Clinical Research Directory
Browse clinical research sites, groups, and studies.
Artificial Intelligence Integration in Breast Cancer Screening: The ANIHTA Study
Sponsor: Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Summary
The goal of this observational study is to evaluate how artificial intelligence (AI) can be integrated into an organized breast cancer screening program for women aged 50-74 years undergoing mammography screening. The main questions it aims to answer are: * Can an AI-based workflow that identifies selected mammograms for review by a third radiologist improve or maintain the cancer detection rate compared with the current AI-supported double-reading workflow? * How would this AI-based workflow affect recall rates, biopsy referrals, false-positive results, interval cancers, radiologists' workload, and the number of cases requiring third-reader review? Researchers will compare the currently used screening strategy, in which mammograms are independently read by two radiologists with AI support, with an alternative AI-based strategy reconstructed using a target trial emulation approach. In the alternative strategy, predefined AI score thresholds will be used to identify selected cases for an offline review by an independent third radiologist. Participants will not be asked to undergo additional examinations or changes to their clinical care. Researchers will use routinely collected mammography screening data, AI scores, radiologists' readings, screening outcomes, and follow-up information. The alternative AI-based screening workflow will be evaluated retrospectively and will not affect participants' screening results or clinical management.
Official title: Introducing Artificial Intelligence in Personalised Breast Screening Programs: a Health Technology Assessment
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
200075
Start Date
2026-11-01
Completion Date
2029-10-31
Last Updated
2026-10-19
Healthy Volunteers
No
Conditions
Interventions
Artificial intelligence-based software for mammography
Lunit INSIGHT MMG is an artificial intelligence-based software for mammography that generates a continuous malignancy score ranging from 0 to 100. In the retrospective breast screening cohort, AI scores will be used to assess diagnostic performance and to analytically reconstruct alternative AI-supported screening workflow strategies. Strategy A represents the observed routine AI-supported double-reading workflow without third-reader arbitration. Strategy B represents an emulated AI-triggered workflow in which prespecified AI score thresholds (AIpt and AInt) are used to identify selected examinations for offline third-radiologist assessment or direct recall classification. Strategy B will be reconstructed retrospectively and will not be prospectively applied to clinical decision-making or patient management.
Discrete Choice Experiment on AI-Supported Breast Cancer Screening
Healthcare professionals involved in the organized breast cancer screening program will complete a structured Discrete Choice Experiment (DCE) designed to assess preferences regarding the organizational and clinical integration of artificial intelligence into breast cancer screening. The DCE will evaluate acceptability, usability, trust in AI, perceived utility, satisfaction, and preferences regarding alternative characteristics of AI-supported screening workflows. The survey is observational and does not modify clinical practice or patient management.
Locations (1)
Azienda Sanitaria Locale Roma 2
Rome, Lazio, Italy