Radiology Reimagined: Advancing Clinical Practice Through AI Innovation (2025)-"What is the Radiologist's Future Role?"

"What is the Radiologist's Future Role?" – Dr. Nina Kottler

Pdf Summary

The presentation "What Happens Next? The Future of Radiology" by Dr. Nina Kottler explores the evolution of artificial intelligence (AI) in radiology and its impact on the specialty's future. Traditional narrow AI tools have provided modest efficiency gains (~5%) and have not fully solved radiologist capacity or burnout issues. However, the advent of foundation models, including large language models (LLMs) and multimodal models (LMMs), heralds a transformative shift.<br /><br />These advanced AI systems enhance radiologist capacity and workflow by automating complex tasks such as scheduling, protocol selection, image denoising, lesion detection, report generation, and clinical decision support. Unlike basic voice recognition (VR) systems, LLM-assisted report drafting streamlines report creation by reducing steps requiring direct radiologist input from 26 to 7, consequently freeing radiologists to concentrate on higher-value and more meaningful clinical interpretations.<br /><br />The integration of AI tools into a comprehensive data and AI ecosystem—combining worklist management, viewer optimization, automatic anatomical segmentation, explainable AI results, EMR integration, critical case prioritization, and automated communication—maximizes the clinical impact of imaging data. This ecosystem will enable radiologists to evolve from pure image readers to “information experts,” integrating genomics, radiomics, molecular imaging, and clinical data for holistic patient care.<br /><br />The future of radiology will be driven by general AI models replacing narrow AI and transforming workflows rather than eliminating the need for radiologists. Continuous improvement in AI tools is essential to address the growing volume-capacity mismatch in imaging studies. Dr. Kottler emphasizes that embracing AI is necessary, warning that failure to innovate risks being overtaken by others.<br /><br />In summary, AI advancements will augment radiologists’ capabilities, improve patient care, and redefine radiologists' roles, making the future of radiology an exciting landscape where technology and human expertise synergize.

Keywords

Artificial Intelligence

Radiology

Foundation Models

Large Language Models

Multimodal Models

Radiologist Workflow

Report Generation

Clinical Decision Support

Imaging Data Integration

Future of Radiology