology & Imaging news

Oncology & Cancer

30-year smoking duration-based criteria could increase lung cancer screening

Thirty-year smoking duration-based criteria could reduce eligibility gaps for all races relative to whites, while improving six-year lung cancer detection sensitivity, according to a study published online Dec. 16 in the ...

Oncology & Cancer

New Raman imaging system detects subtle tumor signals

Researchers have developed a new compact Raman imaging system that is sensitive enough to differentiate between tumor and normal tissue. The system offers a promising route to earlier cancer detection and to making molecular ...

Oncology & Cancer

WISDOM trial weighs risk-based cancer screening

University of California, San Francisco investigators led WISDOM, a randomized comparison of risk-based breast cancer screening and annual mammography. Rates of stage ≥IIB breast cancers met a noninferiority threshold under ...

Oncology & Cancer

New technology reduces false positives in breast ultrasounds

New ultrasound technology developed at Johns Hopkins can distinguish fluid from solid breast masses with near perfect accuracy, an advance that could save patients, especially those with dense breast tissue, from unnecessary ...

Radiology & Imaging

AI can detect early signs of aging from chest X-rays

Artificial intelligence may be able to reveal how fast your body is aging by analyzing a chest X-ray, according to a new study published in The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. ...

Diseases, Conditions, Syndromes

Neutron scattering sheds light on lung injuries linked to vaping

Researchers from the University of Windsor are using neutrons at the Department of Energy's Oak Ridge National Laboratory to better understand symptoms associated with e-cigarette/vaping-associated lung injury (EVALI).

Neuroscience

Unified EEG imaging improves mapping for epilepsy surgery

A new advance from Carnegie Mellon University researchers could reshape how clinicians identify the brain regions responsible for drug-resistant epilepsy. Surgery can be a life-changing option for millions of epilepsy patients ...

Diseases, Conditions, Syndromes

Real-time MRI reveals the movement dynamics of stuttering

Researchers at the University Medical Center Göttingen (UMG) and the Max Planck Institute for Multidisciplinary Sciences (MPI-NAT) have succeeded in visualizing the movement patterns of the internal speech muscles of a stuttering ...

Cardiology

AI yields promising results for advancing coronary angiography

New insights from the AI-ENCODE study showed artificial intelligence (AI) successfully allowed the automated extraction of key functional and physiological data from routine angiograms. The results were presented at the Society ...

Other

Radiologists propose actions to combat climate change

A diverse writing group—lead by authors at the University of Toronto—have developed an approach for radiology departments and practices to reduce their greenhouse gas emissions and become more resilient to the effects ...

Inflammatory disorders

PET scans uncover smoldering inflammation in MS patients

A new study from Brigham and Women's Hospital suggests that positron emission tomography (PET) brain scans could reveal hidden inflammation in patients with multiple sclerosis (MS) who are being treated with highly-effective ...

Radiology & Imaging

Advancing high-resolution ultrasound imaging with deep learning

Researchers at the Beckman Institute for Advanced Science and Technology have developed a new technique to make ultrasound localization microscopy, an emerging diagnostic tool used for high-resolution microvascular imaging, ...

Oncology & Cancer

AI software could advance voice box cancer treatment

Artificial intelligence has been found to improve the outcome of patients with voice box cancer, which is a step closer to personalized treatment, new research has revealed.

Radiology & Imaging

New AI method captures uncertainty in medical images

In biomedicine, segmentation involves annotating pixels from an important structure in a medical image, like an organ or cell. Artificial intelligence models can help clinicians by highlighting pixels that may show signs ...