The use of AI software for digital breast tomosynthesis (DBT) facilitated a higher cancer detection rate and over double the PPV for exams with abnormal interpretation, according to a newly published study.

In a second part of a new podcast episode on recently published research on projected radiation-induced cancers from computed tomography (CT) scans, Mahadevappa Mahesh, MS, Ph.D., and Joseph Cavallo, M.D., offer current perspectives on cardiac CT dosing, AI advances and the importance of teamwork in ensuring appropriate dosing for CT.

Is there an achievable balance between leisurely relaxation and cramming must-do sightseeing into a short amount of time?

In a new podcast, Mahadevappa Mahesh, MS, Ph.D., and Joseph Cavallo, M.D., share their perspectives on recently published research looking at projections for future radiation-induced cancers from computed tomography (CT) scans.

While AI-enabled hippocampal segmentation on MRI offered a 95 percent AUC for differentiating between Alzheimer’s disease and normal controls in a 27-study meta-analysis, it offered significantly lower sensitivity and specificity in differentiating mild cognitive impairment.

For DBT breast cancer screening, 47 percent of radiologist-only flagged false positives involved mass presentations whereas 40 percent of AI-only flagged false positive cases involved benign calcifications, according to research presented at the recent American Roentgen Ray Society (ARRS) conference.