Abstract

The development of consistent procedures with the inclusion of patient-specific data is essential in the computational modeling of biological processes, in order to achieve clinical relevant data. In this work, these issues are addressed with the development of a methodology that combines the gold standard technique for bone mineral density measurement and osteoporosis diagnosis, Dual energy X-ray absorptiometry (DXA), with a computational model for bone remodeling simulation. The DXA results were divided in three samples constituted from proximal femur DXA exams of patients in different stages of bone mineral density (normal, osteopenia and osteoporosis). These results were quantitatively compared with computational model results. A correlation study was performed between femoral neck T-score and a parameter from the model to ascertain the hypothesis of adjusting the model accordingly to biological variables. The results evidenced the predictive ability of the computational model in the estimation of femoral neck bone mineral content (BMC), with a maximum relative error of 3.92%. On the other hand, a strong correlation ( R=−0.862) was found between the variables in study and a mathematical relationship was obtained to estimate the range of values for a model parameter that leads to biological relevant results. The methodology developed and the results obtained represent a solid and reliable basis to further studies on bone quality, ensuring the validity of the computational model in the simulation of bone remodeling process.

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