Evidence map›Paper›PMID 28004226›Full record

ArticleBiomechanics and modeling in mechanobiology2017

Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments.

Lorenzo Grassi, Sami P Väänänen, Matti Ristinmaa, Jukka S Jurvelin, Hanna Isaksson

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
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

17 citing papers in PubMed, 48 citations in OpenAlex.

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  13. Perspectives on the non-invasive evaluation of femoral strength in the assessment of hip fracture risk.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2020
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  17. Sideways fall-induced impact force and its effect on hip fracture risk: a review.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2017
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Lorenzo GrassiDepartment of Biomedical Engineering, Lund University, BMC D13, 221 84, Lund, Sweden. lorenzo.grassi@bme.lth.se.ORCID http://orcid.org/0000-0001-7824-9947
Sami P VäänänenDepartment of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Matti RistinmaaDivision of Solid Mechanics, Lund University, Lund, Sweden.
Jukka S JurvelinDepartment of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Hanna IsakssonDepartment of Biomedical Engineering, Lund University, BMC D13, 221 84, Lund, Sweden.
Lund University · SEUniversity of Eastern Finland · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computed tomography (CT)-based finite element (FE) models may improve the current osteoporosis diagnostics and prediction of fracture risk by providing an estimate for femoral strength. However, the need for a CT scan, as opposed to the conventional use of dual-energy X-ray absorptiometry (DXA) for osteoporosis diagnostics, is considered a major obstacle. The 3D shape and bone mineral density (BMD) distribution of a femur can be reconstructed using a statistical shape and appearance model (SSAM) and the DXA image of the femur. Then, the reconstructed shape and BMD could be used to build FE models to predict bone strength. Since high accuracy is needed in all steps of the analysis, this study aimed at evaluating the ability of a 3D FE model built from one 2D DXA image to predict the strains and fracture load of human femora. Three cadaver femora were retrieved, for which experimental measurements from ex vivo mechanical tests were available. FE models were built using the SSAM-based reconstructions: using only the SSAM-reconstructed shape, only the SSAM-reconstructed BMD distribution, and the full SSAM-based reconstruction (including both shape and BMD distribution). When compared with experimental data, the SSAM-based models predicted accurately principal strains (coefficient of determination >0.83, normalized root-mean-square error <16%) and femoral strength (standard error of the estimate 1215 N). These results were only slightly inferior to those obtained with CT-based FE models, but with the considerable advantage of the models being built from DXA images. In summary, the results support the feasibility of SSAM-based models as a practical tool to introduce FE-based bone strength estimation in the current fracture risk diagnostics.

Indexed as

Absorptiometry, PhotonBone DensityFemurFinite Element AnalysisFractures, BoneHumansOsteoporosisReproducibility of ResultsTomography, X-Ray ComputedFinite elementProximal femurStatistical appearance modelStatistical shape modelValidation

Identifiers

PMID28004226
PMCPMC5422489
OpenAlexW2565466202

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.