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 second of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD discuss how to handle disagreements with adjunctive AI in breast imaging, whether to include AI assessments in PACS, and whether patients should pay for the use of adjunctive AI.
In the first of a three-part podcast episode, Wendie Berg, MD, PhD, FACR, FSBI, Manisha Bahl, MD, and Amy Patel, MD share insights on the utility of AI in breast imaging with respect to potential advantages, current concerns and future directions.
Assessing breast MRI scans, pathology and clinical data, the AI-powered TumorSight Risk software reportedly provides five- and 10-year risk for breast cancer recurrence for women with HR+, HER2-negative stage I-IIIA breast cancer.
Incorporation of pseudocapsule presence into a modified Clear Cell Likelihood Score (m-ccLS) was associated with a greater than 11 percent higher AUC in differentiating benign and malignant renal masses on mpMRI, according to a new study.