This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. (We are requesting an expedited review. I conducted this work with my graduate student, Charles Negus, and during the break, we would like to do one more run in anticipation of a new project. The abstract is below: While mechanobiological bone research begins at or below the cellular level, it finds its ultimate application in improving patient care in a clinical setting. A crucial field of study in bridging the gap between the cellular level research and clinical application is computational mechanics. Stress fracture formation is a mechanically mediated pathology that has the potential to be directly aided by advances in computational methods and mechanobiological research. Stress fracture etiology seems to be a highly patient-specific interplay of bone loads arising from an individuals biomechanics, bone geometry, and bone quality. Bone geometry and quality will inherently reflect both genetic influences and prior functional adaptation. Repeated loads to the bone result in fatigue-like damage accumulation, particularly in highly mineralized, brittle bone where small cracks coalesce into stress fractures under repeated loading [1]. Local remodeling around the fracture which attempts to clear the damage, if it occurs in the presence of continued loading, can actually exacerbate the problem. Assessing an individuals stress fracture potential thus entails assessing their bone quality as well as their peak stresses under repeated loads. Estimating a subjects tibial stress profile suggests a patient-specific finite element analysis, whose geometry is ideally based on low radiation dosage, noninvasive imaging techniques. Assigning trabecular and cortical density distributions to this model present other challenges. We have previously described a novel, but computationally simple approach to density redistribution and orthotropic material alignment [2]. Dynamic Hypoelastic Remodeling is inspired by current understanding of cellular mechanotransduction as being predicated on interstitial fluid flow resulting from dynamic loading. The remodeling algorithm is incorporated in an explicit, dynamic finite element code parallelized using Message Passing Interface. Remodeling occurs at discrete, periodically occurring time steps. Cortical and trabecular apparent densities are updated based on local strain rate, and realignment of principal material directions is driven by the local stress tensor. Stress is calculated using a path-dependent hypoelastic constitutive law, formulated with the Jaumann stress rate. Loading conditions were linearized around instants of peak rate of application during normal gait and stair climbing, assumed to occur with sufficient frequency to exceed the threshold cycle number for cellular remodeling activation. Results from simulations involving the proximal femur indicate that a target strain rate for this dynamic approach is |D_I | = 1.7%/sec. Additionally, we apply DHR to patient-specific 3D models of the tibia. Peripheral quantitative computed tomography (pQCT) scans of the left tibia were collected for female subjects at 4%, 38%, and 66% of tibial length. Based on these three scans, approximate 3D models of the entire tibial surface was estimated by extrapolation. Each subject-specific model tibia was assigned generic epiphyses from the Standardized Tibia Project which were scaled according to her anthropometrics. Then the periosteal boundaries of the pQCT scans were imported into the diaphyseal region, and a 3D lofted surface was generated between the epiphyses and pQCT boundaries. The 3D surface was then meshed with trilinear hexahedral elements. The distal end of the tibia was assumed fixed, and five ramped loading conditions, defined based on each subjects body weight, were applied to the medial and lateral articular surfaces. The diaphyseal density distribution predicted by DHR will be compared against the original pQCT scans to assess the predicted cortical thickness against actual thickness. These models can then be used to conduct patient-specific stress analyses which could aid in assessing peak stresses that could lead to stress fracture. This research illustrates how modern cellular research, imaging techniques, and computational methods can be integrated in a manner which has potential clinical practicality.
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