Large language model–based simplification of breast imaging reports: a prospective multicentre study with 2965 patient-based evaluations

OBJECTIVE: To compare patient perceptions of radiologist-written and artificial intelligence (AI)-generated simplifications of breast imaging reports in terms of simplicity, comprehensibility, empathy, and overall preference. MATERIALS AND METHODS: In this prospective multicentre survey-based study, 10 anonymized breast imaging reports (5 ultrasound, 5 mammography; one BI-RADS category 1-5 per modality) were simplified by ChatGPT-4 within a 50-word limit. After assessment by a panel of 20 physicians, paired radiologist-written and AI-generated reports were evaluated by 314 patients (2965 evaluations) who rated simplicity, comprehensibility, and empathy on a 5-point Likert scale and indicated their preferred report. The origin of each report was concealed, and each pair was presented in randomized order. Univariable and multivariable mixed-effects logistic regression analyses were performed to identify factors associated with preferring AI-generated reports. RESULTS: AI-generated reports were preferred in 63.3% (1876/2965) of evaluations. High simplicity and comprehensibility scores (4-5) were more frequently assigned to AI reports than to radiologist-written reports (70.0% vs 43.4% and 68.1% vs 40.4%, respectively). In multivariable analysis, higher comprehensibility was the strongest predictor in both directions: higher comprehensibility of AI-generated reports increased the odds of preferring AI (score 4: adjusted OR 1.87, 95% CI 1.08-3.23, p = 0.025), while higher comprehensibility of radiologist-written reports reduced them (score 4: adjusted OR 0.45, 95% CI 0.29-0.69, p < 0.001). Preference for AI-generated reports showed a non-significant trend toward increase with educational level. CONCLUSION: AI-generated breast imaging reports were preferred by most patients and perceived as clearer, supporting a complementary and supervised use of AI-generated summaries. KEY POINTS: Question Patients increasingly access their own radiology reports, yet standard radiologist-written reports are often difficult to understand, highlighting the need for patient-friendly alternatives. Findings In this study, AI-generated breast imaging reports were preferred by patients in 63.3% of evaluations, with comprehensibility emerging as the strongest predictor of preference. CRITICAL RELEVANCE STATEMENT: AI-generated breast imaging reports were preferred by most patients and received higher ratings for simplicity and comprehensibility than radiologist-written reports, supporting a supervised and complementary use of AI-generated summaries in clinical breast imaging.

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Journal
Insights into Imaging
Published
2026-11-02
DOI
https://doi.org/10.1186/s13244-026-02423-0
Primary Topic
Artificial Intelligence in Healthcare and Education
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article
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article

Large language model–based simplification of breast imaging reports: a prospective multicentre study with 2965 patient-based evaluations

Sonia Santicchia, Giulia Querques, Maria Iodice, Alessandro Liguori et al.
8 links
Insights into Imaging
Artificial Intelligence in Healthcare and Education
article

Large language model–based simplification of breast imaging reports: a prospective multicentre study with 2965 patient-based evaluations

Sonia Santicchia, Giulia Querques, Maria Iodice, Alessandro Liguori, Mario R. Pannarale, Filippo Pesapane, Andrea Cozzi, Veronica Magni, Gianpaolo Carrafiello, Marta Montesano, Maurizio Cè, Sveva Mortellaro, Luca Nicosia, Matilde Pavan, Serena Carriero, Giulia Quercioli, Maria Cosentino
article en

Abstract

OBJECTIVE: To compare patient perceptions of radiologist-written and artificial intelligence (AI)-generated simplifications of breast imaging reports in terms of simplicity, comprehensibility, empathy, and overall preference. MATERIALS AND METHODS: In this prospective multicentre survey-based study, 10 anonymized breast imaging reports (5 ultrasound, 5 mammography; one BI-RADS category 1-5 per modality) were simplified by ChatGPT-4 within a 50-word limit. After assessment by a panel of 20 physicians, paired radiologist-written and AI-generated reports were evaluated by 314 patients (2965 evaluations) who rated simplicity, comprehensibility, and empathy on a 5-point Likert scale and indicated their preferred report. The origin of each report was concealed, and each pair was presented in randomized order. Univariable and multivariable mixed-effects logistic regression analyses were performed to identify factors associated with preferring AI-generated reports. RESULTS: AI-generated reports were preferred in 63.3% (1876/2965) of evaluations. High simplicity and comprehensibility scores (4-5) were more frequently assigned to AI reports than to radiologist-written reports (70.0% vs 43.4% and 68.1% vs 40.4%, respectively). In multivariable analysis, higher comprehensibility was the strongest predictor in both directions: higher comprehensibility of AI-generated reports increased the odds of preferring AI (score 4: adjusted OR 1.87, 95% CI 1.08-3.23, p = 0.025), while higher comprehensibility of radiologist-written reports reduced them (score 4: adjusted OR 0.45, 95% CI 0.29-0.69, p < 0.001). Preference for AI-generated reports showed a non-significant trend toward increase with educational level. CONCLUSION: AI-generated breast imaging reports were preferred by most patients and perceived as clearer, supporting a complementary and supervised use of AI-generated summaries. KEY POINTS: Question Patients increasingly access their own radiology reports, yet standard radiologist-written reports are often difficult to understand, highlighting the need for patient-friendly alternatives. Findings In this study, AI-generated breast imaging reports were preferred by patients in 63.3% of evaluations, with comprehensibility emerging as the strongest predictor of preference. CRITICAL RELEVANCE STATEMENT: AI-generated breast imaging reports were preferred by most patients and received higher ratings for simplicity and comprehensibility than radiologist-written reports, supporting a supervised and complementary use of AI-generated summaries in clinical breast imaging.

Insights into ImagingVol. 17(1)
University of Milan (IT), Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT), Ente Ospedaliero Cantonale (CH), Ospedale A. Perrino (IT), Ospedale di Stato della Repubblica di San Marino (SM), European Institute of Oncology (IT)
Good health and well-being
Openalex Percentile: Top 22%
Artificial Intelligence in Healthcare and Education
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