AI-Can Reduce Workload in Breast Cancer Screening

A study published in Radiology determined that an artificial intelligence (AI) algorithm could reduce the digital breast tomosynthesis (DBT) and mammography (DM) workload of radiologists without impacting diagnostic accuracy.

A total of 15,987 DM and DBT examinations (which included 98 screening-detected and 15 interval cancers from the 15,987 women were evaluated.  In comparison with the double reading of the DBT images, AI with DBT would result in 72.5% less workload, noninferior sensitivity, and a 16.7% lower recall rate.  Similar results were obtained for AI and DM. 

AI could obviate over 70% of radiologists' double reading thus enable DBT adoption in breast cancer screening programs.

Improved breast cancer screening and treatment may have saved many lives.

A study using data from the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute published in Cancer estimated as many as 600,000 breast cancer deaths were avoided since 1989 in women aged 40 to 84 years thanks screening and treatment advances. 

The authors report that from 1975 to 1990, female breast cancer mortality rates in the United States increased by 0.4% per year. Since 1990, breast cancer mortality rates have fallen between 1.8% and 3.4% per year, a decrease that is attributed to increased mammography screening and improvements in treatment.

The authors concluded that since 1989, between 384,000 and 614,500 breast cancer deaths have been averted because of widespread use of screening mammography and advances in the treatment of breast cancer.

Breast density assessment varies among radiologists

Sprangue et al published in Annals of Internal Medicine the findings of their study that suggests that radiologists often do not agree on what qualifies as dense breast.

The investigators looked at 216,783 mammograms from 145,123 women aged 40 to 89 years that were interpreted by 83 radiologists in 30 radiology facilities in 4 States.

Overall, 36.9% of mammograms were rated as showing dense breasts. Across radiologists, this percentage ranged from 6.3% to 84.5% (median, 38.7%). Examination of patient subgroups revealed that variation in density assessment across radiologists was pervasive in all but the most extreme patient age and BMI combinations. Among women who had consecutive mammograms interpreted by different radiologists, 17.2% (5909 of 34 271) of them suggested different density rating on the two tests.

The authors concluded because there is wide variation in density assessment across radiologists it is a fact should be carefully considered by providers and policymakers when considering supplemental screening strategies.

Radiologists perform better at screening if they follow up with diagnostic mammograms

Buist et al in their Radiology article analyzed the performance of 96 radiologists at screening mammograms (651 671).  They looked at the effect the number of diagnostic work-ups performed after abnormal findings were found at screening had if the same or a different radiologist interpreted them.

Annually, 38% of radiologists performed the diagnostic work-up for 25 or fewer of their own recalled screening mammograms, 24% for 0–50, and 39% for more than 50. For the work-up of recalled screening mammograms from other radiologists, 24% of radiologists performed the work-up for 0–50 mammograms, 32% performed the work-up for 51–125, and 44% performed the work-up for more than 125.

With increasing numbers of radiologist work-ups for their own recalled mammograms, the sensitivity of screening mammography increased, yielding a stepped increase in women recalled per cancer detected from 17.4 for 25 or fewer mammograms to 24.6 for more than 50 mammograms. Increases in work-ups for any radiologist yielded significant increases in false positive rate and cancer detection rate and a non-significant increase in sensitivity. Radiologists with a lower annual volume of any work-ups had consistently lower false positive rate, sensitivity, and cancer detection rate at all annual interpretive volumes.

They conclude that radiologists may improve their screening accuracy by performing diagnostic work-up for their own recalled screening mammograms.  They recommend arranging for radiologists to work up a minimum number of their own recalled cases in order to improve their accuracy in screening.