Bioengineering of exercise: biomechanical and metabolic aspects

The field of research of this dissertation concerns the bioengineering of exercise, in particular the relationship between biomechanical and metabolic knowledge. This relationship can allow to evaluate exercise in many different circumstances: optimizing athlete performance, understanding and helping compensation in prosthetic patients and prescribing exercise with high caloric consumption and minimal joint loading to obese subjects. Furthermore, it can have technical application in fitness and rehabilitation machine design, predicting energy consumption and joint loads for the subjects who will use the machine. The aim of this dissertation was to further understand how mechanical work and metabolic energy cost are related during movement using interpretative models. Musculoskeletal models, when including muscle energy expenditure description, can be useful to address this issue, allowing to evaluate human movement in terms of both mechanical and metabolic energy expenditure. A whole body muscle-skeletal model that could describe both biomechanical and metabolic aspects during movement was identified in literature and then was applied and validated using an EMG-driven approach. The advantage of using EMG driven approach was to avoid the use of arbitrary defined optimization functions to solve the indeterminate problem of muscle activations. A sensitivity analysis was conducted in order to know how much changes in model parameters could affect model outputs: the results showed that changing parameters in between physiological ranges did not influence model outputs largely. In order to evaluate its predicting capacity, the musculoskeletal model was applied to experimental data: first the model was applied in a simple exercise (unilateral leg press exercise) and then in a more complete exercise (elliptical exercise). In these studies, energy consumption predicted by the model resulted to be close to energy consumption estimated by indirect calorimetry for different intensity levels at low frequencies of movement. The use of muscle skeletal models for predicting energy consumption resulted to be promising and the use of EMG driven approach permitted to avoid the introduction of optimization functions. Even though many aspects of this approach have still to be investigated and these results are preliminary, the conclusions of this dissertation suggest that musculoskeletal modelling can be a useful tool for addressing issues about efficiency of movement in healthy and pathologic subjects.

Development of musculoskeletal models for the design and the pre-clinical validation of hip resurfacing prosthesis

Background. The surgical treatment of dysfunctional hips is a severe condition for the patient and a costly therapy for the public health. Hip resurfacing techniques seem to hold the promise of various advantages over traditional THR, with particular attention to young and active patients. Although the lesson provided in the past by many branches of engineering is that success in designing competitive products can be achieved only by predicting the possible scenario of failure, to date the understanding of the implant quality is poorly pre-clinically addressed. Thus revision is the only delayed and reliable end point for assessment. The aim of the present work was to model the musculoskeletal system so as to develop a protocol for predicting failure of hip resurfacing prosthesis. Methods. Preliminary studies validated the technique for the generation of subject specific finite element (FE) models of long bones from Computed Thomography data. The proposed protocol consisted in the numerical analysis of the prosthesis biomechanics by deterministic and statistic studies so as to assess the risk of biomechanical failure on the different operative conditions the implant might face in a population of interest during various activities of daily living. Physiological conditions were defined including the variability of the anatomy, bone densitometry, surgery uncertainties and published boundary conditions at the hip. The protocol was tested by analysing a successful design on the market and a new prototype of a resurfacing prosthesis. Results. The intrinsic accuracy of models on bone stress predictions (RMSE < 10%) was aligned to the current state of the art in this field. The accuracy of prediction on the bone-prosthesis contact mechanics was also excellent (< 0.001 mm). The sensitivity of models prediction to uncertainties on modelling parameter was found below 8.4%. The analysis of the successful design resulted in a very good agreement with published retrospective studies. The geometry optimisation of the new prototype lead to a final design with a low risk of failure. The statistical analysis confirmed the minimal risk of the optimised design over the entire population of interest. The performances of the optimised design showed a significant improvement with respect to the first prototype (+35%). Limitations. On the authors opinion the major limitation of this study is on boundary conditions. The muscular forces and the hip joint reaction were derived from the few data available in the literature, which can be considered significant but hardly representative of the entire variability of boundary conditions the implant might face over the patients population. This moved the focus of the research on modelling the musculoskeletal system; the ongoing activity is to develop subject-specific musculoskeletal models of the lower limb from medical images. Conclusions. The developed protocol was able to accurately predict known clinical outcomes when applied to a well-established device and, to support the design optimisation phase providing important information on critical characteristics of the patients when applied to a new prosthesis. The presented approach does have a relevant generality that would allow the extension of the protocol to a large set of orthopaedic scenarios with minor changes. Hence, a failure mode analysis criterion can be considered a suitable tool in developing new orthopaedic devices.

Subject-specific musculoskeletal models of the lower limbs for the prediction of skeletal loads during motion

The determination of skeletal loading conditions in vivo and their relationship to the health of bone tissues, remain an open question. Computational modeling of the musculoskeletal system is the only practicable method providing a valuable approach to muscle and joint loading analyses, although crucial shortcomings limit the translation process of computational methods into the orthopedic and neurological practice. A growing attention focused on subject-specific modeling, particularly when pathological musculoskeletal conditions need to be studied. Nevertheless, subject-specific data cannot be always collected in the research and clinical practice, and there is a lack of efficient methods and frameworks for building models and incorporating them in simulations of motion. The overall aim of the present PhD thesis was to introduce improvements to the state-of-the-art musculoskeletal modeling for the prediction of physiological muscle and joint loads during motion. A threefold goal was articulated as follows: (i) develop state-of-the art subject-specific models and analyze skeletal load predictions; (ii) analyze the sensitivity of model predictions to relevant musculotendon model parameters and kinematic uncertainties; (iii) design an efficient software framework simplifying the effort-intensive phases of subject-specific modeling pre-processing. The first goal underlined the relevance of subject-specific musculoskeletal modeling to determine physiological skeletal loads during gait, corroborating the choice of full subject-specific modeling for the analyses of pathological conditions. The second goal characterized the sensitivity of skeletal load predictions to major musculotendon parameters and kinematic uncertainties, and robust probabilistic methods were applied for methodological and clinical purposes. The last goal created an efficient software framework for subject-specific modeling and simulation, which is practical, user friendly and effort effective. Future research development aims at the implementation of more accurate models describing lower-limb joint mechanics and musculotendon paths, and the assessment of an overall scenario of the crucial model parameters affecting the skeletal load predictions through probabilistic modeling.

Musculoskeletal tissue regeneration by human non-embryonic stem cells

The aim of this thesis was to investigate the regenerative potential of alternative sources of stem cells, derived from human dental pulp (hDPSCs) and amniotic fluid (hAFSCs) and, specifically, to evaluate their capability to be committed towards osteogenic and myogenic lineages, for the eventual applicability of these stem cells to translational strategies in regenerative medicine of bone and skeletal muscle tissues. The in vitro bone production by stem cells may represent a radical breakthrough in the treatment of pathologies and traumas characterized by critical bone mass defects, with no medical or surgical solution. Human DPSCs and AFSCs were seeded and pre-differentiated on different scaffolds to test their capability to subsequently reach the osteogenic differentiation in vivo, in order to recover critical size bone defects. Fibroin scaffold resulted to be the best scaffold promoting mature bone formation and defect correction when combined to both hDPSCs and hAFSCs. This study also described a culture condition that might allow human DPSCs to be used for human cell therapy in compliance with good manufacturing practices (GMPs): the use of human serum (HS) promoted the expansion and the osteogenic differentiation of hDPSCs in vitro and, furthermore, allowed pre-differentiated hDPSCs to regenerate critical size bone defects in vivo. This thesis also showed that hDPSCs and hAFSCs can be differentiated towards the myogenic lineage in vitro, either when co-cultured with murine myoblasts and when differentiated alone after DNA demethylation treatment. Interestingly, when injected into dystrophic muscles of SCID/mdx mice - animal model of Duchenne Muscular Dystrophy (DMD) - hDPSCs and hAFSCs pre-differentiated after demethylating treatment were able to regenerate the skeletal muscle tissue and, particularly, to restore dystrophin expression. These observations suggest that human DPSCs and AFSCs might be eventually applied to translational strategies, in order to enhance the repair of injured skeletal muscles in DMD patients.