Researchers have developed an agentic framework that uses small language models to refine and improve free-text chest X-ray reports. The system demonstrates that smaller, more efficient language models can effectively enhance medical imaging documentation without requiring the computational resources of larger models. This approach offers potential applications for healthcare institutions seeking to optimize radiology report quality while managing operational costs.