Evidence map›Paper›PMID 29246133›Full record

ArticleBMC musculoskeletal disorders2017

Prediction of fracture load and stiffness of the proximal femur by CT-based specimen specific finite element analysis: cadaveric validation study.

Michiaki Miura, Junichi Nakamura, Yusuke Matsuura, Yasushi Wako, Takane Suzuki, Shigeo Hagiwara, Sumihisa Orita, Kazuhide Inage, Yuya Kawarai, Masahiko Sugano and 2 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC musculoskeletal disorders, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.0field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 55 citations in OpenAlex.

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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

12 authors at 1 institution in 1 country.

Michiaki MiuraDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan. michi.m.55@gmail.com.ORCID http://orcid.org/0000-0003-3913-8130
Junichi NakamuraDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Yusuke MatsuuraDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Yasushi WakoDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Takane SuzukiDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Shigeo HagiwaraDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Sumihisa OritaDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Kazuhide InageDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Yuya KawaraiDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Masahiko SuganoDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Kento NawataDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Seiji OhtoriDepartment of Orthopedic Surgery, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba city, Chiba, 260-8677, Japan.
Chiba University · JP

Funding

Japan Society for the Promotion of Science 25870125
6 · The paper itself

Abstract

backgroundFinite element analysis (FEA) of the proximal femur has been previously validated with large mesh size, but these were insufficient to simulate the model with small implants in recent studies. This study aimed to validate the proximal femoral computed tomography (CT)-based specimen-specific FEA model with smaller mesh size using fresh frozen cadavers.

methodsTwenty proximal femora from 10 cadavers (mean age, 87.1 years) were examined. CT was performed on all specimens with a calibration phantom. Nonlinear FEA prediction with stance configuration was performed using Mechanical Finder (mesh,1.5 mm tetrahedral elements; shell thickness, 0.2 mm; Poisson's coefficient, 0.3), in comparison with mechanical testing. Force was applied at a fixed vertical displacement rate, and the magnitude of the applied load and displacement were continuously recorded. The fracture load and stiffness were calculated from force-displacement curve, and the correlation between mechanical testing and FEA prediction was examined.

resultsA pilot study with one femur revealed that the equations proposed by Keller for vertebra were the most reproducible for calculating Young's modulus and the yield stress of elements of the proximal femur. There was a good linear correlation between fracture loads of mechanical testing and FEA prediction (R

conclusionsCT-based specimen-specific FEA model of the proximal femur with small element size was validated using fresh frozen cadavers. The equations proposed by Keller for vertebra were found to be the most reproducible for the proximal femur in elderly people.

Indexed as

Weight-BearingAgedAged, 80 and overCadaverFemaleFemurFinite Element AnalysisForecastingFractures, BoneHumansMalePilot ProjectsTomography, X-Ray ComputedFinite element analysisFresh frozen cadaverOsteoporosisProximal femoral fractureValidation study

Identifiers

PMID29246133
PMCPMC5732520
OpenAlexW2771334500

What OpenQuestion holds

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LicenceCC BY
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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.