Femoral fracture type can be predicted from femoral structure: A finite element study validated by digital volume correlation experiments.

Abstract

Proximal femoral fractures can be categorized into two main types: Neck and intertrochanteric fractures accounting for 53% and 43% of all proximal femoral fractures, respectively. The possibility to predict the type of fracture a specific patient is predisposed to would allow drug and exercise therapies, hip protector design, and prophylactic surgery to be better targeted for this patient rendering fracture preventing strategies more effective. This study hypothesized that the type of fracture is closely related to the patient-specific femoral structure and predictable by finite element (FE) methods. Fourteen femora were DXA scanned, CT scanned, and mechanically tested to fracture. FE-predicted fracture patterns were compared to experimentally observed fracture patterns. Measurements of strain patterns to explain neck and intertrochanteric fracture patterns were performed using a digital volume correlation (DVC) technique and compared to FE-predicted strains and experimentally observed fracture patterns. Although loaded identically, the femora exhibited different fracture types (six neck and eight intertrochanteric fractures). CT-based FE models matched the experimental observations well (86%) demonstrating that the fracture type can be predicted. DVC-measured and FE-predicted strains showed obvious consistency. Neither DXA-based BMD nor any morphologic characteristics such as neck diameter, femoral neck length, or neck shaft angle were associated with fracture type. In conclusion, patient-specific femoral structure correlates with fracture type and FE analyses were able to predict these fracture types. Also, the demonstration of FE and DVC as metrics of the strains in bones may be of substantial clinical value, informing treatment strategies and device selection and design. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:993-1001, 2018.