Revolutionizing 3D Cast Solutions for Orthopedic Care
We were thrilled to witness our research fellow, Kassem Ghayyad, MD, present our publication, Optimizing Wrist Splint Fitting Parameters Through Artificial Intelligence Analysis, at the 2025 American Association for Hand Surgery (AAHS) Meeting in Hawaii!
The Challenge
The traditional method for determining wrist splint size relies on measuring wrist circumference, which often leads to poor fit and discomfort for patients. At Dimension Ortho, we aim to revolutionize orthopedic care with 3D cast and 3D splint solutions, and our study aimed to improve this process by evaluating additional hand features using 3-dimensional (3D) scanned data and Artificial Intelligence (AI).
Our Approach
We recruited 54 healthy volunteers who were fitted with a standard wrist brace (Short Arm Brace, Ossur, Iceland). Using an infrared-based 3D scanner (Einscan Pro, Shining3D, China), we collected data and analyzed 14 distinct hand features using a correlation map. By applying machine learning models, including Extreme Gradient Boosting (XGB) Classifier, RandomForestClassifier, and Support Vector Classifier (SVC), we discovered wrist width showed the highest classification accuracy (91%) for both the XGB Classifier and RandomForestClassifier. The measurements including hand wrist width, mid-forearm width, and hand crease line width also performed well with the XGB Classifier, achieving an accuracy of 90%.
The Conclusion
Combining AI with 3D scanning technology enables accurate wrist splint size prediction from a single image, allowing for contactless, personalized fitting. This innovative approach enhances patient comfort and improves outcomes.
A big thank you to Dr. Kassem Ghayyad for representing Dimension Ortho and showcasing our hard work! To read the full paper and learn more about the role of AI in orthopedic care and 3D cast solutions, click the link below:
https://pubmed.ncbi.nlm.nih.gov/39421289/
