Evidence map›Paper›PMID 41946845›Full record

ArticleScientific reports2026

Assessing the reproducibility of a subject-specific finite element modelling pipeline for the human metastatic vertebrae.

Robert Roger, Rajdeep Ghosh, Yuanrui Cai, Fiona Gibson, Áron Lazáry, Lingzhong Guo, Damien Lacroix, Enrico Dall'Ara

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Robert RogerInsigneo Institute, The University of Sheffield, Sheffield, UK.
Rajdeep GhoshInsigneo Institute, The University of Sheffield, Sheffield, UK.
Yuanrui CaiInsigneo Institute, The University of Sheffield, Sheffield, UK.
Fiona GibsonInsigneo Institute, The University of Sheffield, Sheffield, UK.
Áron LazáryNational Center for Spinal Disorders, Budapest, Hungary.
Lingzhong GuoInsigneo Institute, The University of Sheffield, Sheffield, UK.
Damien LacroixInsigneo Institute, The University of Sheffield, Sheffield, UK.
Enrico Dall'AraInsigneo Institute, The University of Sheffield, Sheffield, UK. e.dallara@sheffield.ac.uk.

Funding

European Commission EU H2022 grant ID 101080135European Commission and UK Research and Innovation EU H2022 grant ID 101080135; UKRI Horizon Europe Guarantee Extension ID: 10075325
6 · The paper itself

Abstract

Computed tomography (CT)-based subject-specific finite element (SS-FE) models offer a quantitative approach to assessing the stability of metastatic vertebrae. A critical step in developing SS-FE models is image segmentation, however automatic techniques fail to accurately capture the altered contours of metastatic vertebrae, making manual image segmentation the preferred approach. This introduces operator-dependent steps into the CT-to-FE modelling pipeline that may influence the model's mechanical properties. To assess these dependencies, this study evaluated intra- and inter-operator reproducibility of a CT-to-FE pipeline applied to six lumbar vertebrae, three radiologically healthy and three lytic metastases. All models were developed using a standardised pipeline incorporating densitometric calibration, 1 mm quadratic tetrahedral meshing, and heterogeneous isotropic elasto-plastic material properties, with vertebrae loaded in uniaxial compression to 1.9% apparent strain. Geometrical/volumetrical metrics from segmented images and mechanical metrics from the SS-FE models were assessed. Intra-operator reproducibility was high across geometric and mechanical metrics, whereas inter-operator reproducibility showed modest variability, particularly in local mechanical metrics of metastatic vertebrae. Consistent volumetric inconsistencies between segmentations significantly correlated with variation in predicted failure load of SS-FE models. Overall reproducibility was high, demonstrating the reliability of the CT-based SS-FE modelling pipeline for estimating vertebral strength.

Indexed as

Finite Element AnalysisLumbar VertebraeSpinal NeoplasmsHumansReproducibility of ResultsTomography, X-Ray ComputedComputed tomographyFinite element modellingImage segmentationMetastatic vertebraeReproducibilitySubject-specific

Identifiers

PMID41946845
PMCPMC13199536

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