Women’s imaging encompasses many radiology procedures related to women and the diseases that are most prevalent to women such as breast cancer or gynecological issues. Mammogram, breast ultrasound, breast MRI and breast biopsy are the most commonly used procedures.
A team of experts determined that correlating masses initially detected on MRI are significantly more likely to result in a cancer diagnosis than other common findings.
This latest research further confirms that breast MRI not only detects tumors that mammography cannot, but it also spots invasive cases that pose greater risks to patients.
Experts, medical organizations and advocates alike are coming forward saying that the new guidelines “do not go far enough,” particularly when it comes to addressing the screening needs of certain patients.
This psychological phenomenon describes the notion that people believe they can make better predictions or decisions once they have been exposed to new information on the subject, often causing them to overestimate their own abilities.
The USPSTF’s update suggests that women should screen every other year, but the group's own modeling studies have cited the benefits of annual screening.
These findings warrant serious consideration by physicians caring for pregnant women in the future, as the link between poor mental health and placental development remains “underappreciated.”
Researchers suggested these findings could be used as a noninvasive tool in creating more personalized treatment options for patients facing a cancer diagnosis that is invasive in nature.
Breast density is known to drop over time, but the rate at which density decreases merits special attention, as it could be associated with a woman’s chance of developing cancer.
A team of experts recently developed the new system to differentiate between malignant and benign "second look" lesions on MRI for women with known breast cancer.
Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.
Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.
"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.