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Patient Preferences for Artificial Intelligence in Medical Imaging: A Single-Center Cross-Sectional Survey
Kennedye N McGhee1, D Jonah Barrett2, Omar Safarini2
1University of Alabama at Birmingham Marnix. E. Heersink School of Medicine, 619 19th Street South, Birmingham, AL, 35233, USA. knm0036@uab.edu.
Journal of Imaging Informatics in Medicine
|August 7, 2025
Summary
Patients undergoing medical imaging want to be informed about Artificial Intelligence (AI) use in their care. Transparency and disclosure are crucial for AI adoption in radiology practices.
Area of Science:
- Medical Imaging
- Artificial Intelligence in Healthcare
- Patient Perceptions
Background:
- Artificial Intelligence (AI) is increasingly used in clinical settings to enhance diagnostic accuracy and reduce clinician burnout.
- Patient understanding and perspectives on AI's role in their medical care are not well-established.
- Cross-sectional imaging exams are a key area where AI implementation is growing.
Purpose of the Study:
- To investigate patient preferences regarding the use of and communication about Artificial Intelligence (AI) in their cross-sectional imaging examinations.
- To assess patient knowledge, perceptions, and economic considerations related to AI in healthcare.
- To explore patient willingness to accept AI-generated results and AI-exclusive interpretations.
Main Methods:
- A single-center, cross-sectional study surveyed 226 outpatients undergoing CT or MRI exams.
- Structured questionnaires assessed patient knowledge of AI, perspectives on AI in care, and preferences for AI result communication.
- Data collected using Likert scales and categorical questions, with analysis of socioeconomic status correlations.
Main Results:
- A significant majority (90.3%) of patients desired to be informed about AI use in their care and supported the right to opt out (91.1%).
- Most patients (91.1%) preferred explicit notification when AI interpreted their medical images, with 65.6% unwilling to accept exclusively AI-interpreted screening exams.
- Lower socioeconomic status correlated with lower patient knowledge of AI in medicine (p < .001).
Conclusions:
- Patients strongly advocate for transparency and disclosure regarding AI utilization in their medical imaging.
- Radiology practices must prioritize clear communication and patient engagement to align AI adoption with patient expectations.
- Standardized disclosure of AI use, without overburdening workflows, is essential for building patient trust and acceptance.
Keywords:
Artificial IntelligenceInformed consentMedical imagingPatient preferencesRadiology practiceTransparencyMore Related Videos
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