Promising research on 4D mammo | Confusion over screening ages | BAC notifications | AI determines need for supplemental imaging

The 4D system harnesses X-ray diffraction to measure molecular-level signatures of disease; these tissue “fingerprints” could help providers diagnose breast cancer in its earliest stages.

New findings support the routine use of deep learning-based risk assessments, as this method can decrease subjectivity, reduce unnecessary imaging and improve diagnostic accuracy. 

It may be more than anxiety and forgetfulness to blame for women missing their scheduled mammograms, according to new survey data. 

New findings suggest that 99mTc-maraciclatide can help physicians more accurately identify endometriosis on imaging.

The responses also suggested that a significant amount of women believe mammograms start before 40, highlighting a gap in screening policy knowledge.

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.”

HB 1364, a bill some radiologists pushed back against, is headed to the Governor’s desk to be finalized. It is set to take effect on Oct. 1. 

NCCN suggests that 5-year future breast cancer risk assessments based on routine mammograms should be integrated into standard practices. 

EndomAI was developed to support radiologists in detecting and quantifying endometriosis on magnetic resonance imaging scans. 

The filler contains hydroxylapatite microspheres, which may be visible on medical imaging.