journal of biomedical informatics
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Musculoskeletal Modeling of Hip Joint and Fracture Analysis for Surgical Planning Using FEA

Author(s): Sathya Ganapathi, Shilfa Thoppay Premkumar, Thenmozhi Malaikannu, Kavitha Anandan

Background: Hip fractures are a major cause for disability in patients. They require immediate attention as they could otherwise cause death. Hip fractures are almost always treated with surgery by implantation. Implants are of various types accounting for the many variations in hip fractures.

Objectives: This paper presents the design and analysis of a hip implant using Finite element analysis. Fracture conditions are determined and the optimal design of the implant is obtained for improving healthcare and patient safety.

Methods: Anthropometric parameters of the human femur bone are collected from a particular age group. These are then used to obtain a CAD model of the bone using CATIA. The standard Charnley hip implant, used in total hip replacement surgery is also modeled. The proposed models are analyzed using ANSYS software by assigning appropriate material properties to the bone and implant. The stress distribution is observed when loads corresponding to normal gait conditions are applied. The load at which fracture occurs is then determined experimentally.

Results: Based on the analysis results of the modeled bone, the implant is optimized by varying the base cross section, the bio-materials used, and the design parameters so that, its stress response mimics that of the actual bone. It is found that the model no 2 as in Table 6 with head diameter 28mm, neck diameter 10mm, neck angle 128 degrees has minimum strain at the neck region with a value of 0.65 and is found to be suitable for implant design. Results show that initiation of fracture in the implant occurs at 2000N and complete fracture occurs at 2400N.

Conclusions: The 3D models are very useful in simulation of bone fractures and internal fixations with implants. In this work, the hip joint and implant model, developed in CATIA software, help to understand how these structures adapt to external forces disturbances [15]. This will help the doctors to chose the optimal implant for a particular patient. This leads to greater accuracy and patient specificity.