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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Influence of AI Decision Support on Radiologists' Performance and Visual Search in Screening Mammography.

Jessie J J Gommers¹, Sarah D Verboom¹, Katya M Duvivier²

¹Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, the Netherlands.

|July 8, 2025

Summary

Artificial intelligence (AI) decision support improved breast cancer detection accuracy in screening mammography. Radiologists using AI spent more time on suspicious areas, indicating a more efficient visual search.

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Area of Science:

Radiology
Medical Imaging
Artificial Intelligence

Background:

Artificial intelligence (AI) decision support may enhance radiologist performance in screening mammography.
Its impact on radiologists' visual search behavior requires further investigation.

Purpose of the Study:

To compare radiologist performance and visual search patterns during mammography interpretation with and without AI decision support.

Main Methods:

Retrospective multireader multicase study involving 12 experienced breast screening radiologists.
Mammograms were evaluated with and without an AI decision support system.
Eye tracking monitored visual search behavior, comparing AUC, sensitivity, specificity, reading time, and fixation patterns.

Main Results:

Mean AUC was significantly higher with AI support (0.97) versus unaided reading (0.93).
Breast fixation coverage decreased with AI, while fixation time in lesion regions increased.
No significant differences were found in sensitivity, specificity, or reading time.

Conclusions:

AI decision support improves breast cancer detection accuracy in mammography interpretation.
AI facilitates a more efficient visual search by directing focus to suspicious regions.
AI shows promise in enhancing screening mammography interpretation.