Moderators: Laurent Létourneau-Guillon & Jaron Chong

This year’s Radiology AI session shifts from theoretical discussions to practical, real-world applications and experiences from Canadian centres. Presentations will cover the spectrum from resident use of AI tools to prospective independent clinical evaluation of AI models, highlighting both the benefits and challenges of AI in Radiology. The session will illustrate how AI is being adopted and tested in everyday radiology practice across the country.

At the end of this session, delegates will be able to:

  • Describe common pearls and pitfalls encountered by radiology trainees when using AI tools in clinical practice and discuss strategies to ensure responsible integration of AI.
  • Explain the current applications, benefits, and limitations of AI-assisted dictation systems in radiology reporting.
  • Recognize the role of AI in breast-imaging detection workflows and evaluate its impact on diagnostic accuracy, workflow, and patient care.
  • Identify key challenges and lessons learned from the prospective validation of AI software for musculoskeletal radiograph interpretation.

CanMEDS:

  • Medical Expert
  • Communicator
  • Collaborator
  • Leader
  • Health Advocate
  • Professional

Target Audience:

  • Radiologist
  • Resident
  • Medical Student

COI: Dr. Létourneau-Guillon reports receiving research funding from the Fonds de recherche du Québec en Santé and the Fondation de l’Association des radiologistes du Québec, including Radiology Research Funding and a Clinical Research Scholarship–Junior 1 Salary Award. He also receives internal research funding from the Département de radiologie, radio-oncologie et médecine nucléaire de l’Université de Montréal, the Centre hospitalier de l’Université de Montréal (CHUM), and the CHUM Research Center (CRCHUM). These research relationships are not directly related to the content of this session.Pearls &

Training in the Age of AI: Pearls, Pitfalls, and the Resident Perspective
Kay Wu

This presentation will highlight key pearls and pitfalls for the integration of AI into radiology practice, from the resident perspective. Practical insights, challenges, and opportunities that trainees experience will be shared as AI becomes increasingly embedded in clinical workflows.

COI: None Declared

Say It Smarter: AI-Powered Dictation in Everyday Radiology Practice
Christopher Fung

This presentation will provide a practical review of AI-based dictation platforms.

COI: Dr. Fung has disclosed a financial relationship with AbbVie, having received speaker honoraria in 2025. He is also a co-investigator on a funded research grant associated with the ExactVu Imaging OPTIMUM Trial, focused on prostate micro-ultrasound.

Promise and Pitfalls: AI in Screening Mammography—A Case-Based Review
Raman Verma

Using case-based examples, this presentation will provide a practical overview of AI in screening mammography, illustrating both the benefits and challenges encountered by radiologists.

COI: Dr. Raman Verma has financial payments as an educational consultant for BD.

Prospective Validation of AI Software for Interpretation of Musculoskeletal Radiographs: Lessons Learned
An Tang

This presentation will provide a real-world case study to illuminate the essential steps and common challenges involved in adopting AI software in clinical or educational settings. Attendees will also explore practical mitigation strategies that support effective validation and successful implementation.