ChatGPT and the future of radiology reporting

Abstract

To explore the role of large language models (LLMs), such as ChatGPT, in enhancing radiology reporting and patient interaction, highlighting their benefits, limitations, and ethical implications. The integration of ChatGPT into radiology can potentially streamline workflows by providing succinct impressions and extracting longitudinal patient information from electronic medical records (EMR), thereby increasing efficiency and workflow for radiologists. It helps facilitate patient understanding by simplifying complex medical information, fostering better engagement and understanding. Despite their promise, ChatGPT face substantial limitations, particularly in accurately contextualising intricate medical data and performing abstract clinical reasoning—areas where human expertise is indispensable. Ethical considerations include ensuring transparency, accountability, and the reduction of inherent biases to safeguard patient care. Additionally, the current medicolegal frameworks are insufficient in addressing the liability of errors or misinterpretations generated by AI. LLMs such as ChatGPT can serve as valuable adjuncts in radiology, enhancing report drafting and patient communication. However, responsible integration requires rigorous validation, ethical oversight, and adherence to updated regulatory standards. Radiologists' expertise remains essential to ensure precise, contextually accurate reporting and maintain high-quality patient care. Continuous research and policy development are needed to optimize and safely harness the potential of LLMs in medical practice.

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