Simulation Enabled Search for Explanatory Mechanisms of the Fracture Healing Process

Abstract

A significant portion of bone fractures fail to heal properly, increasing healthcare costs. Advances in fracture management have slowed because translational barriers have limited generation of mechanism-based explanations for the healing process. When uncertainties are numerous, analogical modeling can be an effective strategy for developing plausible explanations of complex phenomena. We demonstrate the feasibility of engineering analogical models in software to provide plausible biomimetic explanations for how fracture healing may progress. Concrete analogical models - Callus Analogs - were created using the MASON simulation toolkit. We designated a Target Region initial state within a characteristic tissue section of mouse tibia fracture at day-7 and posited a corresponding day-10 Target Region final state. The goal was to discover a coarse-grain analog mechanism that would enable the discretized initial state to transform itself into the corresponding Target Region final state, thereby providing a new way to study the healing process. One of nine quasi-autonomous Tissue Unit types is assigned to each grid space, which maps to an 80x80 {micro}m region of the tissue section. All Tissue Units have an opportunity each time step to act based on individualized logic, probabilities, and information about adjacent neighbors. Action causes transition from one Tissue Unit type to another, and simulation through several thousand time steps generates a coarse-grain analog - a theory - of the healing process. We prespecified a minimum measure of success: simulated and actual Target Region states achieve [≥] 70% Similarity. We used an iterative protocol to explore many combinations of Tissue Unit logic and action constraints. Workflows progressed through four stages of analog mechanisms. Similarities of 73-90% were achieved for Mechanisms 2-4. The range of Upper-Level similarities increased to 83-94% when we allowed for uncertainty about two Tissue Unit designations. We have demonstrated how Callus Analog experiments provide domain experts with a new medium and tools for thinking about and understanding the fracture healing process.\n\nAuthor summaryTranslational barriers have limited the generation of mechanism-based explanations of fracture healing processes. Those barriers help explain why, to date, biological therapeutics have had only a minor impact on fracture management. New approaches are needed, and we present one that is intended to overcome those barriers incrementally. We created virtual Callus Analogs to simulate how the histologic appearance of a mouse fracture callus may transition from day-7 to day-10. Callus Analogs use software-based model mechanisms. Simulation experiments enable challenging and improving those model mechanisms. During execution, model mechanism operation provides a coarse-grain explanation (a theory) of a four-day portion of the healing process. Simulated day-10 callus histologic images achieved 73-94% similarity to a corresponding day-10 fracture callus image, thus demonstrating feasibility. Simulated healing provides a new perspective on the actual healing process and a new way of thinking about plausible fracture-healing processes. Our working hypothesis is that the approach can be extended to cover more of the healing process while making features of simulated and actual fracture healing increasingly analogous. The methods presented are intended to be extensible to other research areas that use histologic analysis to investigate and explain tissue level phenomena.