Resident-led research grounded in patient care
About TORRC
The Toronto Orthopaedic Resident Research Committee (TORRC) is a resident-led initiative dedicated to fostering a culture of academic excellence and inquiry within orthopaedic surgery.
Our mission is to support, connect, and empower orthopaedic residents and medical students to engage in meaningful research that advances patient care and the field of musculoskeletal medicine.
Through structured programs, mentorship, and collaboration with faculty and clinical researchers, TORRC serves as a hub for research activity within the Division of Orthopaedic Surgery at the University of Toronto.
SUPPORT
Structured programs and mentorship that lower the barrier to high-quality clinical research
CONNECT
A network of residents, students, faculty, and clinical researchers across U of T sites
EMPOWER
Original research that improves patient care and shapes the future of musculoskeletal medicine
Research
Repository
The TORRC Research Repository is a centralized internal resource designed to support ongoing resident research collaboration within the Division of Orthopaedic Surgery. Access is restricted to authorized resident members through the UofT Orthopaedic Surgery Portal.
Fellowship
The TORRC Medical Student Orthopaedic Research Fellowship (MS-ORF) is a structured research opportunity for medical students with an interest in orthopaedic surgery. Fellows are paired with resident and faculty mentors to complete a defined research project.
What You'll Gain
- Hands-on research experience
- Mentorship from residents and faculty
- Opportunity to present work
- Strong academic foundation
Who Should Apply
- Medical students at any stage
- Interest in orthopaedics or research
- Willingness to commit to a project
- Curiosity over credentials
Leadership
Faculty Leads
Resident Leads
Program Assistants
Publications
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2026
Comparison of volar distal radius and iliac crest bone grafts in the treatment of scaphoid non-union with humpback deformity: a systematic review and meta-analysis
Hand Surgery & Rehabilitation · Art. 102740 · DOI: 10.1016/j.hansur.2026.102740
A meta-analysis of three comparative studies (166 patients) found no significant difference in union rates between volar distal radius and iliac crest bone grafts for scaphoid non-union with humpback deformity. Distal radius grafts showed modestly faster time to union and lower donor-site morbidity, though certainty of evidence was very low.
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2026
Opportunistic screening for osteoporosis using chest X-rays and deep learning: A systematic review and meta-analysis
Bone · Vol. 210, 117923 · DOI: 10.1016/j.bone.2026.117923
Deep learning models applied to chest radiographs show promising diagnostic performance for opportunistic osteoporosis screening. Across 12 studies and 200,796 patients, internally validated models achieved pooled sensitivity 0.85 and specificity 0.83, with external AUCs ranging 73.4–94.6%.
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2026
Artificial Intelligence in Pelvic Fracture Diagnosis and Outcome Prediction: A Systematic Review and Meta-analysis
ScienceDirect · PII: S2949761226000337
A systematic review and meta-analysis evaluating the performance of artificial intelligence models for the diagnosis of pelvic fractures and the prediction of clinical outcomes — synthesizing evidence across published studies to assess readiness for clinical translation.
Journal Club
& Research Workshops
Journal Club
Quarterly conversations on the literature
TORRC Journal Clubs are opportunities for attending physicians and residents to discuss recent papers published within orthopaedics. They are organized roughly every three months — a chance to read closely, critique generously, and bring evidence to the bedside
Research Workshops · Fall 2026
Hands-on sessions to sharpen your research toolkit
Starting fall 2026, TORRC will organize dedicated workshops for medical students and residents — talks from research experts, plus an open-floor segment where you can share progress and get advice from peers and attendings. A low- pressure environment to troubleshoot projects.
Get Involved
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