A patient-specific musculoskeletal model of total knee arthroplasty to predict in vivo knee biomechanics

Marco A. Marra, Valentine Vanheule, René Fluit, Bart F.J.M. Koopman, John Rasmussen, Nico Verdonschot, Michael S. Andersen

    Research output: Contribution to conferenceAbstract

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    Abstract

    Musculoskeletal(MS) models are useful to gain information on in vivo biomechanics that would be otherwise very difficult to obtain.However, before entering the clinical routine MS models must be thoroughlyvalidated. This study presents a novel MS modelling framework capable ofintegrating the patient-specific MS architecture in a very detailed way, andsimultaneously simulating body level dynamics and secondary knee kinematics.The model predictions were further validated against publicly available in vivo experimental data.

    The bonegeometries were segmented from CT images of a patient with an instrumentedTotal Knee Arthroplasty (TKA) from the “Grand Challenge Competition to Predict In Vivo Knee Loads” dataset. These were inputtedinto an advanced morphing technique in order to scale the MS architecture of thenew TLEM 2.0 model1 to the specific patient. A detailed 11-DOF modelof the knee joint was constructed that included ligaments and rigid contact. Aninverse kinematic and a force-dependent kinematic technique2 wereutilized to simulate one gait cycle and one right-turn trial. Tibiofemoral (TF)joint contact force predictions were evaluated against experimental TF forcesrecorded by the TKA prosthesis, and secondary knee kinematics againstexperimental fluoroscopy data.

    The coefficientof determination and the root-mean-square error between predicted andexperimental tibiofemoral forces were larger than 0.9 and smaller than 0.3body-weights, respectively, for both gait and right-turn trials. Secondary kneekinematics were estimated with an average Sprague and Geers’ combined error assmall as 0.06.

    Themodelling strategy proposed permits a high level of patient-specificpersonalization and does not require any non-physiological parameter tuning.The very good agreement between predictions and experimental in vivo data is promising for the futureintroduction of the model into clinical applications.

    Original languageEnglish
    Publication statusPublished - 22 Jan 2015
    Event5th Dutch Bio-Medical Engineering Conference, BME 2015 - Hotel Zuiderduin, Egmond aan Zee, Netherlands
    Duration: 22 Jan 201523 Jan 2015
    Conference number: 5
    http://www.bme2015.nl/

    Conference

    Conference5th Dutch Bio-Medical Engineering Conference, BME 2015
    Abbreviated titleBME 2015
    CountryNetherlands
    CityEgmond aan Zee
    Period22/01/1523/01/15
    Internet address

    Fingerprint

    Knee Replacement Arthroplasties
    Biomechanical Phenomena
    Knee
    Gait
    Knee Prosthesis
    Fluoroscopy
    Knee Joint
    Ligaments
    Joints
    Weights and Measures

    Keywords

    • METIS-310910

    Cite this

    Marra, M. A., Vanheule, V., Fluit, R., Koopman, B. F. J. M., Rasmussen, J., Verdonschot, N., & Andersen, M. S. (2015). A patient-specific musculoskeletal model of total knee arthroplasty to predict in vivo knee biomechanics. Abstract from 5th Dutch Bio-Medical Engineering Conference, BME 2015, Egmond aan Zee, Netherlands.
    Marra, Marco A. ; Vanheule, Valentine ; Fluit, René ; Koopman, Bart F.J.M. ; Rasmussen, John ; Verdonschot, Nico ; Andersen, Michael S. / A patient-specific musculoskeletal model of total knee arthroplasty to predict in vivo knee biomechanics. Abstract from 5th Dutch Bio-Medical Engineering Conference, BME 2015, Egmond aan Zee, Netherlands.
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    Marra, MA, Vanheule, V, Fluit, R, Koopman, BFJM, Rasmussen, J, Verdonschot, N & Andersen, MS 2015, 'A patient-specific musculoskeletal model of total knee arthroplasty to predict in vivo knee biomechanics' 5th Dutch Bio-Medical Engineering Conference, BME 2015, Egmond aan Zee, Netherlands, 22/01/15 - 23/01/15, .

    A patient-specific musculoskeletal model of total knee arthroplasty to predict in vivo knee biomechanics. / Marra, Marco A.; Vanheule, Valentine; Fluit, René; Koopman, Bart F.J.M.; Rasmussen, John; Verdonschot, Nico; Andersen, Michael S.

    2015. Abstract from 5th Dutch Bio-Medical Engineering Conference, BME 2015, Egmond aan Zee, Netherlands.

    Research output: Contribution to conferenceAbstract

    TY - CONF

    T1 - A patient-specific musculoskeletal model of total knee arthroplasty to predict in vivo knee biomechanics

    AU - Marra, Marco A.

    AU - Vanheule, Valentine

    AU - Fluit, René

    AU - Koopman, Bart F.J.M.

    AU - Rasmussen, John

    AU - Verdonschot, Nico

    AU - Andersen, Michael S.

    PY - 2015/1/22

    Y1 - 2015/1/22

    N2 - Musculoskeletal(MS) models are useful to gain information on in vivo biomechanics that would be otherwise very difficult to obtain.However, before entering the clinical routine MS models must be thoroughlyvalidated. This study presents a novel MS modelling framework capable ofintegrating the patient-specific MS architecture in a very detailed way, andsimultaneously simulating body level dynamics and secondary knee kinematics.The model predictions were further validated against publicly available in vivo experimental data.The bonegeometries were segmented from CT images of a patient with an instrumentedTotal Knee Arthroplasty (TKA) from the “Grand Challenge Competition to Predict In Vivo Knee Loads” dataset. These were inputtedinto an advanced morphing technique in order to scale the MS architecture of thenew TLEM 2.0 model1 to the specific patient. A detailed 11-DOF modelof the knee joint was constructed that included ligaments and rigid contact. Aninverse kinematic and a force-dependent kinematic technique2 wereutilized to simulate one gait cycle and one right-turn trial. Tibiofemoral (TF)joint contact force predictions were evaluated against experimental TF forcesrecorded by the TKA prosthesis, and secondary knee kinematics againstexperimental fluoroscopy data.The coefficientof determination and the root-mean-square error between predicted andexperimental tibiofemoral forces were larger than 0.9 and smaller than 0.3body-weights, respectively, for both gait and right-turn trials. Secondary kneekinematics were estimated with an average Sprague and Geers’ combined error assmall as 0.06.Themodelling strategy proposed permits a high level of patient-specificpersonalization and does not require any non-physiological parameter tuning.The very good agreement between predictions and experimental in vivo data is promising for the futureintroduction of the model into clinical applications.

    AB - Musculoskeletal(MS) models are useful to gain information on in vivo biomechanics that would be otherwise very difficult to obtain.However, before entering the clinical routine MS models must be thoroughlyvalidated. This study presents a novel MS modelling framework capable ofintegrating the patient-specific MS architecture in a very detailed way, andsimultaneously simulating body level dynamics and secondary knee kinematics.The model predictions were further validated against publicly available in vivo experimental data.The bonegeometries were segmented from CT images of a patient with an instrumentedTotal Knee Arthroplasty (TKA) from the “Grand Challenge Competition to Predict In Vivo Knee Loads” dataset. These were inputtedinto an advanced morphing technique in order to scale the MS architecture of thenew TLEM 2.0 model1 to the specific patient. A detailed 11-DOF modelof the knee joint was constructed that included ligaments and rigid contact. Aninverse kinematic and a force-dependent kinematic technique2 wereutilized to simulate one gait cycle and one right-turn trial. Tibiofemoral (TF)joint contact force predictions were evaluated against experimental TF forcesrecorded by the TKA prosthesis, and secondary knee kinematics againstexperimental fluoroscopy data.The coefficientof determination and the root-mean-square error between predicted andexperimental tibiofemoral forces were larger than 0.9 and smaller than 0.3body-weights, respectively, for both gait and right-turn trials. Secondary kneekinematics were estimated with an average Sprague and Geers’ combined error assmall as 0.06.Themodelling strategy proposed permits a high level of patient-specificpersonalization and does not require any non-physiological parameter tuning.The very good agreement between predictions and experimental in vivo data is promising for the futureintroduction of the model into clinical applications.

    KW - METIS-310910

    M3 - Abstract

    ER -

    Marra MA, Vanheule V, Fluit R, Koopman BFJM, Rasmussen J, Verdonschot N et al. A patient-specific musculoskeletal model of total knee arthroplasty to predict in vivo knee biomechanics. 2015. Abstract from 5th Dutch Bio-Medical Engineering Conference, BME 2015, Egmond aan Zee, Netherlands.