Alignment of policy, practice, and patient safety for trustworthy AI in radiology.

Policies shaping AI in radiology directly affect diagnostic safety. This review proposes a practical, lifecycle-based framework aligning AI governance with clinical practice. It clarifies what AI must deliver to clinicians and patients, and what institutions need for safe implementation. Covering data stewardship, development, validation, deployment, and monitoring, it defines shared responsibilities among vendors, institutions, and clinicians—grounded in trustworthy AI principles to protect patient safety.