Diagnostic Imaging's Weekly Scan: March 12-March 18
Catch up on the top radiology content of the past week.
Diagnostic Imaging's Weekly Scan is your chance to catch up on the latest radiology content, from new research and device news to the latest case quizzes and conference reports. Review the slideshow below to see this week's top content:
Diagnostic Imaging's Weekly Scan: March 12-March 18
Click the arrows above to view top radiology content from the past week.
Mammography Study Shows 22 Percent Higher Incidence of Dense Breasts in Women with a Family History of Breast Cancer
Newly published retrospective research involving a large database of premenopausal women in Korea showed that women were 64 percent more likely to have dense breasts if their mother and a sister had breast cancer. READ MORE
Seven Takeaways from Best Practice Recommendations for Incidental Radiology Findings in the ER
Noting that computed tomography (CT) scans are obtained for more than 30 million emergency department (ED) patients annually and that 31.3 percent of ED CT scans reveal incidental findings, representatives from the American College of Radiology (ACR) and the American College of Emergency Physicians (ACEP) recently collaborated on best practice recommendations for addressing incidental imaging findings in EDs. READ MORE
Large Mammography Study Reaffirms Benefits of Digital Breast Tomosynthesis
In a recent interview, Emily Conant, M.D., discussed findings from a large multicenter study highlighting the benefits of digital breast tomosynthesis (DBT) in breast cancer screening. READ MORE
Illuccix Gets Expanded FDA Approval for Imaging of Metastatic Prostate Cancer
The expanded indication could facilitate improved access to imaging for patients with metastatic prostate cancer who are candidates for radioligand treatment. READ MORE
Meta-Analysis Finds High Risk of Bias in 83 Percent of AI Neuroimaging Models for Psychiatric Diagnosis
In a review of 555 neuroimaging-based artificial intelligence (AI) models for the diagnosis of psychiatric disorders, researchers found that nearly 72 percent of the AI models had an inadequate sample size and over 99 percent were insufficient at handling data complexity. READ MORE
