Comparative analysis of the use of medical decision support systems in the analysis of mammographic studies in the Krasnoyarsk region

Abstract

Aim: To evaluate the effectiveness of artificial intelligence (AI) technologies in interpreting mammographic images using a comparative analysis of reports from primary care radiologists and specialists from the reference center of the of the A.I. Kryzhanovsky Krasnoyarsk Territorial Clinical Oncology Dispensary (KKKOD) when interpreting mammographic studies conducted in the Krasnoyarsk Territory.

We conducted a retrospective analysis of 1012 mammographic examinations performed in March-May 2025, sent to the KKKOD reference center according to the established procedure. The reports from KKKOD reference center and primary care radiologists, as well as the results of two AI services using the BI-RADS scale, were evaluated. Statistical processing was performed using StatTech 4.0.6, and a discordance index was calculated for clinical cases that impact subsequent patient management.

Results: in the Krasnoyarsk Region, the introduction of a second artificial intelligence (AI) service for mammography interpretation by radiologists led to an increase in the diagnostically challenging BI-RADS 3.4 categories, increasing the workload of the KKKOD reference center by 29.5%. However, the discordance rate remained unchanged (27.5%) compared to 2024, when only one AI service was used in the region. A retrospective analysis revealed differences in the performance of the two AI services when interpreting mammography examinations.

Conclusion: the use of multifunctional AI-based digital platforms improves the quality of disease prevention and diagnosis, reducing the likelihood of medical errors. However, the simultaneous use of several services increases the workload of specialists due to the need to analyze multiple interpretation options.