Aldieri, Alessandra ;
La Mattina, Antonino Amedeo
(2022)
Dataset related to VVUQ main activities to assess the credibility of the Bologna Biomechanical Computed Tomography in silico methodology.
University of Bologna.
DOI
10.6092/unibo/amsacta/7123.
[Dataset]
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Abstract
This dataset contains the details (inputs and outputs) of the main VVUQ activities performed in order to assess the credibility of Bologna Biomechanical Computed Tomography (BBCT)-hip according to ASMEV&V40-2018. BBCT-hip model calculates ARF0, the hip fracture risk upon falling, by modelling a fall to the side. In principle, ARF0 is identified by calculating possible impact forces derived from a fall (through a stochastic mathematical model) and by assessing which of those, exceeding the load to failure (determined through a patient-specific finite element model), lead to a fracture event. More in detail, BBCT-hip uses a stochastic mathematical model to simulate 1,000,000 falls of a body of the height and weight equal to those of the patient, each with initial conditions assigned randomly according to specific probability distributions, and for each of these falls predicts the resulting impact force. In parallel, a patient-specific Finite Element (FE) model of the femur informed by the patient’s QCT data is run 28 times, varying the femur orientation at the impact (femoral impact pose). For each impact pose, the load to failure, i.e. the intensity of the force required to fracture the femur, is computed based on principal strains. The FE model-derived loads to failure inform a reduced-order model (response surface) which allows inferring the magnitude of the load to failure for each possible impact direction at a reasonable computational cost. The surrogate biomarker ARF0 is calculated as the ratio of the number of simulated falls that the model predicts would cause a fracture divided by the total number of simulated falls.
Abstract
This dataset contains the details (inputs and outputs) of the main VVUQ activities performed in order to assess the credibility of Bologna Biomechanical Computed Tomography (BBCT)-hip according to ASMEV&V40-2018. BBCT-hip model calculates ARF0, the hip fracture risk upon falling, by modelling a fall to the side. In principle, ARF0 is identified by calculating possible impact forces derived from a fall (through a stochastic mathematical model) and by assessing which of those, exceeding the load to failure (determined through a patient-specific finite element model), lead to a fracture event. More in detail, BBCT-hip uses a stochastic mathematical model to simulate 1,000,000 falls of a body of the height and weight equal to those of the patient, each with initial conditions assigned randomly according to specific probability distributions, and for each of these falls predicts the resulting impact force. In parallel, a patient-specific Finite Element (FE) model of the femur informed by the patient’s QCT data is run 28 times, varying the femur orientation at the impact (femoral impact pose). For each impact pose, the load to failure, i.e. the intensity of the force required to fracture the femur, is computed based on principal strains. The FE model-derived loads to failure inform a reduced-order model (response surface) which allows inferring the magnitude of the load to failure for each possible impact direction at a reasonable computational cost. The surrogate biomarker ARF0 is calculated as the ratio of the number of simulated falls that the model predicts would cause a fracture divided by the total number of simulated falls.
Tipologia del documento
Dataset
Autori
Parole chiave
ASMEV&V40, in silico trials, model credibility
Settori scientifico-disciplinari
DOI
Contributors
Data di deposito
16 Dic 2022 09:30
Ultima modifica
16 Dic 2022 09:30
Nome del Progetto
Programma di finanziamento
EC - H2020
URI
Altri metadati
Tipologia del documento
Dataset
Autori
Parole chiave
ASMEV&V40, in silico trials, model credibility
Settori scientifico-disciplinari
DOI
Contributors
Data di deposito
16 Dic 2022 09:30
Ultima modifica
16 Dic 2022 09:30
Nome del Progetto
Programma di finanziamento
EC - H2020
URI
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