PATIENT-SPECIFIC MUSCULOSKELETAL MODELS TO IMPROVE PREDICTABILITY OF FUNCTIONAL RECOVERY OF PATIENTS REQUIRING SEVERE RECONSTRUCTIVE SURGERY

INTRODUCTION The burden of Musculoskeletal (M-S) diseases and prosthetic revision operations is huge and increasing rapidly with the aging population. For patients that require a major surgical intervention, procedures are unsafe, uncertain in outcome and have a high complication rate. The goal of this project is to create an ICT-based patient-specific surgical navigation system that helps the surgeon safely reaching the optimal functional result for the patient and is a user friendly training facility for the surgeons. The purpose of this paper is to demonstrate the advancements in personalized musculoskeletal modeling for patients who require severe reconstructive surgery of the lower extremity. METHODS TLEM safe is a European Project dedicated to generating semi-automated 3-D image-analyzing tools to simulate the musculoskeletal (M-S) system. The patient-specific parameters are fed into models with which the patient specific functional outcome can be predicted. Hence, we can analyze the functional effect e.g. due to placement of prosthetic components in a patient. Surgeons can virtually operate on the patient-specific model after which the model predicts the functional effects. Once the optimal plan is selected, this is fed into a computer navigation system (see figure 1). RESULTS The applicability of personalized musculoskeletal models is demonstrate in 10 healthy subjects: in the personalized models the muscle activation levels were much more physiological than those generated in scaled models. Hence, scaled models (as commonly used) were much less suitable to assess muscle forces and joint contact forces than personalized models. To enable usage of the personalized models for patient related issues we developed a Surgery Planning Environment 3D (SPE3D) (figure 1), which allows the surgeon to operate on the virtual patient. We have made personalized models of osteosarcoma patients and patients suffering from hip dysplasia (see figures 2 and 3). Currently we are comparing the functional predictions of the models to those occurring in these two patient categories. CONCLUSION Considerable progress in patient specific modeling has been made. This capability in conjunction with a surgeon friendly virtual pre-planner has opened the way to quantify the functional outcome of severe musculoskeletal surgery in a clinically relevant manner. Significance TLEMsafe aids the surgeon to preplan the surgery and optimize post-operative functional outcome for patients requiring reconstructive surgery for hip reconstruction or tumor surgery of the lower extremity. By using TLEMsafe the quality of the treatment can be improved.