Mechanical Characterization and Standardization of Silicon Scalp and Dura Surrogates for Neurosurgical Simulation.

BACKGROUND: Simulation-based neurosurgical training allows the development of surgical skills outside the operating room. However, the use of nonstandardized materials and poor haptic feedback remain the primary limitations of the surgical simulators. Therefore, this work proposes a comprehensive scheme for scalp and dura surrogate synthesis and their standardization for neurosurgical training. METHODS: Eight different variants of silicone-based scalp (S1-S8) and dura (D1-D8) surrogates were synthesized. The samples were evaluated by 26 neurosurgeons. They provided their feedback in a Likert scale questionnaire. Kruskal-Wallis test with Dunn multiple comparisons was used for statistical analysis of surgeons' scores. The samples were mechanically characterized using Shore A hardness and dynamic nanoindentation testing. RESULTS: The highest mean Likert score values were obtained for S3 scalp and D8 dura variants. The comparison of S3 and D8 with the rest of the variants in the respective groups was statistically significant in 21 of 28 instances. The average Shore A hardness and storage modulus of the S3 variant were 21.9 DU and 505.3 kPa, respectively. The corresponding values for the D8 variant were 32.5 DU and 632 kPa, respectively. CONCLUSIONS: This study proposes a method for the synthesis, evaluation, and standardization of scalp and dura surrogates. The study achieved standardized silicone compositions along with a recommendable range of Shore hardness and viscoelastic moduli values for the scalp and dura surrogates. This work can be extended for the standardization of surrogates for other tissues involved in neurosurgical simulators.

A Simplistic Approach to Bone Healing Simulation.

A simple computational approach to simulation of healing in long bone fractures is presented. In particular, an algorithm that could simulate the formation, maturation, and resorption of fracture callus is developed and validated. The simplicity of the approach lies in the fact that the algorithm uses only the applied load and a single constraint parameter for the entire simulation. The work hypothesizes bone healing as a comprehensive energy minimization process where mechanical stimulation is proposed as the primary precursor for the beginning of different stages (i.e., callus formation, mineralization, and resorption). As such, the hypothesis is derived from the second law of thermodynamics which states that the energy of a closed system should be minimum at equilibrium. Alternatively, each stage of healing bone healing may be termed a state of homeostasis. The validation is done through a multi-material, time-based simulation of bone healing in a damaged tibia. The simulation uses a cross-section-based finite element model and an advanced version of an already validated structural optimization algorithm. The optimization objective is to minimize overall strain energy for the entire process, subject to a polar first moment of mass constraint. The simulation results show different stages of healing, where the algorithm generates a callus geometry similar to those observed experimentally. Eventually, a geometry similar to that in an intact cross-section is achieved by resorption of the callus from the unwanted sites.

Exploring conditions that make cortical bone geometry optimal for physiological loading.

While physiological loading on lower long bones changes during bone development, the bone cross section either remains circular or slowly changes from nearly circular to other shapes such as oval and roughly triangular. Bone is said to be an optimal structure, where strength is maximized using the optimal distribution of bone mass (also called Wolff's law). One of the most appropriate mathematical validations of this law would be a structural optimization-based formulation where total strain energy is minimized against a mass and a space constraint. Assuming that the change in cross section during bone development and homeostasis after adulthood is direct result of the change in physiological loading, this work investigates what optimization problem formulation (collectively, design variables, objective function, constraints, loading conditions, etc.) results in mathematically optimal solutions that resemble bones under actual physiological loading. For this purpose, an advanced structural optimization-based computational model for cortical bone development and defect repair is presented. In the optimization problem, overall bone stiffness is maximized first against a mass constraint, and then also against a polar first moment of area constraint that simultaneously constrains both mass and space. The investigation is completed in two stages. The first stage is developmental stage when physiological loading on lower long bones (tibia) is a random combination of axial, bending and torsion. The topology optimization applied to this case with the area moment constraint results into circular and elliptical cross sections similar to that found in growing mouse or human. The second investigation stage is bone homeostasis reached in adulthood when the physiological loading has a fixed pattern. A drill hole defect is applied to the adult mouse bone, which would disrupt the homeostasis. The optimization applied after the defect interestingly brings the damaged section back to the original intact geometry. The results, however, show that cortical bone geometry is optimal for the physiological loading only when there is also a constraint on polar moment of area. Further numerical experiments show that application of torsion along with the gait-analysis-based physiological loading improves the results, which seems to indicate that the cortical bone geometry is optimal for some amount of torsion in addition to the gait-based physiological loading. This work has a potential to be extended to bone growth/development models and fracture healing models, where topology optimization and polar moment of area constraint have not been introduced earlier.