The Effect of AI-Enhanced Breast Imaging on the Caring Radiologist-Patient Relationship

AI has shown radiologist-level performance at diagnosis and detection of breast cancer from breast imaging such as ultrasound and mammography. Integration of AI-enhanced breast imaging into a radiologist's workflow through the use of computer-aided diagnosis systems, may affect the relationship they maintain with their patient. This raises ethical questions about the maintenance of the radiologist-patient relationship and the achievement of the ethical ideal of shared decision-making (SDM) in breast imaging. In this paper we propose a caring radiologist-patient relationship characterized by adherence to four care-ethical qualities: attentiveness, competency, responsiveness, and responsibility. We examine the effect of AI-enhanced imaging on the caring radiologist-patient relationship, using breast imaging to illustrate potential ethical pitfalls.Drawing on the work of care ethicists we establish an ethical framework for radiologist-patient contact. Joan Tronto's four-phase model offers corresponding elements that outline a caring relationship. In conjunction with other care ethicists, we propose an ethical framework applicable to the radiologist-patient relationship. Among the elements that support a caring relationship, attentiveness is achieved after AI-integration through emphasizing radiologist interaction with their patient. Patients perceive radiologist competency by effective communication and medical interpretation of CAD results from the radiologist. Radiologists are able to administer competent care when their personal perception of their competency is unaffected by AI-integration and they effectively identify AI errors. Responsive care is reciprocal care wherein the radiologist responds to the reactions of the patient in performing comprehensive ethical framing of AI recommendations. Lastly, responsibility is established when the radiologist demonstrates goodwill and earns patient trust by acting as a mediator between their patient and the AI system.