Szyszko, Julia Aleksandra ;
Aldieri, Alessandra ;
Baruffaldi, Fabio ;
Viceconti, Marco
(2026)
Load-to-Failure Prediction Through CT-Based Subject-Specific FE Models.
Alma Mater Studiorum - Università di Bologna.
DOI
10.6092/unibo/amsacta/9101.
[Dataset]
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Abstract
This dataset contains the data and supporting materials generated for the study “Load-to-Failure Prediction Through CT-Based Subject-Specific FE Models: Effect of the Adopted CT Scanning Protocol.”
Two cadaveric femurs and a calibration phantom were scanned using CT protocols combining two slice thicknesses (0.625 and 1.25 mm) and tube currents ranging from 80 to 180 mA. Subject-specific FE models were generated for each CT protocol, and sideways-fall simulations were performed to quantify and compare load-to-failure using the BBCT-hip pipeline [1].
The dataset includes processed finite element meshes, protocol-specific material properties, nodal maximum and minimum principal strains for each model, and load-to-failure values. Detailed instructions describing the CT-based FE modelling workflow are also provided to support reproducibility. Raw CT data from the scanned femurs and calibration phantom are additionally included.
Abstract
This dataset contains the data and supporting materials generated for the study “Load-to-Failure Prediction Through CT-Based Subject-Specific FE Models: Effect of the Adopted CT Scanning Protocol.”
Two cadaveric femurs and a calibration phantom were scanned using CT protocols combining two slice thicknesses (0.625 and 1.25 mm) and tube currents ranging from 80 to 180 mA. Subject-specific FE models were generated for each CT protocol, and sideways-fall simulations were performed to quantify and compare load-to-failure using the BBCT-hip pipeline [1].
The dataset includes processed finite element meshes, protocol-specific material properties, nodal maximum and minimum principal strains for each model, and load-to-failure values. Detailed instructions describing the CT-based FE modelling workflow are also provided to support reproducibility. Raw CT data from the scanned femurs and calibration phantom are additionally included.
Tipologia del documento
Dataset
Autori
Parole chiave
CT-based FE modelling; CT acquisition protocol; Femur FE model; Femoral load-to-failure estimation in silico;
Settori scientifico-disciplinari
DOI
Contributors
Data di deposito
28 Ago 2026 08:24
Ultima modifica
28 Ago 2026 08:27
Nome del Progetto
Programma di finanziamento
Italian Complementary National Plan (PNC) - PNC-I.1 – “Research initiatives for innovative technologies and pathways in the health and welfare sector”
URI
Altri metadati
Tipologia del documento
Dataset
Autori
Parole chiave
CT-based FE modelling; CT acquisition protocol; Femur FE model; Femoral load-to-failure estimation in silico;
Settori scientifico-disciplinari
DOI
Contributors
Data di deposito
28 Ago 2026 08:24
Ultima modifica
28 Ago 2026 08:27
Nome del Progetto
Programma di finanziamento
Italian Complementary National Plan (PNC) - PNC-I.1 – “Research initiatives for innovative technologies and pathways in the health and welfare sector”
URI
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