Evidence map›Paper›PMID 42367376›Full record

ArticleFrontiers in bioengineering and biotechnology2026

Understanding the influence of geometry and material properties on femoral and tibial stress and strain analysis in a paediatric population for single-leg standing simulation.

Seraina Kämpf, Yidan Xu, Julie Choisne

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Article in Frontiers in bioengineering and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Seraina KämpfInstitute for Biomechanics, ETH Zurich, Zürich, Switzerland.
Yidan XuAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Julie ChoisneAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Paediatric Finite Element (FE) models of bones are scarce due to data Q7 unavailability. Recent research has developed statistical shape and density models (SSDMs) for paediatric populations, enabling good predictions of bone geometry and bone mineral density (BMD). However, the impact of bone shape and material property accuracy on stress and strain calculation remains poorly understood. Therefore, the aim of this study was to investigate the influence of geometry and material property accuracies on Von Mises stress and 1st principalstrain distribution in paediatric femora and tibiae. Methods: Patient-specific bone geometry and BMD were extracted from 330 paediatric CT scans. Subsequently, two paediatric SSDMs were created, which can predict bone shape and BMD for the femur and tibia, respectively. Next, nine FE models were built for each femur and tibia in the dataset using different inputs for geometry and material properties: i) patient-specific from the CT scans; ii) predicted from the SSDM; iii) generic from the literature. Von Mises stresses and 1st principal strains were compared between the models under identical loading conditions. Results: The results showed that using SSDM-predicted or generic material properties increased the Von Mises stress and 1st principal strain Root Mean Square Errors compared to using material properties derived from CT scans. SSDM-predicted geometry and genericbased geometry associated with CT-based material properties showed the lowest errors of the eight models compared to the CT-based geometry and material properties model. Discussion: The results show a trend toward a greater influence of material property inaccuracies on the Von Mises stress and 1st principal strain distribution than geometry for this paediatric population.

Indexed as

femurfinite element analysispaediatric bonestatistical shape and density modeltibia

Identifiers

PMID42367376
PMCPMC13294268

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