IMPACT Award Recognizes ROCK Research Group’s Advances in Knee Osteochondritis Dissecans Treatment

NEW ORLEANS, March 4, 2026 – The 2026 Improving Musculoskeletal Patient Care Through Outcomes Research (IMPACT) Award has been presented to Kevin Shea, MD, FAAOS, and the Research in Osteochondritis of the Knee (ROCK) Research Study Group. The award acknowledges 15 years of collaborative effort to improve prevention and treatment strategies for knee osteochondritis dissecans (OCD).

Understanding Knee OCD

Osteochondritis dissecans (OCD) is a joint condition that primarily affects adolescents. If left untreated, it can progress to osteoarthritis. The condition impacts the cartilage and underlying bone, and can cause pain and instability in the knee. Knee OCD is a condition that affects young athletes at the peak of their athletic activity, potentially causing psychosocial impacts due to loss of physical activity, and can lead to osteoarthritis in less than 15 years if not addressed.

The ROCK Research Study Group

The ROCK Research Study Group was established in response to limited research highlighted in a 2010 American Academy of Orthopaedic Surgeons (AAOS) Clinical Practice Guideline on the Diagnosis and Treatment of OCD. Founded by Dr. Shea, Theodore Ganley, MD, FAAOS (Children’s Hospital Philadelphia), and Eric Wall, MD, FAAOS (Cincinnati Children’s Hospital), ROCK has grown into an international, multicenter research consortium.

Currently, ROCK comprises over 70 active members, including surgeons, veterinarians, physical therapists, and radiologists, investigating more than 100 research questions. Since 2014, the group has enrolled over 1,900 patients across 25 academic centers, resulting in numerous publications on the etiology, classification, epidemiology, healing prediction, and surgical treatment of OCD.

Key Research Achievements

ROCK’s research has focused on several critical areas:

• Standardized Classification: The group developed a highly reliable six-category arthroscopic classification system for knee OCD by reviewing 300 arthroscopy videos. Research examined X-ray, MRI, and arthroscopy classification systems, finding MRI classification to be more challenging but an ongoing priority for refinement.
• Predictive Algorithms: Utilizing machine learning, ROCK developed algorithms to predict the likelihood of healing without surgery, considering factors like age, sex, lesion size, stability, and skeletal maturity. Lesion location – specifically the posterior aspect of the condyle on sagittal MRI and the medial or lateral-most locations on coronal MRI – were identified as significant predictors of nonoperative treatment success.
• Optimal Surgical Techniques: A randomized controlled trial was conducted to compare trans-articular and retro-articular drilling techniques for OCD, aiming to determine the most effective surgical methodology.

Future Directions

ROCK is now concentrating on leveraging advanced machine learning to enhance the precision and consistency of patient care. This includes developing an AI-driven platform to automatically identify and quantify clinically relevant features from radiographs, CT scans, and MRI studies, such as lesion size, fragment stability, and cartilage integrity. Future research will also explore the role of biological stimulants and adjuvants to healing, including growth factors, bone grafting, and stem cell therapies.

About the AAOS

The American Academy of Orthopaedic Surgeons (AAOS) is the world’s largest medical association of musculoskeletal specialists, with over 39,000 members. The AAOS is dedicated to advancing musculoskeletal health through education, research, and advocacy.

Disclosure/Funding and Conflicts of Interest information is available upon request.