Diagnostic screening programs help catch cancer, abnormalities or other diseases before they reach an advanced stage, saving lives and healthcare costs. Screening programs include, lung, breast, prostate, and cervical cancer, among many others.
The COlorectal Cancer detection with AI, or COCA, model is a cost-effective, scalable solution that turns routine CT scans into opportunistic exams that can be used to proactively identify CRC.
Two respected radiology organizations have issued a stark warning on the new recommendations, stating that they risk confusing patients and “may contribute to thousands of additional breast cancer deaths each year.”
New findings from a large CT lung cancer screening dataset reveal that a substantial number of patients have significant incidental findings visible on their scans.
Decreased screening rates among different subgroups highlight the ongoing need for outreach strategies that target vulnerable populations, experts contend.
The ACR hopes these changes, including the addition of diagnostic performance feedback, will help reduce the number of patients with incidental nodules lost to follow-up each year.
Ultrasound is routinely used to screen for HCC. However, its utility is limited by numerous factors, including patient body habitus, operator experience and certain liver conditions, all of which contribute to decreases in sensitivity.
In conjunction with prevention efforts, the introduction of screening examinations has resulted in a reduction of nearly 6 million cancer-related deaths since 1975.
Breast density is most often discussed within the context of cancer risk, but new research suggests that it also could be used as a marker of cardiometabolic health.
The newly cleared offering, AutoChamber, was designed with opportunistic screening in mind. It can evaluate many different kinds of CT images, including those originally gathered to screen patients for lung cancer.