Patient identifiers such as gender, race and ethnicity cannot predict the shape of a person's knee, a study published in The Knee found.
The study, published March 19, examined the shapes of about 1,000 knee joints acquired from computed tomography. Two comprehensive feature sets were used to describe bone shapes. One was based on morphological measurements and the other on statistical shape model weights.
Researchers completed a cluster analysis with different algorithms, and the clusters were evaluated with several metrics. Data found a low tendency to form clusters.
The study concluded: "After anisotropic normalization by size, which removes size and aspect ratio related differences, the data exhibited no morphotypes. This showed that there are no relevant hidden variables, e.g., gender, body type or ethnicity, which influence the shape of the knee joint. Instead, knee shape is highly individual."
Orthopedic device maker Conformis helped fund the study and provided the computed tomography images to researchers, according to a May 24 news release.
"This new research reinforces the importance of precisely matching the implant to the individual patient," Conformis CEO and President Mark Augusti said in the release. "This study further supports our long-held business case that fully personalized implants provide the best fit for patients, eliminate clinically-significant overhang, minimize postoperative pain, speed recovery time and enhance flexibility and performance."