In the latest episode of her Breast Imaging in Focus series, Manisha Bahl, MD, MPH, FSBI, discusses new research comparing mammography-based AI models for breast cancer detection and short-term risk prediction.

Use of the AI-enabled slab technology from reconstructed DBT imaging led to a 7.4-second mean reduction in reading time in a new study involving 391 cases and 15 reviewing radiologists.

A Kaiser score > 5 with breast MRI demonstrated a 97 percent sensitivity and 87.9 percent specificity for predicting malignancy in patients with BI-RADS 0 or 4 presentations on mammography and breast ultrasound, according to a new study.

In the third of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD discuss recent developments with autonomous AI in breast imaging and share their perspective on the overall potential of AI to help mitigate the radiologist shortage.

Catch up on the top radiology content of the past week.

The use of adjunctive CT bone reading software in women with breast cancer detected between 8 to 22 percent more metastatic lesions for reviewing radiologists and reduced CT interpretation time by 50 percent or more, according to a new study.

Catch up on the top radiology content of the past week.

In a recent interview with Diagnostic Imaging, Eliad Josephson discussed key attributes of the HLTH USA conference, AI trends and an ongoing shift of emphasis on the development of predictive technologies with diagnostics at center stage.