Final Report Summary - BIOMECHTOOLS (Biomechanical diagnostic, pre-planning and outcome tools to improve musculoskeletal surgery)
Within the ERC project BioMechTools (see www.erc-BioMechTools.eu) we have generated a toolbox which allow us to generate musculoskeletal models of the lower extremity. To create such a model one requires: 1) geometrical information of the structures, 2) information how the knee dynamically deforms and 3) information about the mechanical properties of the tissues involved.
1) We have generated MRI-based automatic segmentation tools to define the geometries of the femur, the tibia and their cartilage layers. The cartilage segementation works on proton density weighted scans which is most often used in clinical practice. Previously, in a European project (www.TLEMsafe.eu) we developed, together with Materialise, segmentation tools for the muscles.
2) The kinematic behavior of the knee was quantified in two ways. The first method was based on dynamic MRI. We developed algorithms which allowed accelerated dynamic MRI scanning of knee kinematics. The accelerated method allows free movement of the knee without any external triggering of joint movement. This is an important step forward as some patients are not able to move (injured or painful) joints at a prescribed frequency. The other method to assess the kinematical behavior of the knee is based on multiple A-mode ultrasound transducers which are 3-D tracked using a motion capture system. By tracking the femoral bone and the tibia bone (each with 15 tansducers), the kinematic behavior of the tibio-femoral joint can be quantified.
3) We have made attempts to determine the mechanical properties of the knee ligaments using MRI techniques. Results show that MRI can be used to give an indication of the stiffness and strength but it need further improvement will it be of use for personalized musculoskeletal modeling. Recently, we utilized ultrasound techniques to assess the strains within the collateral ligaments. The quantification was validated against digital image correlation using an optical method. Future research should focus on how to utilize these measurements in personalized models.
With the developed toolbox (attachment Figure 9) we have developed cadaver specific finite element models with which we showed to be able to optimize ACL reconstructive surgery. We furthermore made a personalized musculoskeletal model in which we demonstrated the effects of total knee replacement variations.
Currently we are working on creating patient specific models of the patella-femoral joint. Hereby, dynamic imaging, muscle properties, cartilage quality and ligament properties are important. We aim for a biomechanical-functional pre-planning system which can be used by the surgeon to optimize his surgery and functional outcome of the patient.
1) We have generated MRI-based automatic segmentation tools to define the geometries of the femur, the tibia and their cartilage layers. The cartilage segementation works on proton density weighted scans which is most often used in clinical practice. Previously, in a European project (www.TLEMsafe.eu) we developed, together with Materialise, segmentation tools for the muscles.
2) The kinematic behavior of the knee was quantified in two ways. The first method was based on dynamic MRI. We developed algorithms which allowed accelerated dynamic MRI scanning of knee kinematics. The accelerated method allows free movement of the knee without any external triggering of joint movement. This is an important step forward as some patients are not able to move (injured or painful) joints at a prescribed frequency. The other method to assess the kinematical behavior of the knee is based on multiple A-mode ultrasound transducers which are 3-D tracked using a motion capture system. By tracking the femoral bone and the tibia bone (each with 15 tansducers), the kinematic behavior of the tibio-femoral joint can be quantified.
3) We have made attempts to determine the mechanical properties of the knee ligaments using MRI techniques. Results show that MRI can be used to give an indication of the stiffness and strength but it need further improvement will it be of use for personalized musculoskeletal modeling. Recently, we utilized ultrasound techniques to assess the strains within the collateral ligaments. The quantification was validated against digital image correlation using an optical method. Future research should focus on how to utilize these measurements in personalized models.
With the developed toolbox (attachment Figure 9) we have developed cadaver specific finite element models with which we showed to be able to optimize ACL reconstructive surgery. We furthermore made a personalized musculoskeletal model in which we demonstrated the effects of total knee replacement variations.
Currently we are working on creating patient specific models of the patella-femoral joint. Hereby, dynamic imaging, muscle properties, cartilage quality and ligament properties are important. We aim for a biomechanical-functional pre-planning system which can be used by the surgeon to optimize his surgery and functional outcome of the patient.