14 März 2023
HW Koch, M Larsen, H Bartsch, KD Kurz, S Hofvind
Artifcial intelligence in BreastScreen Norway: a retrospective analysis of a cancer‑enriched sample including 1254 breast cancer cases
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To compare results of selected performance measures in mammographic screening for Transpara versus independent double reading by radiologists.
Materials and Methods
In this retrospective study, we analyzed data from 949 screen-detected breast cancers, 305 interval cancers, and 13,646 negative examinations performed in BreastScreen Norway during the period from 2010 to 2018. Transpara scored the examinations from 1 to 10, based on the risk of malignancy. Results from Transpara were compared to screening results after independent double reading. A Transpara score of 10 was set as the threshold. The results were stratified by mammographic density.
A total of 92.7% of the screen-detected and 40.0% of the interval cancers had a Transpara score of 10. Among women with a negative screening outcome, 9.1% had a Transpara score of 10. For women with the highest breast density, Transpara scored 100% of the screen-detected cancers and 48.6% of the interval cancers with a Transpara score of 10, which resulted in a sensitivity of 80.9% for women with the highest breast density for Transpara, compared to 62.8% for independent double reading. For women with screen-detected cancers who had prior mammograms available, 41.9% had a Transpara score of 10 at the prior screening round.
The high proportion of cancers with a Transpara score of 10 indicates the promising performance of Transpara, particularly for women with dense breasts. Results on prior mammograms with a Transpara score of 10 illustrate the potential for earlier detection of breast cancers by using AI in screen-reading.