Meeting Banner
Abstract #4432

Statistical Shape Models of Bone and Cartilage for Predicting Demographics: Data from the Osteoarthritis Initiative

Anthony A Gatti1, Kuan-Chieh Wang2, Garry E. Gold1, Scott L. Delp3, and Akshay C. Chaudhari1
1Radiology, Stanford University, Stanford, CA, United States, 2Computer Science, Stanford University, Stanford, CA, United States, 3Bioengineering, Stanford University, Stanford, CA, United States


Three-dimensional statistical shape models built from MRI data can predict future disease and distinguish between groups. However, these models do not leverage the major advantage of MRI – the ability to visualize and quantify soft tissues such as cartilage. This study built three MRI-based statistical shape models, 1) bone shape, 2) cartilage thickness, 3) both bone shape and cartilage thickness. We showed that bone shape and bone shape + cartilage thickness models predicted sex with an R2 of ~0.9, significantly outperforming cartilage thickness alone (0.8). However, cartilage thickness alone was significantly better at predicting radiographic knee osteoarthritis.

This abstract and the presentation materials are available to members only; a login is required.

Join Here