Evidence map›Paper›PMID 40252160›Full record

ArticleBiomechanics and modeling in mechanobiology2025

Comparing the predictions of CT-based subject-specific finite element models of human metastatic vertebrae with digital volume correlation measurements.

Chiara Garavelli, Alessandra Aldieri, Marco Palanca, Enrico Dall'Ara, Marco Viceconti

Abstract readComparative Study
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

11 citing papers in PubMed.

  1. Article
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  5. Review
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  8. Review
  9. Can Multi-Vertebral CT-Based Finite Element Models Accurately Predict Strains? An In Vitro Validation Study.International journal for numerical methods in biomedical engineering · 2025
    Article
  10. Article
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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

5 authors.

Chiara GaravelliDepartment of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy.ORCID http://orcid.org/0000-0002-6921-0730
Alessandra AldieriPolitoBIOMedLab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca Degli Abruzzi, 24, Turin, Italy. alessandra.aldieri@polito.it.ORCID http://orcid.org/0000-0002-2397-3353
Marco PalancaDepartment of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy.ORCID http://orcid.org/0000-0002-1231-2728
Enrico Dall'AraDivision of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0003-1471-5077
Marco VicecontiDepartment of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy.ORCID http://orcid.org/0000-0002-2293-1530

Funding

AOSpine Discovery and Innovation Awards AOSDIA 2019_063_TUM_PalancaEngineering and Physical Sciences Research Council (EPSRC) Frontier Multisim Grant EP/K03877X/1 and EP/S032940/1European Commission 101016503European Commission 823712Marie Skłodowska-Curie Individual Fellowship 832430/2018
6 · The paper itself

Abstract

Several conditions can increase the incidence of vertebral fragility fractures, including metastatic bone disease. Computational tools could help clinicians estimate the risk of vertebral fracture in these patients; however, comparison with in vitro data is mandatory before using them in clinical practice. Nine spine segments were tested under compression and imaged with micro-computed tomography (µCT). The displacement field was calculated for each vertebra using a global digital volume correlation (DVC) approach. Subject-specific homogenised finite element models of each vertebra were built from µCT images, applying experimentally matched boundary conditions at the endplates. Numerical and experimental displacements, reaction forces, and locations showing higher strain concentrations were eventually compared. Additionally, given that µCT cannot be performed in clinical settings, the outcomes of a µCT-based model were also compared to those of a model built from clinical CT scans of the same specimen. Good agreement between DVC and µCT-based FE displacements was found, both for healthy (R

Indexed as

Finite Element AnalysisSpinal NeoplasmsSpineTomography, X-Ray ComputedX-Ray MicrotomographyBiomechanical PhenomenaFemaleHumansMaleMiddle AgedStress, MechanicalDigital volume correlationFinite element modelFracture predictionValidationVertebra

Identifiers

PMID40252160
PMCPMC12162702

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.