Knee Implant Model - Computational Biomechanics of the Musculoskeletal System - page 94

8.1 IntroduCtIon

8.1.1 B ackGround
Knee replacements generally boast good longevity and high survivorship and are commonly pre-
scribed for patients with severe knee problems, predominantly osteoarthritis (National Institutes of
Health 2003). The disease is more prevalent in the elderly, due to accumulative overuse and degen-
eration. With an ever-aging population, the number of people using joint replacement is expected
to increase. It is logical to assume that most people would like to get an implant and remain mobile
rather than be confined to a wheelchair.
Despite the high demand and success of knee implants, some failure is inevitable (National
Institutes of Health 2003). Though uncommon, periprosthetic fracture is one cause of failure, with a
prevalence ranging from 0.3% to 2.5% (Su, DeWal, and Di Cesare 2004). In fact, the consequences
of periprosthetic fracture are devastating, with complication rates of 25% to 75% after treatment
(Dennis 2001). The majority of the fractures are associated with elderly subjects with osteoporo-
sis and rheumatoid arthritis patients receiving steroid therapy. These risk factors are related to a
reduction of bone stock, with a consequential loss in bone strength and stress alterations within
the bone.

8.1.2 n otcHinG and S treSS c oncentration
Anterior notching of implants is believed to contribute to the risk of periprosthetic fracture. Culp
et al. (1987) conducted a theoretical analysis and suggested that a 3-mm notching reduced bone
torsional strength by 29.2%. This result was further supported by Lesh et al. (2000), who reported
a decrease of 18% in bending strength and 39.2% in torsional strength after notching. Zalzal et al.
(2006) characterized local stress by notching and believed that a femoral notch greater than 3 mm
with sharp corners would produce high stress concentration. However, Gujarathi et al. (2009) sug-
gested that there was no relationship between minimal notching and fracture. Though the vulner-
able location was identified, the mechanism of fracture and the association with loading conditions
are not well understood. Su, DeWal, and Di Cesare (2004) suggested that fractures occurred most
frequently from low-velocity falls, while high-energy trauma contributed to a smaller proportion
of fractures. With the growing number of knee replacements and increased activity of elderly
patients, an investigation of the fracture mechanism could aid physicians in determining viable
knee replacements.
Computational methods are efficient tools to investigate the parametric effects of the bone-
implant interface in a well-controlled environment. In the present study, a three-dimensional FE
bone-implant model was developed to study the effect of reducing bone strength on periprosthetic
stress failure.

8.2 model develoPment

8.2.1 m odel c onStruction
The geometry of the distal femur and proximal tibia was acquired from MRI of a normal adult
female subject (age 28, height 165 cm, weight 54 kg), and reconstructed using the segmentation
software MIMICS (Materialise, Leuven, Belgium). The knee implant (Advance ® Primary System,
Wright Medical Technology Inc., Arlington, Virginia) was digitized and reconstructed using the
reverse engineering software Rapidform XOR2 (INUS Technology, Seoul, South Korea). The bone-
implant model was then imported into the FE software ABAQUS (Dassault Systèmes Technologies,
RI, USA) for FE meshing and analysis.