Personalized Cine Cardiac MRI Protocol Optimization Using a Retrieval-Augmented Large Language Model: A Prospective Comparison With Technologist-Optimized Protocol.

Cine cardiac magnetic resonance imaging (magnetic resonance imaging) protocols are typically based on static templates, which may not optimally address individual patient limitations such as arrhythmia or limited breath-hold capacity.

To test whether an artificial intelligence (artificial intelligence) framework using a large language model with retrieval-augmented generation (large language model with retrieval-augmented generation) can provide cine cardiac magnetic resonance imaging protocols that are equivalent or noninferior to those of technologist-optimized protocols.