2026 CAP Congress / Congrès de l'ACP 2026

Session

W2-4 SYMPOSIUM: Artificial Intelligence in Radiotherapy | L'intelligence artificielle en radiothérapie

W2-4

24 Jun 2026, 14:15

U. Ottawa - Learning Crossroads (CRX) Building

Description

Artificial Intelligence in Radiotherapy explores how advanced computational methods are transforming radiation oncology across the full clinical workflow. From automated image segmentation and adaptive treatment planning to outcome prediction, response assessment, and biologically informed dose optimization, AI-driven approaches are reshaping how radiotherapy is designed, delivered, and evaluated. This symposium will highlight methodological advances, clinical translation, and emerging challenges in validation, robustness, and implementation. By bringing together expertise spanning medical physics, imaging science, machine learning, and clinical oncology, the session aims to provide a comprehensive perspective on how AI is advancing precision, efficiency, and personalization in radiotherapy.

Le symposium « L'intelligence artificielle en radiothérapie » explore la manière dont les méthodes informatiques avancées transforment la radio-oncologie tout au long du parcours clinique. De la segmentation automatisée des images et de la planification adaptative des traitements à la prédiction des résultats, à l'évaluation de la réponse et à l'optimisation des doses fondée sur des données biologiques, les approches basées sur l'IA redéfinissent la manière dont la radiothérapie est conçue, administrée et évaluée. Ce symposium mettra en lumière les avancées méthodologiques, la transposition clinique et les nouveaux défis en matière de validation, de robustesse et de mise en œuvre. En réunissant des experts en physique médicale, en imagerie, en apprentissage automatique et en oncologie clinique, cette session vise à offrir une perspective globale sur la manière dont l'IA améliore la précision, l'efficacité et la personnalisation en radiothérapie.

1046. Integrating Artificial Intelligence into Head and Neck Radiotherapy: Early Steps Toward Response-Adaptive Treatment

Houda Bahig (Centre hospitalier de l'Université de Montréal (CHUM))

24/06/2026, 14:15

Artificial Intelligence in Radiotherapy / L'intelligence artificielle en radiothérapie

Invited Speaker / Conférencier(ère) invité(e)

As cure rates improve for HPV-associated oropharyngeal cancer, attention has shifted toward reducing the burden of treatment toxicity without compromising disease control. Artificial intelligence and advanced imaging may offer tools to support this goal, though their clinical readiness remains an open question. This talk describes an ongoing research program exploring AI applications across...

564. Does suppressing inflammation response in lung radiotherapy protect the lung cancer cells

Garrett Kirk (Western University)

24/06/2026, 14:45

Physics in Medicine and Biology / Physique en médecine et en biologie (DPMB-DPMB)

Oral not-in-competition (Graduate Student) / Orale non-compétitive (Étudiant(e) du 2e ou 3e cycle)

Radiation-induced lung injury, characterized by chronic inflammation and fibrosis, limits the dose we can give in lung cancer radiotherapy. Drugs that block the inflammatory/fibrosis response have been shown to protect normal lung tissues from radiation. In this study, we wish to determine if one of these drugs also protect the lung cancer cells.
To initiate this study, we developed and...

791. Towards quantum microdosimetry: A novel approach for modeling low energy electron transport in biological tissues

Matthew Inglis-Whalen (Carleton University)

24/06/2026, 15:00

Artificial Intelligence in Radiotherapy / L'intelligence artificielle en radiothérapie

Oral (Non-Student) / Orale (non-étudiant(e))

Background: Therapeutic and accidental radiation exposure contexts typically focus on absorbed dose as the figure of merit for assessing tissue damage. However, physical processes underlying genetic damage are primarily mediated by secondary electrons with energies near the ionization threshold energy of DNA. This has motivated efforts to push Monte Carlo simulations of radiation transport...

1061. From Automated Analysis to Data Completion: Toward Robust AI for Radiotherapy Imaging in Neuro-Oncology

Dr Ali Sadeghi-Naini (Electrical Engineering & Computer Science, York University)

24/06/2026, 15:15

Invited Speaker / Conférencier(ère) invité(e)

Artificial intelligence (AI) is increasingly applied in radiotherapy for tasks such as tumor segmentation and longitudinal response assessment. These methods, however, often assume complete high-quality imaging, which is not always available in clinical datasets. Missing or incomplete scans, particularly contrast-enhanced MRI, limit both inclusive AI model development and multi-institutional...