Arthur Child Comprehensive Cancer Centre (ACCCC) | Department of Radiation Oncology | Online Campus

Head and Neck Malignancies All Lectures | Residency Program Academic Half Day

Pediatric Malignancies All Lectures | Residency Program Academic Half Day

Hematologic Malignancies All Lectures | Residency Program Academic Half Day

Central Nervous System Malignancies All Lectures | Residency Program Academic Half Day

Sarcoma and Cutaneous Malignancies All Lectures | Residency Program Academic Half Day

Breast Malignancies All Lectures | Residency Program Academic Half Day

Gynecologic Malignancies All Lectures | Residency Program Academic Half Day

Genitourinary Malignancies All Lectures | Residency Program Academic Half Day

Gastrointestinal Malignancies All Lectures | Residency Program Academic Half Day

This comprehensive 20-25 hour training program equips radiation therapists with expert-level skills in pelvic anatomy identification and contouring for prostate cancer and oligometastatic treatments using MR-Linac systems. Through a blend of interactive lectures, hands-on labs, and AI-assisted tools, participants will: Master Pelvic Anatomy: Identify normal structures (prostate, rectum, bladder, lymph nodes, neurovascular bundles) and pathologies on MRI/CT. Distinguish anatomical boundaries (e.g., rectosigmoid junction, anal canal) using 3D atlases (e-Anatomy) and custom medical illustrations. Develop Contouring Expertise: Apply RTOG/ESTRO guidelines for target/OAR delineation with ProKnow/EduCase labs. Practice adaptive workflows with synthetic MRI datasets and AI tools (MVision AI, Varian Eclipse).

This intensive annual Canadian Radiation Oncology review course is specifically designed for radiation oncology residents preparing to sit the 2026 Royal College of Physicians Radiation Oncology Board Examination. Focused on high-yield, exam-critical content, the curriculum delivers a comprehensive exploration of current evidence-based practice patterns for the management of all cancer sites, including breast, prostate, lung, gastrointestinal, central nervous system, gynecologic, genitourinary, sarcoma, lymphoma, pediatric malignancies, and rare tumors. Participants will engage with the latest clinical evidence, national/international guidelines (2025–2026), and emerging innovations shaping modern radiation oncology practice. The course emphasizes the integration of radiotherapy within multidisciplinary care, dose fractionation principles, toxicity mitigation strategies, and the interpretation of landmark trials that inform clinical decision-making. Structured to align with the Royal College’s exam blueprint, sessions incorporate case-based scenarios, rapid-fire Q&A, and mock oral exam drills to refine diagnostic reasoning, treatment planning, and critical appraisal skills. Attendees will gain proficiency in addressing complex exam questions while mastering the evolving standards of care across both common and rare malignancies. By synthesizing cutting-edge research with core board examination competencies, this course equips residents with the knowledge, confidence, and strategic approach required to excel on the 2026 certification exam and deliver evidence-driven, patient-centered care in their clinical practice.

Joey Aggabao

+10

This course provides a comprehensive exploration of the rapidly evolving field of Artificial Intelligence (AI) and its transformative impact on Radiation Oncology. The curriculum is structured to guide students from the foundational principles to hands-on application, covering three critical areas. First, we will examine the **ethical governance and regulatory landscape** surrounding AI in medicine, ensuring a responsible understanding of its implementation. Next, we will delve into the **core clinical applications** of AI, including automated segmentation, treatment planning, and image guidance, which are revolutionizing modern radiotherapy workflows. The course then transitions to the **AI development lifecycle**, focusing on standardization, quality assurance, and practical data handling. A significant "Magician's Corner" workshop series will equip you with the foundational skills to build, optimize, and evaluate deep learning models yourself. Finally, we will explore essential tools and platforms for AI research, from public data repositories and coding assistants to high-performance computing and large language models, preparing you to contribute to the future of AI-driven cancer care.