Prediction of jaw opening function after mandibular reconstruction using subject-specific musculoskeletal modelling.

BACKGROUND: Mandibular reconstruction patients often suffer abnormalities in the mandibular kinematics. In silico simulations, such as musculoskeletal modelling, can be used to predict post-operative mandibular kinematics. It is important to validate the mandibular musculoskeletal model and analyse the factors influencing its accuracy. OBJECTIVES: To investigate the jaw opening-closing movements after mandibular reconstruction, as predicted by the subject-specific musculoskeletal model, and the factors influencing its accuracy. METHODS: Ten mandibular reconstruction patients were enrolled in this study. Cone-beam computed tomography images, mandibular movements, and surface electromyogram signals were recorded preoperatively. A subject-specific mandibular musculoskeletal model was established to predict surgical outcomes using patient-averaged muscle parameter changes as model inputs. Jaw bone geometry was replaced by surgical planning results, and the muscle insertion sites were registered based on the non-rigid iterative closest point method. The predicted jaw kinematic data were validated based on 6-month post-operative measurements. Correlations between the prediction accuracy and patient characteristics (age, pathology and surgical scope) were further analysed. RESULTS: The root mean square error (RMSE) for lower incisor displacement was 31.4%, and the error for peak magnitude of jaw opening was 4.9 mm. Age, post-operative infection and radiotherapy influenced the prediction accuracy. The amount of masseter detachment showed little correlation with jaw opening. CONCLUSION: The mandibular musculoskeletal model successfully predicted short-range jaw opening functions after mandibular reconstruction. It provides a novel surgical planning method to predict the risk of developing trismus.

Self-Similar Functional Circuit Models of Arteries and Deterministic Fractal Operators: Theoretical Revelation for Biomimetic Materials.

In this paper, the self-similar functional circuit models of arteries are proposed for bioinspired hemodynamic materials design. Based on the mechanical-electrical analogous method, the circuit model can be utilized to mimic the blood flow of arteries. The theoretical mechanism to quantitatively simulate realistic blood flow is developed by establishing a fractal circuit network with an infinite number of electrical components. We have found that the fractal admittance operator obtained from the minimum repeating unit of the fractal circuit can simply and directly determine the blood-flow regulation mechanism. Furthermore, according to the operator algebra, the fractal admittance operator on the aorta can be represented by Gaussian-type convolution kernel function. Similarly, the arteriolar operator can be described by Bessel-type function. Moreover, by the self-similar assembly pattern of the proposed model, biomimetic materials which contain self-similar circuits can be designed to mimic physiological or pathological states of blood flow. Studies show that the self-similar functional circuit model can efficiently describe the blood flow and provide an available and convenient structural theoretical revelation for the preparation of in vitro hemodynamic bionic materials.

Designing customized temporomandibular fossa prosthesis based on envelope surface of condyle movement: validation via in silico musculoskeletal simulation.

Objective: This study presents an innovative articular fossa prosthesis generated by the envelope surface of condyle movement, and compares its mandible movements, muscle activities, and joint reaction forces with two temporomandibular joint (TMJ) prostheses using multibody musculoskeletal simulation. Methods: A healthy 23-year-old female was recruited for this study. Cone-beam computed tomographic (CBCT) was performed to reconstruct the mandibular bone geometry. A customized TMJ fossa prosthesis was designed based on the subject-specific envelope surface of condyle movement (ESCM). Mandibular kinematics and jaw-closing muscle electromyography (EMG) were simultaneously recorded during maximum jaw opening-closing movements. To validate our prosthesis design, a mandibular musculoskeletal model was established using flexible multibody dynamics and the obtained kinematics and EMG data. The Biomet fossa prosthesis and the ellipsoidal fossa prosthesis designed by imitating the lower limb prostheses were used for comparison. Simulations were performed to analyze the effects of different fossa prostheses on jaw opening-closing motions, mandibular muscle activation, and contact forces. Results: The maximum opening displacement for the envelope-based fossa prosthesis was greater than those for Biomet and ellipsoidal prostheses (36 mm, 35 mm, and 33 mm, respectively). The mandibular musculoskeletal model with ellipsoidal prosthesis led to dislocation near maximal jaw opening. Compared to Biomet, the envelope-based fossa reduced the digastric and lateral pterygoid activation at maximal jaw opening. It also reduced the maximal resistance to condylar sliding on the intact side by 63.2 N. Conclusion: A customized TMJ fossa prosthesis was successfully developed using the ESCM concept. Our study of musculoskeletal multibody modeling has highlighted its advantages and potential. The artificial fossa design successfully achieved a wider condylar range of motion. It also reduced the activation of jaw opening muscles on the affected side and resistance on the intact side. This study showed that an ESCM-based approach may be useful for optimizing TMJ fossa prostheses design.

EMG-assisted forward dynamics simulation of subject-specific mandible musculoskeletal system.

Assessment of mandibular dynamics is essential for examining stomatognathic functions, and many kinds of stomatognathic diseases, such as temporomandibular joint (TMJ) disorder and jaw tumors, require individual diagnosis and rehabilitation treatments. Musculoskeletal models of the mandible system provide an efficient tool for fulfilling these tasks, but most existing models are generic, without direct correlation to subject-specific data. For this reason, the objective of this study was to establish a subject-specific mandible modeling framework based on clinical measurements, including medical imaging, jaw kinematics, and electromyographic (EMG) acquisition. First, a non-rigid iterative closest point method was performed to register muscle insertion sites. A flexible multibody approach was introduced to describe the large deformation behavior of jaw muscles. The EMG signals of the temporalis and masseter muscles were then utilized to determine their active forces. Meanwhile, a feedback loop for tracking desired mandibular kinematics was presented to calculate the activations of jaw opening and pterygoid muscles. The subject-specific muscle forces and TMJ joint loading during jaw opening-closing movements were then calculated based on forward-inverse coupling dynamics procedure. As a validation of the proposed framework, the mandible trajectories of seven healthy subjects were predicted and compared with experimental data. The results demonstrated unintentional movement of the head-neck complex together with the activation patterns of jaw opening and lateral pterygoid muscles for different people. The proposed framework combines musculoskeletal modeling with dental biomechanical testing, providing an efficient method of predicting and understanding the dynamics of subject-specific mandible systems.