Benign biopsy effect on artificial intelligence cancer detector in screening mammography - a retrospective study Artificial intelligence cancer detector in a mammography data set

Artificial intelligence (AI) cancer detectors are showing promising results and may soon be used for clinical breast cancer screening in radiology departments. Validation of such programs in different settings is mandatory. This is a retrospective study after the application of a commercial AI cancer detector program to a cancer-enriched mammography screening dataset where 10 889 women with a median age for the study population of 56 years and a range between 40 and 74 years old where included. The program is intended for 2D mammography and it generate a prediction score for tumor presence with a decimal number between 0 and 1, where 1 represented the highest level of suspicion. The AI score median and interquartile range for women who were healthy, who had a benign biopsy, and who were diagnosed with breast cancer, was calculated. For women with a previous benign biopsy, the time between mammogram and the biopsy was stratified. The effect of increasing age was examined using stratified analysis and linear regression modelling. The proportion of healthy women above the AI abnormality threshold (0.4) defined at our hospital was 3.5%, 11% and 84% for healthy women without a benign biopsy, healthy women with a benign biopsy, and for women with breast cancer, respectively (p<0.001) and the AI score correlated positively with increasing age of the women in the cancer group (p<0.05). While 16% of the women who had a benign biopsy after mammography had an AI score above the cut-off point, there were 33% of those when they had their biopsy before the mammography. AI cancer detection systems can reliable be used in a screening setting. Adding information about possible prior benign biopsy and other symptoms can probably improve accuracy and subsequently reduce the workload for radiologists.