Diagnostic Imaging

Breast cancer screening using digital breast tomosynthesis has risen rapidly in the United States, but that isn’t the case in all regions or across all institutions, according to a new study published in Current Problems in Diagnostic Radiology.

Gadolinium-based contrast agents (GBCAs) can often bring out the best in MRI, but they’re controversial and thus increasingly avoided. A pilot study in Germany shows how an algorithm might substitute for an injection to track tumors of the brain and spinal cord (aka gliomas).

A deep neural network platform can help radiologists detect abdominal aortic aneurysms (AAAs) on CT images, and is especially helpful in clinically challenging cases, according to research presented at the SIIM annual conference.

Aided by augmented reality, AI and portable neuroimaging technology, physicians may soon be able to tease out images of patients’ brains—right there in the doctor’s office—to see how much pain each patient is suffering.

A higher level of background parenchymal enhancement (BPE) measured during breast MRI is associated with the presence of breast cancer in women at high risk of breast cancer but not in women with average risk, according to a new study.

Supplemental training can improve radiologists’ performance in reading screening mammograms, according to a recent study.

Health officials south of the border may soon be able to fight a nasty disease using just their smartphones and an AI tool for reverse image searches.

A recent study validating the 2017 version of the ultrasound Liver Imaging Reporting and Data System (US LI-RADS) for detecting hepatocellular carcinoma (HCC) identified a few limitations in its scoring.

The American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) was originally created to improve patient management and avoid unnecessary fine needle aspiration biopsy in patients with thyroid nodules. However, its clinical use is still questioned.

Radiology is the medical specialty most conducive to clinical AI applications. After all, the pre-AI technique of computer-aided detection has been used in mammography since 1998, for example. So it shouldn’t come as a surprise to find AI “app stores” rising in radiology.

Cardiac MRI can detect cocaine’s impact on the cardiovascular system and help differentiate between a wide range of heart diseases, according to a new literature review study published in Radiology: Cardiothoracic Imaging.

Researchers created and validated a machine learning model using features taken from baseline, laboratory, electrocardiography (ECG), echocardiography and cardiovascular resonance (CMR) imaging data.