The role of an artificial intelligence software in clinical senology: a mammography multi-reader study

Purpose To evaluate the diagnostic role of a dedicated AI software in detecting anomalous breast findings on mammography and tomosynthesis images in the clinical setting, stand-alone and as aid of four readers. Methods A total of 210 patients with complete clinical and radiologic records were retros...

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Bibliographic Details
Published in:Radiologia medica 2024-02, Vol.129 (2), p.202-210
Main Authors: Bassi, Enrica, Russo, Anna, Oliboni, Eugenio, Zamboni, Federico, De Santis, Cecilia, Mansueto, Giancarlo, Montemezzi, Stefania, Foti, Giovanni
Format: Article
Language:English
Subjects:
Artificial intelligence
Breast Radiology
Cancer
Diagnostic Radiology
Imaging
Interventional Radiology
Lesions
Medical imaging
Medicine
Medicine & Public Health
Neuroradiology
Radiology
Sensitivity
Software
Ultrasound
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Summary:Purpose To evaluate the diagnostic role of a dedicated AI software in detecting anomalous breast findings on mammography and tomosynthesis images in the clinical setting, stand-alone and as aid of four readers. Methods A total of 210 patients with complete clinical and radiologic records were retrospectively analyzed. Pathology was used as the reference standard for patients undergoing surgery or biopsy, and a 1-year follow-up was used to confirm no change in the remaining patients. The image evaluation was performed by four readers with different levels of experience (a junior and three senior breast radiologists) using a 5-point Likert scale moving from 1 (definitively no cancer) to 5 (definitively cancer). The positivity of mammograms was assessed on the presence of any breast lesion (masses, architectural distortions, asymmetries, calcifications), including malignant and benign ones. A multi-reader multi-case analysis was performed. A p value 
ISSN:1826-6983
0033-8362
1826-6983
DOI:10.1007/s11547-023-01751-1