The implant position can be optimized to obtain specific joint kinematics or kinetics, while accounting for muscle and ligament forces. This can be done using the methods described in “Implant behavior inside body – motion, forces, stability”
Optimization can be done using built-in gradient-based optimization solvers or from external optimizers by accessing the AnyBody Modeling System through the command line application of AnyBody.
Examples:
- Restore natural knee kinematics
- Mechanical and kinematic alignments in total knee arthroplasty
- Joint stability following arthroplasty
- Patellar tracking
- Knee stability
- Soft tissue balancing
Examples of input and output for an implant positioning model:
Input:
- Implants CAD files (STL)
- Implant positioning data
- Bone CAD files (STL)
- Anthropometrics data
- Motion data and ground reaction force
- Definition of objective for optimization (e.g. minimize joint reaction forces)
Output:
- Optimal implant position
- Implant secondary DOF motion
- Implant contact forces (accounting for muscles)
- Muscle and ligament forces
- And much more
Contact us to learn more or to discuss how we could solve your problem
The steps to model this can be the following
- Reproduce the activity, e.g. walking, using your own data or an existing AnyBody model
- Create a force-dependent model of the joint in question see “Implant behavior inside body – motion, forces, stability”
- Create design variables in the model, which can alter the implant position
- Create an objective function based on biomechanical properties in the model such as joint motion, joint forces, and ligament forces.
- Create the optimization study incorporating the design variables that control implant positions and the biomechanically based objective function
Models in AMMR
Webcasts
- Toward personalized total knee arthroplasty – Pre-planning the patient’s optimal joint function in robotic-asssisted surgery
- Patient-Specific Spine Analytics
- The future of personalized orthopedics: Kinematic modeling to restore premorbid knee functionality through robotic assisted TKA
- Subject-specific lower limb modeling and evaluation with a force-dependent kinematics natural knee model
Selected papers
- Tzanetis P, Fluit R, de Souza K, Robertson S, Koopman B, Verdonschot N, (2023), “Pre-Planning the Surgical Target for Optimal Implant Positioning in Robotic-Assisted Total Knee Arthroplasty”. Bioengineering, vol. 10, pp. 543. [ DOI, WWW ]
- Zhang Y, Chen Z, Zhao H, Zhao D, Zhang X, Ma X, Jin Z, (2022), “Comparison of joint load, motions and contact stress and bone‐implant interface micromotion of three implant designs for total ankle arthroplasty”. Comput. Methods Programs Biomed., vol. 223, pp. 106976. [ DOI, WWW ]
- Zhang Y, Chen Z, Zhao D, Yu J, Ma X, Jin Z, (2022), “Anatomic ankle implant can provide better tibiotalar joint kinematics and loading”. Med. Eng. Phys., vol. 103, pp. 103789. [ DOI, WWW ]
- Dejtiar DL, Bartsoen L, Wesseling M, Wirix-Speetjens R, Sloten JV, Perez MA, (2020), “Standard Cruciate-Retaining Total Knee Arthroplasty Implants can Reproduce Native Kinematics”. Book Chapter, In: F. Rodriguez Y Baena and F. Tatti (eds.), (Ed), CAOS 2020 (EPiC Series in Health Sciences, vol. 4), vol. 4, pp. 61–64.
- Dejtiar DL, Dzialo CM, Pedersen PH, Jensen KK, Fleron M, Andersen MS (2019), “Development and evaluation of a subject-specific lower limb model with an 11 DOF natural knee model using MRI and EOS during a quasi-static lunge“, J. Biomech. Eng.. [DOI]
More papers on orthopedics